cphmd.bib

@ARTICLE{Humphrey_Schulten_1996_J.Mol.Graph.,
  title    = {{VMD}: visual molecular dynamics},
  author   = {Humphrey, W and Dalke, A and Schulten, K},
  abstract = {VMD is a molecular graphics program designed for the display and
              analysis of molecular assemblies, in particular biopolymers such
              as proteins and nucleic acids. VMD can simultaneously display any
              number of structures using a wide variety of rendering styles and
              coloring methods. Molecules are displayed as one or more
              ``representations,'' in which each representation embodies a
              particular rendering method and coloring scheme for a selected
              subset of atoms. The atoms displayed in each representation are
              chosen using an extensive atom selection syntax, which includes
              Boolean operators and regular expressions. VMD provides a
              complete graphical user interface for program control, as well as
              a text interface using the Tcl embeddable parser to allow for
              complex scripts with variable substitution, control loops, and
              function calls. Full session logging is supported, which produces
              a VMD command script for later playback. High-resolution raster
              images of displayed molecules may be produced by generating input
              scripts for use by a number of photorealistic image-rendering
              applications. VMD has also been expressly designed with the
              ability to animate molecular dynamics (MD) simulation
              trajectories, imported either from files or from a direct
              connection to a running MD simulation. VMD is the visualization
              component of MDScope, a set of tools for interactive problem
              solving in structural biology, which also includes the parallel
              MD program NAMD, and the MDCOMM software used to connect the
              visualization and simulation programs. VMD is written in C++,
              using an object-oriented design; the program, including source
              code and extensive documentation, is freely available via
              anonymous ftp and through the World Wide Web.},
  journal  = {J. Mol. Graph.},
  volume   =  14,
  number   =  1,
  pages    = {33-38},
  month    =  feb,
  year     =  1996,
  language = {en},
  doi      = {10.1016/0263-7855(96)00018-5}
}

@ARTICLE{Roe_Thomas_2013_J.Chem.TheoryComput.,
  title     = {{PTRAJ} and {CPPTRAJ}: Software for Processing and Analysis of
               Molecular Dynamics Trajectory Data},
  author    = {Roe, Daniel R and Cheatham, III, Thomas E},
  abstract  = {We describe PTRAJ and its successor    CPPTRAJ, two complementary,
               portable, and freely available computer programs for the
               analysis and processing of time series of three-dimensional
               atomic positions (i.e., coordinate trajectories) and the data
               therein derived. Common tools include the ability to manipulate
               the data to convert among trajectory formats, process groups of
               trajectories generated with ensemble methods (e.g., replica
               exchange molecular dynamics), image with periodic boundary
               conditions, create average structures, strip subsets of the
               system, and perform calculations such as RMS fitting, measuring
               distances, B-factors, radii of gyration, radial distribution
               functions, and time correlations, among other actions and
               analyses. Both the PTRAJ and CPPTRAJ programs and source code
               are freely available under the GNU General Public License
               version 3 and are currently distributed within the AmberTools 12
               suite of support programs that make up part of the Amber package
               of computer programs (see http://ambermd.org ). This overview
               describes the general design, features, and history of these two
               programs, as well as algorithmic improvements and new features
               available in CPPTRAJ.},
  journal   = {J. Chem. Theory Comput.},
  publisher = {ACS Publications},
  volume    =  9,
  number    =  7,
  pages     = {3084--3095},
  month     =  jul,
  year      =  2013,
  language  = {en},
  doi       = {10.1021/ct400341p}
}

@BOOK{Case_Kollman_2020,
  title     = "Amber 2020",
  author    = "Case, David A and Metin Aktulga, H and Belfon, Kellon and
               Ben-Shalom, Ido and Brozell, Scott R and Cerutti, David S and
               Cheatham, III, Thomas E and Cruzeiro, Vin{\'\i}cius Wilian D and
               Darden, Tom A and Duke, Robert E and Giambasu, George and
               Gilson, Michael K and Gohlke, Holger and Goetz, Andreas W and
               Harris, Robert and Izadi, Saeed and Izmailov, Sergei A and Jin,
               Chi and Kasavajhala, Koushik and Kaymak, Mehmet C and King,
               Edward and Kovalenko, Andriy and Kurtzman, Tom and Lee, Taisung
               and LeGrand, Scott and Li, Pengfei and Lin, Charles and Liu,
               Jian and Luchko, Tyler and Luo, Ray and Machado, Matias and Man,
               Viet and Manathunga, Madushanka and Merz, Kenneth M and Miao,
               Yinglong and Mikhailovskii, Oleg and Monard, G{\'e}rald and
               Nguyen, Hai and O'Hearn, Kurt A and Onufriev, Alexey and Pan,
               Feng and Pantano, Sergio and Qi, Ruxi and Rahnamoun, Ali and
               Roe, Daniel R and Roitberg, Adrian and Sagui, Celeste and
               Schott-Verdugo, Stephan and Shen, Jana and Simmerling, Carlos L
               and Skrynnikov, Nikolai R and Smith, Jamie and Swails, Jason and
               Walker, Ross C and Wang, Junmei and Wei, Haixin and Wolf, Romain
               M and Wu, Xiongwu and Xue, Yi and York, Darrin M and Zhao, Shiji
               and Kollman, Peter A",
  abstract  = "Amber is the collective name for a suite of programs that allow
               users to carry out molecular dynamics simulations, particularly
               on biomolecules. None of the individual programs carries this
               name, but the various parts work reasonably well together, and
               provide a powerful framework for many common calculations. The
               term Amber is also used to refer to the empirical force fields
               that are implemented here. It should be recognized, however,
               that the code and force field are separate: several other
               computer packages have implemented the Amber force fields, and
               other force fields can be implemented with the Amber programs.
               Further, the force fields are in the public domain, whereas the
               codes are distributed under a license agreement.The Amber
               software suite is divided into two parts: AmberTools21, a
               collection of freely available programs mostly under the GPL
               license, and Amber20, which is centered around the pmemd
               simulation program, and which continues to be licensed as
               before, under a more restrictive license. Amber20 represents a
               significant change from the most recent previous version,
               Amber18. (We have moved to numbering Amber releases by the last
               two digits of the calendar year, so there are no odd-numbered
               versions.) Please see https://ambermd.org for an overview of the
               most important changes.AmberTools is a set of programs for
               biomolecular simulation and analysis. They are designed to work
               well with each other, and with the ``regular'' Amber suite of
               programs. You can perform many simulation tasks with AmberTools,
               and you can do more extensive simulations with the combination
               of AmberTools and Amber itself. Most components of AmberTools
               are released under the GNU General Public License (GPL). A few
               components are in the public domain or have other open-source
               licenses. See the README file for more information.",
  publisher = "University of California, San Francisco",
  month     =  jun,
  year      =  2021,
  language  = "en"
}

@ARTICLE{Phillips_Tajkhorshid_2020_J.Chem.Phys.,
  title    = "Scalable molecular dynamics on {CPU} and {GPU} architectures with
              {NAMD}",
  author   = "Phillips, James C and Hardy, David J and Maia, Julio D C and
              Stone, John E and Ribeiro, Jo{\~a}o V and Bernardi, Rafael C and
              Buch, Ronak and Fiorin, Giacomo and H{\'e}nin, J{\'e}r{\^o}me and
              Jiang, Wei and McGreevy, Ryan and Melo, Marcelo C R and Radak,
              Brian K and Skeel, Robert D and Singharoy, Abhishek and Wang, Yi
              and Roux, Beno{\^\i}t and Aksimentiev, Aleksei and
              Luthey-Schulten, Zaida and Kal{\'e}, Laxmikant V and Schulten,
              Klaus and Chipot, Christophe and Tajkhorshid, Emad",
  abstract = "NAMDis a molecular dynamics program designed for high-performance
              simulations of very large biological objects on CPU- and
              GPU-based architectures. NAMD offers scalable performance on
              petascale parallel supercomputers consisting of hundreds of
              thousands of cores, as well as on inexpensive commodity clusters
              commonly found in academic environments. It is written in C++ and
              leans on Charm++ parallel objects for optimal performance on
              low-latency architectures. NAMD is a versatile, multipurpose code
              that gathers state-of-the-art algorithms to carry out simulations
              in apt thermodynamic ensembles, using the widely popular CHARMM,
              AMBER, OPLS, and GROMOS biomolecular force fields. Here, we
              review the main features of NAMD that allow both equilibrium and
              enhanced-sampling molecular dynamics simulations with numerical
              efficiency. We describe the underlying concepts utilized by NAMD
              and their implementation, most notably for handling long-range
              electrostatics; controlling the temperature, pressure, and pH;
              applying external potentials on tailored grids; leveraging
              massively parallel resources in multiple-copy simulations; and
              hybrid quantum-mechanical/molecular-mechanical descriptions. We
              detail the variety of options offered by NAMD for
              enhanced-sampling simulations aimed at determining free-energy
              differences of either alchemical or geometrical transformations
              and outline their applicability to specific problems. Last, we
              discuss the roadmap for the development of NAMD and our current
              efforts toward achieving optimal performance on GPU-based
              architectures, for pushing back the limitations that have
              prevented biologically realistic billion-atom objects to be
              fruitfully simulated, and for making large-scale simulations less
              expensive and easier to set up, run, and analyze. NAMD is
              distributed free of charge with its source code at
              www.ks.uiuc.edu.",
  journal  = "J. Chem. Phys.",
  volume   =  153,
  number   =  4,
  pages    = "044130",
  month    =  jul,
  year     =  2020,
  language = "en",
  doi       ={10.1063/5.0014475}
}

@ARTICLE{Abraham_Lindahl_2015_SoftwareX,
  title    = {{GROMACS}: High performance molecular simulations through
              multi-level parallelism from laptops to supercomputers},
  author   = {Abraham, Mark James and Murtola, Teemu and Schulz, Roland and
              P{\'a}ll, Szil{\'a}rd and Smith, Jeremy C and Hess, Berk and
              Lindahl, Erik},
  abstract = {GROMACS is one of the most widely used open-source and free
              software codes in chemistry, used primarily for dynamical
              simulations of biomolecules. It provides a rich set of
              calculation types, preparation and analysis tools. Several
              advanced techniques for free-energy calculations are supported.
              In version 5, it reaches new performance heights, through several
              new and enhanced parallelization algorithms. These work on every
              level; SIMD registers inside cores, multithreading, heterogeneous
              CPU--GPU acceleration, state-of-the-art 3D domain decomposition,
              and ensemble-level parallelization through built-in replica
              exchange and the separate Copernicus framework. The latest
              best-in-class compressed trajectory storage format is supported.},
  journal  = {SoftwareX},
  volume   = {1-2},
  pages    = {19-25},
  month    =  sep,
  year     =  2015,
  doi       = {10.1016/j.softx.2015.06.001}
}

@Article{     Henderson_Shen_2021_J.Chem.Inf.Model.,
  title     = {Exploring the Catalytic Dyad Protonation States and Flap Dynamics of Malarial Plasmepsin II},
  author    = {Henderson, Jack A. and Shen, Jana},
  year      = {2021},
  volume    = {62},
  issue     = {1},
  pages     = {150--158},
  journal	= {J. Chem. Inf. Model.},
  language	= {en},
  doi       = {10.1021/acs.jcim.1c01180}
}

@Article{	  Chen_Khandogin_2008_Curr.Opin.Struct.Biol.,
  title		= {Recent Advances in Implicit Solvent-Based Methods for
		  Biomolecular Simulations},
  author	= {Chen, Jianhan and {Brooks III}, Charles L. and Khandogin, Jana},
  year		= {2008},
  month		= apr,
  journal	= {Curr. Opin. Struct. Biol.},
  volume	= {18},
  number	= {2},
  pages		= {140--148},
  issn		= {0959440X},
  doi		= {10.1016/j.sbi.2008.01.003},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/3RYS9GNK/Chen et al. - 2008 -
		  Recent advances in implicit solvent-based methods .pdf}
}

@Article{	  Chen_Shen_2013_Biophys.J.,
  title		= {Introducing {{Titratable Water}} to {{All}}-{{Atom
		  Molecular Dynamics}} at {{Constant pH}}},
  author	= {Chen, Wei and Wallace, Jason A. and Yue, Zhi and Shen,
		  Jana K.},
  year		= {2013},
  month		= aug,
  journal	= {Biophys. J.},
  volume	= {105},
  number	= {4},
  pages		= {L15-L17},
  issn		= {00063495},
  doi		= {10.1016/j.bpj.2013.06.036},
  abstract	= {Recent development of titratable coions has paved the way
		  for realizing all-atom molecular dynamics at constant pH.
		  To further improve physical realism, here we describe a
		  technique in which proton titration of the solute is
		  directly coupled to the interconversion between water and
		  hydroxide or hydronium. We test the new method in
		  replica-exchange continuous constant pH molecular dynamics
		  simulations of three proteins, HP36, BBL, and HEWL. The
		  calculated pKa values based on 10-ns sampling per replica
		  have the average absolute and root-mean-square errors of
		  0.7 and 0.9 pH units, respectively. Introducing titratable
		  water in molecular dynamics offers a means to model proton
		  exchange between solute and solvent, thus opening a door to
		  gaining new insights into the intricate details of
		  biological phenomena involving proton translocation.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/ZI4ISDHV/Chen_BiophysJ_2013_v105_pL15.pdf}
}

@Article{	  Chen_Shen_2014_Mol.Simulat.,
  title		= {Recent Development and Application of Constant {{pH}}
		  Molecular Dynamics},
  author	= {Chen, Wei and Morrow, Brian H. and Shi, Chuanyin and Shen,
		  Jana K.},
  year		= {2014},
  month		= aug,
  journal	= {Mol. Simulat.},
  volume	= {40},
  number	= {10-11},
  pages		= {830--838},
  issn		= {0892-7022, 1029-0435},
  doi		= {10.1080/08927022.2014.907492},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/2IFPDKHQ/Chen et al. - 2014 -
		  Recent development and application of constant pH .pdf}
}

@Article{	  Chen_Shen_2016_J.Phys.Chem.Lett.,
  title		= {Conformational {{Activation}} of a {{Transmembrane Proton
		  Channel}} from {{Constant pH Molecular Dynamics}}},
  author	= {Chen, Wei and Huang, Yandong and Shen, Jana},
  year		= {2016},
  month		= oct,
  journal	= {J. Phys. Chem. Lett.},
  volume	= {7},
  number	= {19},
  pages		= {3961--3966},
  issn		= {1948-7185},
  doi		= {10.1021/acs.jpclett.6b01853},
  abstract	= {Proton-coupled transmembrane proteins play important roles
		  in human health and diseases; however, detailed mechanisms
		  are often elusive. Experimentally resolving proton
		  positions and structural details is challenging, and
		  conventional molecular dynamics simulations are performed
		  with preassigned and fixed protonation states. To address
		  this challenge, here we illustrate the use of the
		  state-of-the-art continuous constant pH molecular dynamics
		  (CpHMD) to directly describe the activation of the M2
		  channel of influenza virus, for which abundant experimental
		  data are available. Starting from the closed crystal
		  structure, simulation reveals a pH-dependent conformational
		  switch to an activated state that resembles the open
		  crystal structure. Importantly, simulation affords the free
		  energy of channel opening coupled to the titration of a
		  histidine tetrad, thereby providing a thermodynamic
		  mechanism for M2 activation, that is consistent with NMR
		  data and resolves the controversy with crystal structures
		  obtained at different pH values. This work illustrates the
		  utility of CpHMD in offering previously unattainable
		  conformational details and thermodynamic information for
		  proton-coupled transmembrane channels and transporters.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/U39NRT78/Chen_JPhysChemLett_2016_v7_p3961.pdf}
}

@Article{	  Contessoto_Leite_2016_J.Chem.TheoryComput.,
  title		= {{{NTL9 Folding}} at {{Constant pH}}: {{The Importance}} of
		  {{Electrostatic Interaction}} and {{pH Dependence}}},
  shorttitle	= {{{NTL9 Folding}} at {{Constant pH}}},
  author	= {Contessoto, Vin{\'i}cius G. and {de Oliveira},
		  Vin{\'i}cius M. and {de Carvalho}, Sidney J. and Oliveira,
		  Leandro C. and Leite, Vitor B. P.},
  year		= {2016},
  month		= jul,
  journal	= {J. Chem. Theory Comput.},
  volume	= {12},
  number	= {7},
  pages		= {3270--3277},
  publisher	= {{American Chemical Society}},
  issn		= {1549-9618},
  doi		= {10.1021/acs.jctc.6b00399},
  abstract	= {The folding process of the N-terminal domain of ribosomal
		  protein L9 (NTL9) was investigated at constant-pH computer
		  simulations. Evaluation of the role of electrostatic
		  interaction during folding was carried out by including a
		  Debye\textendash H\"uckel potential into a C{$\alpha$}
		  structure-based model (SBM). In this study, the charges of
		  the ionizable residues and the electrostatic potential are
		  susceptible to the solution conditions, such as pH and
		  ionic strength, as well as to the presence of charged
		  groups. Simulations were performed under different pHs, and
		  the results were validated by comparing them with
		  experimental values of pKa and with denaturation experiment
		  data. Also, the free energy profiles, {$\Phi$}-values, and
		  folding routes were calculated for each condition. It was
		  shown how charges vary along the folding under different
		  pH, which is subject to different scenarios. This study
		  reveals how simplified models can capture essential
		  physical features, reproducing experimental results, and
		  presenting the role of electrostatic interactions before,
		  during, and after the transition state.}
}

@Article{	  Cote_Shen_2014_J.Phys.Chem.C,
  title		= {Mechanism of the {{pH}}-{{Controlled Self}}-{{Assembly}}
		  of {{Nanofibers}} from {{Peptide Amphiphiles}}},
  author	= {Cote, Yoann and Fu, Iris W. and Dobson, Eric T. and
		  Goldberger, Joshua E. and Nguyen, Hung D. and Shen, Jana
		  K.},
  year		= {2014},
  month		= jul,
  journal	= {J. Phys. Chem. C},
  volume	= {118},
  number	= {29},
  pages		= {16272--16278},
  issn		= {1932-7447, 1932-7455},
  doi		= {10.1021/jp5048024},
  abstract	= {Stimuli-responsive, self-assembling nanomaterials hold a
		  great promise to revolutionize medicine and technology.
		  However, current discovery is slow and often serendipitous.
		  Here we report a multiscale modeling study to elucidate the
		  pH-controlled self-assembly of nanofibers from the peptide
		  amphiphiles, palmitoyl-I-A3E4-NH2. The coarse-grained
		  simulations revealed the formation of random-coil based
		  spherical micelles at strong electrostatic repulsion.
		  However, at weak or no electrostatic repulsion, the
		  micelles merge into a nanofiber driven by the
		  {$\beta$}-sheet formation between the peptide segments. The
		  all-atom constant pH molecular dynamics revealed a
		  cooperative transition between random coil and
		  {$\beta$}-sheet in the pH range 6-7, matching the CD data.
		  Interestingly, although the bulk pKa is more than one unit
		  below the transition pH, consistent with the titration
		  data, the highest pKa's coincide with the transition pH,
		  suggesting that the latter may be tuned by modulating the
		  pKa's of a few solvent-buried Glu side chains. Together,
		  these data offer, to our best knowledge, the first
		  multiresolution and quantitative view of the pH-dependent
		  self-assembly of nanofibers. The novel protocols and
		  insights gained are expected to advance the computer-aided
		  design and discovery of pH-responsive nanomaterials.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/9D8ZPK2N/Cote et al. - 2014 -
		  Mechanism of the pH-Controlled Self-Assembly of Na.pdf}
}

@Article{	  Ellis_Shen_2015_J.Am.Chem.Soc.,
  title		= {{{pH}}-{{Dependent Population Shift Regulates BACE1
		  Activity}} and {{Inhibition}}},
  author	= {Ellis, Christopher R. and Shen, Jana},
  year		= {2015},
  month		= aug,
  journal	= {J. Am. Chem. Soc.},
  volume	= {137},
  number	= {30},
  pages		= {9543--9546},
  issn		= {0002-7863, 1520-5126},
  doi		= {10.1021/jacs.5b05891},
  abstract	= {BACE1, a major therapeutic target for treatment of
		  Alzheimer's disease, functions within a narrow pH range.
		  Despite tremendous effort and progress in the development
		  of BACE1 inhibitors, details of the underlying pH-dependent
		  regulatory mechanism remain unclear. Here we elucidate the
		  pH-dependent conformational mechanism that regulates BACE1
		  activity using continuous constant-pH molecular dynamics
		  (MD). The simulations reveal that BACE1 mainly occupies
		  three conformational states and that the relative
		  populations of the states shift according to pH. At
		  intermediate pH, when the catalytic dyad is monoprotonated,
		  a binding-competent state is highly populated, while at low
		  and high pH a Tyr-inhibited state is dominant. Our data
		  provide strong evidence supporting conformational selection
		  as a major mechanism for substrate and peptide-inhibitor
		  binding. These new insights, while consistent with
		  experiment, greatly extend the knowledge of BACE1 and have
		  implications for further optimization of inhibitors and
		  understanding potential side effects of targeting BACE1.
		  Finally, the work highlights the importance of properly
		  modeling protonation states in MD simulations.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/P9JD9GK3/Ellis and Shen - 2015
		  - pH-Dependent Population Shift Regulates BACE1 Acti.pdf}
}

@Article{	  Ellis_Shen_2016_J.Phys.Chem.Lett.,
  title		= {Constant {{pH Molecular Dynamics Reveals pH}}-Modulated
		  {{Binding}} of {{Two Small}}-{{Molecule BACE1
		  Inhibitors}}},
  author	= {Ellis, Christopher R. and Tsai, Cheng-Chieh and Hou,
		  Xinjun and Shen, Jana},
  year		= {2016},
  month		= mar,
  journal	= {J. Phys. Chem. Lett.},
  volume	= {7},
  number	= {6},
  pages		= {944--949},
  issn		= {1948-7185},
  doi		= {10.1021/acs.jpclett.6b00137},
  abstract	= {Targeting BACE1 with small-molecule inhibitors offers a
		  promising route for treatment of Alzheimer's disease.
		  However, the intricate pH dependence of BACE1 function and
		  inhibitor efficacy has posed major challenges for
		  structure-based drug design. Here we investigate two,
		  structurally similar BACE1 inhibitors that have
		  dramatically different binding affinity and inhibitory
		  activity using continuous constant pH molecular dynamics
		  (CpHMD). At high pH, both inhibitors are stably bound to
		  BACE1, however, within the enzyme active pH range, only the
		  iminopyrimidinone-based inhibitor remains bound, while the
		  aminothiazine-based inhibitor becomes partially dissociated
		  following the loss of hydrogen bonding with the active site
		  and change of the 10s loop conformation. The drastically
		  lower affinity of the second inhibitor is due to the
		  protonation of a catalytic aspartate and the lack of a
		  propyne tail. This work demonstrates that CpHMD can be used
		  for screening pH-dependent binding profiles of
		  small-molecule inhibitors, providing a new tool for
		  structure-based drug design and optimization.},
  pmcid		= {PMC5713896},
  pmid		= {26905811},
  file		= {/Users/jana/Zotero/storage/XXXMPISY/Ellis et al. - 2016 -
		  Constant pH Molecular Dynamics Reveals pH-modulate.pdf}
}

@Article{	  Ellis_Shen_2017_J.Comput.Chem.,
  title		= {Conformational Dynamics of Cathepsin {{D}} and Binding to
		  a Small-Molecule {{BACE1}} Inhibitor},
  author	= {Ellis, Christopher R. and Tsai, Cheng-Chieh and Lin,
		  Fang-Yu and Shen, Jana},
  year		= {2017},
  month		= jun,
  journal	= {J. Comput. Chem.},
  volume	= {38},
  number	= {15},
  pages		= {1260--1269},
  issn		= {01928651},
  doi		= {10.1002/jcc.24719},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/ZKC9PPZU/Ellis et al. - 2017 -
		  Conformational dynamics of cathepsin D and binding.pdf}
}

@Article{	  Grunewald_Marrink_2020_J.Chem.Phys.,
  title		= {Titratable {{Martini}} Model for Constant {{pH}}
		  Simulations},
  author	= {Gr{\"u}newald, Fabian and Souza, Paulo C. T. and
		  Abdizadeh, Haleh and Barnoud, Jonathan and {de Vries}, Alex
		  H. and Marrink, Siewert J.},
  year		= {2020},
  month		= jul,
  journal	= {J. Chem. Phys.},
  volume	= {153},
  number	= {2},
  pages		= {024118},
  publisher	= {{American Institute of Physics}},
  issn		= {0021-9606},
  doi		= {10.1063/5.0014258}
}

@Article{	  Harris_Shen_2017_J.Phys.Chem.Lett.,
  title		= {Proton-{{Coupled Conformational Allostery Modulates}} the
		  {{Inhibitor Selectivity}} for {$\beta$}-{{Secretase}}},
  author	= {Harris, Robert C. and Tsai, Cheng-Chieh and Ellis,
		  Christopher R. and Shen, Jana},
  year		= {2017},
  month		= oct,
  journal	= {J. Phys. Chem. Lett.},
  volume	= {8},
  number	= {19},
  pages		= {4832--4837},
  issn		= {1948-7185},
  doi		= {10.1021/acs.jpclett.7b02309},
  abstract	= {Many important pharmaceutical targets, such as aspartyl
		  proteases and kinases, exhibit pH-dependent dynamics,
		  functions and inhibition. Accurate prediction of their
		  binding free energies is challenging because current
		  computational techniques neglect the effects of pH. Here we
		  combine free energy perturbation calculations with
		  continuous constant pH molecular dynamics to explore the
		  selectivity of a smallmolecule inhibitor for
		  {$\beta$}-secretase (BACE1), an important drug target for
		  Alzheimer's disease. The calculations predicted identical
		  affinity for BACE1 and the closely related cathepsin D at
		  high pH; however, at pH 4.6 the inhibitor is selective for
		  BACE1 by 1.3 kcal/mol, in excellent agreement with
		  experiment. Surprisingly, the pH-dependent selectivity can
		  be attributed to the protonation of His45, which
		  allosterically modulates a loop-inhibitor interaction.
		  Allosteric regulation induced by proton binding is likely
		  common in biology; considering such allosteric sites could
		  lead to exciting new opportunities in drug design.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/7TIBA2KV/Harris_JPhysChemLett_2017_v8_p4832.pdf}
}

@Article{	  Harris_Shen_2019_J.Chem.Inf.Model.,
  ids		= {Harris_Shen_2019_J.Chem.Inf.Model._4821a},
  title		= {{{GPU}}-{{Accelerated Implementation}} of {{Continuous
		  Constant pH Molecular Dynamics}} in {{Amber}}: {{pKa
		  Predictions}} with {{Single}}-{{pH Simulations}}},
  shorttitle	= {{{GPU}}-{{Accelerated Implementation}} of {{Continuous
		  Constant pH Molecular Dynamics}} in {{Amber}}},
  author	= {Harris, Robert C. and Shen, Jana},
  year		= {2019},
  month		= nov,
  journal	= {J. Chem. Inf. Model.},
  volume	= {59},
  number	= {11},
  pages		= {4821--4832},
  issn		= {1549-9596, 1549-960X},
  doi		= {10.1021/acs.jcim.9b00754},
  abstract	= {We present a GPU implementation of the continuous constant
		  pH molecular dynamics (CpHMD) based on the most recent
		  generalized Born implicit-solvent model in the pmemd engine
		  of the Amber molecular dynamics package. To test the
		  accuracy of the tool for rapid pKa predictions, a series of
		  2 ns single-pH simulations were performed for over 120
		  titratable residues in 10 benchmark proteins that were
		  previously used to test the various continuous CpHMD
		  methods. The calculated pKa's showed a root-mean-square
		  deviation of 0.80 and correlation coefficient of 0.83 with
		  respect to experiment. Also, 90\% of the pKa's were
		  converged with estimated errors below 0.1 pH units.
		  Surprisingly, this level of accuracy is similar to our
		  previous replica-exchange simulations with 2 ns per replica
		  and an exchange attempt frequency of 2 ps-1 (Huang, Harris,
		  and Shen J. Chem. Inf. Model. 2018, 58, 1372-1383).
		  Interestingly, for the linked titration sites in two
		  enzymes, although residuespecific protonation state
		  sampling in the single-pH simulations was not converged
		  within 2 ns, the protonation fraction of the linked
		  residues appeared to be largely converged, and the
		  experimental macroscopic pKa values were reproduced to
		  within 1 pH unit. Comparison with replica-exchange
		  simulations with different exchange attempt frequencies
		  showed that the splitting between the two macroscopic pKa's
		  is underestimated with frequent exchange attempts such as 2
		  ps-1, while single-pH simulations overestimate the
		  splitting. The same trend is seen for the single-pH vs
		  replica-exchange simulations of a hydrogenbonded aspartyl
		  dyad in a much larger protein. A 2 ns single-pH simulation
		  of a 400-residue protein takes about 1 h on a single NVIDIA
		  GeForce RTX 2080 graphics card, which is over 1000 times
		  faster than a CpHMD run on a single CPU core of a
		  highperformance computing cluster node. Thus, we envision
		  that GPU-accelerated continuous CpHMD may be used in
		  routine pKa predictions for a variety of applications, from
		  assisting MD simulations with protonation state assignment
		  to offering pHdependent corrections of binding free
		  energies and identifying reactive hot spots for covalent
		  drug design.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/JWHAPB6X/Harris and Shen - 2019
		  - GPU-Accelerated Implementation of Continuous
		  Const.pdf;/Users/jana/Zotero/storage/PXSUHGBI/Harris and
		  Shen - 2019 - GPU-Accelerated Implementation of Continuous
		  Const.pdf}
}

@Article{	  Harris_Shen_2020_J.Chem.TheoryComput.,
  title		= {Predicting {{Reactive Cysteines}} with
		  {{Implicit}}-{{Solvent}}-{{Based Continuous Constant pH
		  Molecular Dynamics}} in {{Amber}}},
  author	= {Harris, Robert C. and Liu, Ruibin and Shen, Jana},
  year		= {2020},
  month		= jun,
  journal	= {J. Chem. Theory Comput.},
  volume	= {16},
  number	= {6},
  pages		= {3689--3698},
  issn		= {1549-9618, 1549-9626},
  doi		= {10.1021/acs.jctc.0c00258},
  abstract	= {Cysteines existing in the deprotonated thiolate form or
		  having a tendency to become deprotonated are important
		  players in enzymatic and cellular redox functions and
		  frequently exploited in covalent drug design; however, most
		  computational studies assume cysteines as protonated. Thus,
		  developing an efficient tool that can make accurate and
		  reliable predictions of cysteine protonation states is
		  timely needed. We recently implemented a generalized Born
		  (GB) based continuous constant pH molecular dynamics
		  (CpHMD) method in Amber for protein pKa calculations on
		  CPUs and GPUs. Here we benchmark the performance of
		  GB-CpHMD for predictions of cysteine pKa's and reactivities
		  using a data set of 24 proteins with both down- and
		  upshifted cysteine pKa's. We found that 10 ns single-pH or
		  4 ns replica-exchange CpHMD titrations gave
		  root-mean-square errors of 1.2-1.3 and correlation
		  coefficients of 0.8-0.9 with respect to experiment. The
		  accuracy of predicting thiolates or reactive cysteines at
		  physiological pH with single-pH titrations is 86 or 81\%
		  with a precision of 100 or 90\%, respectively. This
		  performance well surpasses the traditional structure-based
		  methods, particularly a widely used empirical pKa tool that
		  gives an accuracy less than 50\%. We discuss simulation
		  convergence, dependence on starting structures, common
		  determinants of the pKa downshifts and upshifts, and the
		  origin of the discrepancies from the structure-based
		  calculations. Our work suggests that CpHMD titrations can
		  be performed on a desktop computer equipped with a single
		  GPU card to predict cysteine protonation states for a
		  variety of applications, from understanding biological
		  functions to covalent drug design.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/MWFT99NR/ct0c00258_si_001.pdf;/Users/jana/Zotero/storage/SWVHRGW6/Harris
		  et al. - 2020 - Predicting Reactive Cysteines with
		  Implicit-Solven.pdf}
}

@Article{	  Henderson_Shen_2018_J.Phys.Chem.Lett.,
  title		= {How {{Ligand Protonation State Controls Water}} in
		  {{Protein}}\textendash{{Ligand Binding}}},
  author	= {Henderson, Jack A. and Harris, Robert C. and Tsai,
		  Cheng-Chieh and Shen, Jana},
  year		= {2018},
  month		= sep,
  journal	= {J. Phys. Chem. Lett.},
  volume	= {9},
  number	= {18},
  pages		= {5440--5444},
  issn		= {1948-7185},
  doi		= {10.1021/acs.jpclett.8b02440},
  abstract	= {The role of water in protein-ligand binding has been an
		  intensely studied topic in recent years; however, how
		  ligand protonation state change perturbs water has not been
		  considered. Here we show that water dynamics and
		  interactions can be controlled by the protonation state of
		  ligand using continuous constant pH molecular dynamics
		  simulations of two closely related model systems,
		  {$\beta$}-secretase 1 and 2 (BACE1 and BACE2), in complex
		  with a small-molecule inhibitor. Simulations revealed that,
		  upon binding, the inhibitor pyrimidine ring remains
		  deprotonated in BACE1 but becomes protonated in BACE2.
		  Pyrimidine protonation results in water displacement,
		  rigidification of the binding pocket, and shift in the
		  ligand binding mode from water-mediated to direct hydrogen
		  bonding. These findings not only support but also
		  rationalize the most recent structure-selectivity data in
		  BACE1 drug design. Binding-induced protonation state
		  changes are likely common; our work offers a glimpse at how
		  modeling protein-ligand binding while allowing ligand
		  titration can further advance the understanding of water
		  and structure-based drug design.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/2A2DLC9J/Henderson et al. -
		  2018 - How Ligand Protonation State Controls Water in
		  Pro.pdf}
}

@Article{	  Henderson_Shen_2020_J.Chem.Phys.,
  title		= {Assessment of Proton-Coupled Conformational Dynamics of
		  {{SARS}} and {{MERS}} Coronavirus Papain-like Proteases:
		  {{Implication}} for Designing Broad-Spectrum Antiviral
		  Inhibitors},
  shorttitle	= {Assessment of Proton-Coupled Conformational Dynamics of
		  {{SARS}} and {{MERS}} Coronavirus Papain-like Proteases},
  author	= {Henderson, Jack A. and Verma, Neha and Harris, Robert C.
		  and Liu, Ruibin and Shen, Jana},
  year		= {2020},
  month		= sep,
  journal	= {J. Chem. Phys.},
  volume	= {153},
  number	= {11},
  pages		= {115101},
  issn		= {0021-9606, 1089-7690},
  doi		= {10.1063/5.0020458},
  abstract	= {Broad-spectrum antiviral drugs are urgently needed to stop
		  the Coronavirus Disease 2019 pandemic and prevent future
		  ones. The novel severe acute respiratory syndrome
		  coronavirus 2 (SARS-CoV-2) is related to the SARS-CoV and
		  Middle East respiratory syndrome coronavirus (MERS-CoV),
		  which have caused the previous outbreaks. The papain-like
		  protease (PLpro) is an attractive drug target due to its
		  essential roles in the viral life cycle. As a cysteine
		  protease, PLpro is rich in cysteines and histidines, and
		  their protonation/deprotonation modulates catalysis and
		  conformational plasticity. Here, we report the pKa
		  calculations and assessment of the proton-coupled
		  conformational dynamics of SARS-CoV-2 in comparison to
		  SARS-CoV and MERS-CoV PLpros using the recently developed
		  graphical processing unit (GPU)-accelerated
		  implicit-solvent continuous constant pH molecular dynamics
		  method with a new asynchronous replica-exchange scheme,
		  which allows computation on a single GPU card. The
		  calculated pKa's support the catalytic roles of the
		  Cys\textendash His\textendash Asp triad. We also found that
		  several residues can switch protonation states at
		  physiological pH among which is C270/271 located on the
		  flexible blocking loop 2 (BL2) of SARS-CoV-2/CoV PLpro.
		  Simulations revealed that the BL2 can open and close
		  depending on the protonation state of C271/270, consistent
		  with the most recent crystal structure evidence.
		  Interestingly, despite the lack of an analogous cysteine,
		  BL2 in MERS-CoV PLpro is also very flexible, challenging a
		  current hypothesis. These findings are supported by the
		  all-atom fixed-charge simulations and provide a starting
		  point for more detailed studies to assist the
		  structure-based design of broad-spectrum inhibitors against
		  CoV PLpros.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/5D6CJSKP/Henderson et al. -
		  2020 - Assessment of proton-coupled conformational
		  dynami.pdf}
}

@Article{	  Henderson_Shen_2020_Proc.Natl.Acad.Sci.USA,
  title		= {Alternative Proton-Binding Site and Long-Distance Coupling
		  in {{{\emph{Escherichia}}}}{\emph{ Coli}} Sodium\textendash
		  Proton Antiporter {{NhaA}}},
  author	= {Henderson, Jack A. and Huang, Yandong and Beckstein,
		  Oliver and Shen, Jana},
  year		= {2020},
  month		= oct,
  journal	= {Proc. Natl. Acad. Sci. USA},
  volume	= {117},
  number	= {41},
  pages		= {25517--25522},
  issn		= {0027-8424, 1091-6490},
  doi		= {10.1073/pnas.2005467117},
  abstract	= {Escherichia coli NhaA is a prototypical sodium\textendash
		  proton antiporter responsible for maintaining cellular ion
		  and volume homeostasis by exchanging two protons for one
		  sodium ion; despite two decades of research, the transport
		  mechanism of NhaA remains poorly understood. Recent crystal
		  structure and computational studies suggested Lys300 as a
		  second proton-binding site; however, functional
		  measurements of several K300 mutants demonstrated
		  electrogenic transport, thereby casting doubt on the role
		  of Lys300. To address the controversy, we carried out
		  state-of-the-art continuous constant pH molecular dynamics
		  simulations of NhaA mutants K300A, K300R, K300Q/D163N, and
		  K300Q/D163N/D133A. Simulations suggested that K300 mutants
		  maintain the electrogenic transport by utilizing an
		  alternative proton-binding residue Asp133. Surprisingly,
		  while Asp133 is solely responsible for binding the second
		  proton in K300R, Asp133 and Asp163 jointly bind the second
		  proton in K300A, and Asp133 and Asp164 jointly bind two
		  protons in K300Q/D163N. Intriguingly, the coupling between
		  Asp133 and Asp163 or Asp164 is enabled through the
		  proton-coupled hydrogen-bonding network at the flexible
		  intersection of two disrupted helices. These data resolve
		  the controversy and highlight the intricacy of the
		  compensatory transport mechanism of NhaA mutants.
		  Alternative proton-binding site and proton sharing between
		  distant aspartates may represent important general
		  mechanisms of proton-coupled transport in secondary active
		  transporters.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/Q3SMDBLT/Henderson et al. -
		  2020 - Alternative proton-binding site and long-distance
		  .pdf}
}

@Article{	  Huang_Shen_2016_J.Chem.TheoryComput.,
  title		= {All-{{Atom Continuous Constant pH Molecular Dynamics With
		  Particle Mesh Ewald}} and {{Titratable Water}}},
  author	= {Huang, Yandong and Chen, Wei and Wallace, Jason A. and
		  Shen, Jana},
  year		= {2016},
  month		= nov,
  journal	= {J. Chem. Theory Comput.},
  volume	= {12},
  number	= {11},
  pages		= {5411--5421},
  issn		= {1549-9618, 1549-9626},
  doi		= {10.1021/acs.jctc.6b00552},
  abstract	= {Development of a pH stat to properly control solution pH
		  in biomolecular simulations has been a longstanding goal in
		  the community. Toward this goal recent years have witnessed
		  the emergence of the so-called constant pH molecular
		  dynamics methods. However, the accuracy and generality of
		  these methods have been hampered by the use of
		  implicit-solvent models or truncation-based electrostatic
		  schemes. Here we report the implementation of the particle
		  mesh Ewald (PME) scheme into the all-atom continuous
		  constant pH molecular dynamics (CpHMD) method, enabling
		  CpHMD to be performed with a standard MD engine at a
		  fractional added computational cost. We demonstrate the
		  performance using pH replica-exchange CpHMD simulations
		  with titratable water for a stringent test set of proteins,
		  HP36, BBL, HEWL, and SNase. With the sampling time of 10 ns
		  per replica, most pKa's are converged, yielding the average
		  absolute and root-mean-square deviations of 0.61 and 0.77,
		  respectively, from experiment. Linear regression of the
		  calculated vs experimental pKa shifts gives a correlation
		  coefficient of 0.79, a slope of 1, and an intercept near 0.
		  Analysis reveals inadequate sampling of structure
		  relaxation accompanying a protonation-state switch as a
		  major source of the remaining errors, which are reduced as
		  simulation prolongs. These data suggest PME-based CpHMD can
		  be used as a general tool for pH-controlled simulations of
		  macromolecular systems in various environments, enabling
		  atomic insights into pH-dependent phenomena involving not
		  only soluble proteins but also transmembrane proteins,
		  nucleic acids, surfactants, and polysaccharides.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/IWZGSBHY/Huang_JChemTheoryComput_2016_v12_p5411.pdf}
}

@Article{	  Huang_Shen_2016_Nat.Commun.,
  title		= {Mechanism of {{pH}}-Dependent Activation of the
		  Sodium-Proton Antiporter {{NhaA}}},
  author	= {Huang, Yandong and Chen, Wei and Dotson, David L. and
		  Beckstein, Oliver and Shen, Jana},
  year		= {2016},
  month		= dec,
  journal	= {Nat. Commun.},
  volume	= {7},
  number	= {1},
  pages		= {12940},
  issn		= {2041-1723},
  doi		= {10.1038/ncomms12940},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/AV2LHZJQ/Huang et al. - 2016 -
		  Mechanism of pH-dependent activation of the sodium.pdf}
}

@Article{	  Huang_Shen_2018_J.Chem.Inf.Model.,
  title		= {Generalized {{Born Based Continuous Constant pH Molecular
		  Dynamics}} in {{Amber}}: {{Implementation}},
		  {{Benchmarking}} and {{Analysis}}},
  shorttitle	= {Generalized {{Born Based Continuous Constant pH Molecular
		  Dynamics}} in {{Amber}}},
  author	= {Huang, Yandong and Harris, Robert C. and Shen, Jana},
  year		= {2018},
  month		= jul,
  journal	= {J. Chem. Inf. Model.},
  volume	= {58},
  number	= {7},
  pages		= {1372--1383},
  issn		= {1549-9596, 1549-960X},
  doi		= {10.1021/acs.jcim.8b00227},
  abstract	= {Solution pH plays an important role in structure and
		  dynamics of biomolecular systems; however, pH effects
		  cannot be accurately accounted for in conventional
		  molecular dynamics simulations based on fixed protonation
		  states. Continuous constant pH molecular dynamics (CpHMD)
		  based on the {$\lambda$}-dynamics framework calculates
		  protonation states on the fly during dynamical simulation
		  at a specified pH condition. Here we report the CPU-based
		  implementation of the CpHMD method based on the GBNeck2
		  generalized Born (GB) implicit-solvent model in the pmemd
		  engine of the Amber molecular dynamics package. The
		  performance of the method was tested using pH
		  replicaexchange titration simulations of Asp, Glu and His
		  side chains in 4 miniproteins and 7 enzymes with
		  experimentally known pKa's, some of which are significantly
		  shifted from the model values. The added computational cost
		  due to CpHMD titration ranges from 11 to 33\% for the data
		  set and scales roughly linearly as the ratio between the
		  titrable sites and number of solute atoms. Comparison of
		  the experimental and calculated pKa's using 2 ns per
		  replica sampling yielded a mean unsigned error of 0.70, a
		  root-mean-squared error of 0.91, and a linear correlation
		  coefficient of 0.79. Though this level of accuracy is
		  similar to the GBSW-based CpHMD in CHARMM, in contrast to
		  the latter, the current implementation was able to
		  reproduce the experimental orders of the pKa's of the
		  coupled carboxylic dyads. We quantified the sampling
		  errors, which revealed that prolonged simulation is needed
		  to converge pKa's of several titratable groups involved in
		  salt-bridge-like interactions or deeply buried in the
		  protein interior. Our benchmark data demonstrate that
		  GBNeck2-CpHMD is an attractive tool for protein pKa
		  predictions.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/IH5RELFA/Huang_JChemInfModel_2018_v58_p1372.pdf}
}

@Article{	  Huang_Shen_2018_J.Phys.Chem.Lett.,
  title		= {Predicting {{Catalytic Proton Donors}} and
		  {{Nucleophiles}} in {{Enzymes}}: {{How Adding Dynamics
		  Helps Elucidate}} the {{Structure}}-{{Function
		  Relationships}}},
  author	= {Huang, Yandong and Yue, Zhi and Tsai, Cheng-Chieh and
		  Henderson, Jack A and Shen, Jana},
  year		= {2018},
  journal	= {J. Phys. Chem. Lett.},
  volume	= {9},
  pages		= {1179--1184},
  abstract	= {Despite the relevance of understanding structure-function
		  relationships, robust prediction of proton donors and
		  nucleophiles in enzyme active sites remains challenging.
		  Here we tested three types of state-of-the-art
		  computational methods to calculate the pKa's of the buried
		  and hydrogen bonded catalytic dyads in five enzymes. We
		  asked the question what determines the pKa order, i.e.,
		  what makes a residue proton donor vs a nucleophile. The
		  continuous constant pH molecular dynamics simulations
		  captured the experimental pKa orders and revealed that the
		  negative nucleophile is stabilized by increased hydrogen
		  bonding and solvent exposure as compared to the proton
		  donor. Surprisingly, this simple trend is not apparent from
		  crystal structures and the static structure-based
		  calculations. While the generality of the findings awaits
		  further testing via a larger set of data, they underscore
		  the role of dynamics in bridging enzyme structures and
		  functions.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/G4IG6ENJ/Huang_JPhysChemLett_2018_v9_p1179.pdf},
  doi       = {10.1021/acs.jpclett.8b00238}
}

@InCollection{	  Huang_Shen_2021_MethodsinMolecularBiology,
  title		= {Continuous Constant {{pH Molecular Dynamics Simulations}}
		  of {{Transmembrane Proteins}}},
  booktitle	= {Methods in {{Molecular Biology}}},
  author	= {Huang, Yandong and Henderson, Jack A. and Shen, Jana},
  year		= {2021},
  series	= {Structure and {{Function}} of {{Membrane Proteins}}},
  volume	= {2302},
  pages		= {275--287},
  publisher	= {{Springer}},
  address	= {{New York}},
  doi		= {10.1101/2020.08.06.239772},
  abstract	= {Many membrane channels, transporters, and receptors
		  utilize a pH gradient or proton coupling to drive
		  functionally relevant conformational transitions.
		  Conventional molecular dynamics simulations employ fixed
		  protonation states, thus neglecting the coupling between
		  protonation and conformational equilibria. Here we describe
		  the membraneenabled hybrid-solvent continuous constant pH
		  molecular dynamics method for capturing atomic details of
		  proton-coupled conformational dynamics of transmembrane
		  proteins. Example protocols from our recent application
		  studies of proton channels and ion/substrate transporters
		  are discussed.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/6JASEFBS/Huang et al. - 2020 -
		  Continuous constant pH Molecular Dynamics Simulati.pdf},
    doi     = {10.1007/978-1-0716-1394-8_15}
}

@Article{	  Khandogin_Brooks_2005_Biophys.J.,
  title		= {Constant {{pH Molecular Dynamics}} with {{Proton Tautomerism}}},
  author	= {Khandogin, Jana and Brooks, III, Charles L.},
  year		= {2005},
  month		= jul,
  journal	= {Biophys. J.},
  volume	= {89},
  number	= {1},
  pages		= {141--157},
  issn		= {00063495},
  doi		= {10.1529/biophysj.105.061341},
  abstract	= {The current article describes a new two-dimensional
		  l-dynamics method to include proton tautomerism in
		  continuous constant pH molecular dynamics (CPHMD)
		  simulations. The two-dimensional l-dynamics framework is
		  used to devise a tautomeric state titration model for the
		  CPHMD simulations involving carboxyl and histidine
		  residues. Combined with the GBSW implicit solvent model,
		  the new method is tested on titration simulations of
		  blocked histidine and aspartic acid as well as two
		  benchmark proteins, turkey ovomucoid third domain (OMTKY3)
		  and ribonuclease A (RNase A). A detailed analysis of the
		  errors inherent to the CPHMD methodology as well as those
		  due to the underlying solvation model is given. The average
		  absolute error for the computed pKa values in OMTKY3 is 1.0
		  pK unit. In RNase A the average absolute errors for the
		  carboxyl and histidine residues are 1.6 and 0.6 pK units,
		  respectively. In contrast to the previous work, the new
		  model predicts the correct sign for all the pKa shifts, but
		  one, in the benchmark proteins. The predictions of the
		  tautomeric states of His12 and His48 and the conformational
		  states of His48 and His119 are in agreement with
		  experiment. Based on the simulations of OMTKY3 and RNase A,
		  the current work has demonstrated the capability of the
		  CPHMD technique in revealing pH-coupled conformational
		  dynamics of protein side chains.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/44F2WRDW/Khandogin_BiophysJ_2005_v89_p141.pdf}
}

@Article{	  Khandogin_Brooks_2006_Biochemistry,
  title		= {Toward the {{Accurate First}}-{{Principles Prediction}} of
		  {{Ionization Equilibria}} in {{Proteins}}
		  {\textsuperscript{\textdagger}}},
  author	= {Khandogin, Jana and Brooks, III, Charles L.},
  year		= {2006},
  month		= aug,
  journal	= {Biochemistry},
  volume	= {45},
  number	= {31},
  pages		= {9363--9373},
  issn		= {0006-2960, 1520-4995},
  doi		= {10.1021/bi060706r},
  abstract	= {The calculation of pKa values for ionizable sites in
		  proteins has been traditionally based on numerical
		  solutions of the Poisson-Boltzmann equation carried out
		  using a high-resolution protein structure. In this paper,
		  we present a method based on continuous constant pH
		  molecular dynamics (CPHMD) simulations, which allows the
		  first-principles description of protein ionization
		  equilibria. Our method utilizes an improved generalized
		  Born implicit solvent model with an approximate
		  Debye-Hu\textasciidieresis ckel screening function to
		  account for salt effects and the replica-exchange (REX)
		  protocol for enhanced conformational and protonation state
		  sampling. The accuracy and robustness of the present method
		  are demonstrated by 1 ns REX-CPHMD titration simulations of
		  10 proteins, which exhibit anomalously large pKa shifts for
		  the carboxylate and histidine side chains. The experimental
		  pKa values of these proteins are reliably reproduced with a
		  root-mean-square error ranging from 0.6 unit for proteins
		  containing few buried ionizable side chains to 1.0 unit or
		  slightly higher for proteins containing ionizable side
		  chains deeply buried in the core and experiencing strong
		  charge-charge interactions. This unprecedented level of
		  agreement with experimental benchmarks for the de novo
		  calculation of pKa values suggests that the CPHMD method is
		  maturing into a practical tool for the quantitative
		  prediction of protein ionization equilibria, and this, in
		  turn, opens a door to atomistic simulations of a wide
		  variety of pH-coupled conformational phenomena in
		  biological macromolecules such as protein folding or
		  misfolding, aggregation, ligand binding, membrane
		  interaction, and catalysis.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/LRCINDTJ/Khandogin_Biochemistry_2006_v45_p9363.pdf}
}

@Article{	  Khandogin_Brooks_2006_Proc.Natl.Acad.Sci.USA,
  title		= {Exploring Atomistic Details of {{pH}}-Dependent Peptide
		  Folding},
  author	= {Khandogin, J. and Chen, J. and Brooks, III, C. L.},
  year		= {2006},
  month		= dec,
  journal	= {Proc. Natl. Acad. Sci. USA},
  volume	= {103},
  number	= {49},
  pages		= {18546--18550},
  issn		= {0027-8424, 1091-6490},
  doi		= {10.1073/pnas.0605216103},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/8JRU6PHW/Khandogin et al. -
		  2006 - Exploring atomistic details of pH-dependent
		  peptid.pdf}
}

@Article{	  Khandogin_Brooks_2007_J.Am.Chem.Soc.,
  title		= {Folding {{Intermediate}} in the {{Villin Headpiece Domain
		  Arises}} from {{Disruption}} of a {{N}}-{{Terminal
		  Hydrogen}}-{{Bonded Network}}},
  author	= {Khandogin, Jana and Raleigh, Daniel P. and Brooks, III, C.
		  L.},
  year		= {2007},
  month		= mar,
  journal	= {J. Am. Chem. Soc.},
  volume	= {129},
  number	= {11},
  pages		= {3056--3057},
  issn		= {0002-7863, 1520-5126},
  doi		= {10.1021/ja0688880},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/Q2IMNJGI/Khandogin et al. -
		  2007 - Folding Intermediate in the Villin Headpiece
		  Domai.pdf}
}

@Article{	  Khandogin_Brooks_2007_Proc.Natl.Acad.Sci.USA,
  title		= {Linking Folding with Aggregation in {{Alzheimer}}'s},
  author	= {Khandogin, Jana and Brooks, III, Charles L.},
  year		= {2007},
  journal	= {Proc. Natl. Acad. Sci. USA},
  volume	= {104},
  issue     = {43},
  pages		= {16880--16885},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/ZBB5KVQA/Khandogin and Iii -
		  Linking folding with aggregation in Alzheimer’s.pdf},
   doi      = {10.1073/pnas.0703832104}
}

@Article{	  Li_Payne_2019_Biofabrication,
  title		= {Electrobiofabrication: Electrically Based Fabrication with
		  Biologically Derived Materials},
  shorttitle	= {Electrobiofabrication},
  author	= {Li, Jinyang and Wu, Si and Kim, Eunkyoung and Yan, Kun and
		  Liu, Huan and Liu, Changsheng and Dong, Hua and Qu, Xue and
		  Shi, Xiaowen and Shen, Jana and Bentley, William E and
		  Payne, Gregory F},
  year		= {2019},
  month		= apr,
  journal	= {Biofabrication},
  volume	= {11},
  number	= {3},
  pages		= {032002},
  issn		= {1758-5090},
  doi		= {10.1088/1758-5090/ab06ea},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/QRJPDSX6/Li et al. - 2019 -
		  Electrobiofabrication electrically based fabricat.pdf}
}

@Article{	  Liu_Shen_2019_J.Am.Chem.Soc.,
  title		= {Assessing {{Lysine}} and {{Cysteine Reactivities}} for
		  {{Designing Targeted Covalent Kinase Inhibitors}}},
  author	= {Liu, Ruibin and Yue, Zhi and Tsai, Cheng-Chieh and Shen,
		  Jana},
  year		= {2019},
  month		= apr,
  journal	= {J. Am. Chem. Soc.},
  volume	= {141},
  number	= {16},
  pages		= {6553--6560},
  issn		= {0002-7863, 1520-5126},
  doi		= {10.1021/jacs.8b13248},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/IFYEITZ8/Liu_JAmChemSoc_2019_v141_p6553.pdf}
}

@Article{	  Liu_Shen_2021_J.Med.Chem.,
  title		= {Reactivities of the {{Front Pocket N}}-{{Cap Cysteines}}
		  in {{Human Kinases}}},
  author	= {Liu, Ruibin and Zhan, Shaoqi and Che, Ye and Shen, Jana},
  year		= {2021},
  month		= jun,
  journal	= {J. Med. Chem.},
  pages		= {In press},
  publisher	= {{Cold Spring Harbor Laboratory}},
  doi		= {10.1101/2021.06.28.450170},
  abstract	= {Discovery of targeted covalent inhibitors directed at
		  nucleophilic cysteines is attracting enormous interest. The
		  front pocket (FP) N-cap cysteine has been the most popular
		  site of covalent modification in kinases. Curiously, a
		  long-standing hypothesis associates the N-cap position with
		  cysteine hyper-reactivity; however, traditional
		  computational methods suggest that the FP N-cap cysteines
		  in all human kinases are predominantly unreactive at
		  physiological pH. Here we applied a newly developed
		  GPU-accelerated continuous constant pH molecular dynamics
		  (CpHMD) tool to test the N-cap hypothesis and elucidate the
		  cysteine reactivities. Simulations showed that the N-cap
		  cysteines in BTK/BMX/TEC/ITK/TXK, JAK3, and MKK7 sample the
		  reactive thiolate form to varying degrees at physiological
		  pH; however, those in BLK and EGFR/ERBB2/ERBB4 which
		  contain an Asp at the N-cap+3 position adopt the unreactive
		  thiol form. The latter argues in favor of the base-assisted
		  thiol-Michael addition mechanisms as suggested by the
		  quantum mechanical calculations and experimental
		  structure-function studies of EGFR inhibitors. Analysis
		  revealed that the reactive N-cap cysteines are stabilized
		  by hydrogen bond as well as electrostatic interactions, and
		  in their absence a N-cap cysteine is unreactive due to
		  desolvation. To test a corollary of the N-cap hypothesis,
		  we also examined the reactivities of the FP N-cap+2
		  cysteines in JNK1/JNK2/JNK3 and CASK. Additionally, our
		  simulations predicted the reactive cysteine and lysine
		  locations in all 15 kinases. Our findings offer a
		  systematic understanding of cysteine reactivities in
		  kinases and demonstrate the predictive power and physical
		  insights CpHMD can provide to guide the rational design of
		  targeted covalent inhibitors.},
  chapter	= {New Results},
  copyright	= {\textcopyright{} 2021, Posted by Cold Spring Harbor
		  Laboratory. This pre-print is available under a Creative
		  Commons License (Attribution 4.0 International), CC BY 4.0,
		  as described at
		  http://creativecommons.org/licenses/by/4.0/},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/PY2P73B4/Liu et al. - 2021 -
		  Reactivities of the Front Pocket N-Cap Cysteines
		  i.pdf;/Users/jana/Zotero/storage/ZVGRGT8G/2021.06.28.html}
}

@Article{	  Ma_Shen_2021_J.Chem.Inf.Model.,
  title		= {Exploring the {{pH}}-{{Dependent
		  Structure}}\textendash{{Dynamics}}\textendash{{Function
		  Relationship}} of {{Human Renin}}},
  author	= {Ma, Shuhua and Henderson, Jack A. and Shen, Jana},
  year		= {2021},
  month		= jan,
  journal	= {J. Chem. Inf. Model.},
  volume	= {61},
  number	= {1},
  pages		= {400--407},
  issn		= {1549-9596, 1549-960X},
  doi		= {10.1021/acs.jcim.0c01201},
  abstract	= {Renin is a pepsin-like aspartyl protease and an important
		  drug target for the treatment of hypertension; despite
		  three decades' research, its pH-dependent
		  structure-function relationship remains poorly understood.
		  Here, we employed continuous constant pH molecular dynamics
		  (CpHMD) simulations to decipher the acid/base roles of
		  renin's catalytic dyad and the conformational dynamics of
		  the flap, which is a common structural feature among
		  aspartyl proteases. The calculated pKa's suggest that
		  catalytic Asp38 and Asp226 serve as the general base and
		  acid, respectively, in agreement with experiment and
		  supporting the hypothesis that renin's neutral optimum pH
		  is due to the substrate-induced pKa shifts of the aspartic
		  dyad. The CpHMD data confirmed our previous hypothesis that
		  hydrogen bond formation is the major determinant of the
		  dyad pKa order. Additionally, our simulations showed that
		  renin's flap remains open regardless of pH, although a
		  Tyr-inhibited state is occasionally formed above pH 5.
		  These findings are discussed in comparison to the related
		  aspartyl proteases, including {$\beta$}-secretases 1 and 2,
		  cathepsin D, and plasmepsin II. Our work represents a first
		  step toward a systematic understanding of the pH-dependent
		  structure-dynamics- function relationships of pepsin-like
		  aspartyl proteases that play important roles in biology and
		  human disease states.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/KJZGMZZ8/Ma et al. - 2021 -
		  Exploring the pH-Dependent
		  Structure–Dynamics–Func.pdf}
}

@Article{	  Morrow_Shen_2011_J.Phys.Chem.B,
  title		= {Simulating {{pH Titration}} of a {{Single Surfactant}} in
		  {{Ionic}} and {{Nonionic Surfactant Micelles}}},
  author	= {Morrow, Brian H. and Wang, Yuhang and Wallace, Jason A.
		  and Koenig, Peter H. and Shen, Jana K.},
  year		= {2011},
  month		= dec,
  journal	= {J. Phys. Chem. B},
  volume	= {115},
  number	= {50},
  pages		= {14980--14990},
  issn		= {1520-6106, 1520-5207},
  doi		= {10.1021/jp2062404},
  abstract	= {Calculation of surfactant pKa's in micelles is a
		  challenging task using traditional electrostatic methods
		  due to the lack of structural data and information
		  regarding the effective dielectric constant. Here we test
		  the implicit- and hybridsolvent-based continuous constant
		  pH molecular dynamics (CpHMD) methods for predicting the
		  pKa shift of a lauric acid solubilized in three micelles:
		  dodecyl sulfate (DS), dodecyltrimethylammonium (DTA), and
		  dodecyltriethylene glycol ether (DE3). Both types of
		  simulations are able to reproduce the observed positive pKa
		  shifts for the anionic DS and nonionic DE3 micelles.
		  However, for the cationic DTA micelle, the implicit-solvent
		  simulation fails to predict the direction of the pKa shift,
		  while the hybrid-solvent simulation, where conformational
		  sampling is conducted in explicit solvent, is consistent
		  with experiment, although the specific-ion effects remain
		  to be accurately determined. Comparison between the
		  implicit- and hybridsolvent data shows that the latter
		  gives a more realistic description of the conformational
		  environment of the titrating probe. Surprisingly, in the
		  DTA micelle, surfactants are only slightly attracted to the
		  laurate ion, which diminishes the magnitude of the
		  electrostatic stabilization, resulting in a positive pKa
		  shift that cannot be explained by chemical intuition or
		  other theoretical models. Our data underscores the
		  importance of microscopic models and ionization-coupled
		  conformational dynamics in quantitative prediction of the
		  pKa shifts in micelles.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/8F9ABDL3/Morrow et al. - 2011 -
		  Simulating pH Titration of a Single Surfactant in .pdf}
}

@Article{	  Morrow_Shen_2012_J.Chem.Phys.,
  title		= {Atomistic Simulations of {{pH}}-Dependent Self-Assembly of
		  Micelle and Bilayer from Fatty Acids},
  author	= {Morrow, Brian H. and Koenig, Peter H. and Shen, Jana K.},
  year		= {2012},
  month		= nov,
  journal	= {J. Chem. Phys.},
  volume	= {137},
  number	= {19},
  pages		= {194902},
  issn		= {0021-9606, 1089-7690},
  doi		= {10.1063/1.4766313},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/PCSTWMNW/Morrow et al. - 2012 -
		  Atomistic simulations of pH-dependent self-assembl.pdf}
}

@Article{	  Morrow_Shen_2013_Langmuir,
  title		= {Self-{{Assembly}} and {{Bilayer}}\textendash{{Micelle
		  Transition}} of {{Fatty Acids Studied}} by
		  {{Replica}}-{{Exchange Constant pH Molecular Dynamics}}},
  author	= {Morrow, Brian H. and Koenig, Peter H. and Shen, Jana K.},
  year		= {2013},
  month		= dec,
  journal	= {Langmuir},
  volume	= {29},
  number	= {48},
  pages		= {14823--14830},
  issn		= {0743-7463, 1520-5827},
  doi		= {10.1021/la403398n},
  abstract	= {Recent interest in the development of surfactant-based
		  nanodelivery systems targeting tumor sites has sparked our
		  curiosity in understanding the detailed mechanism of the
		  self-assembly and phase transitions of pH-sensitive
		  surfactants. Toward this goal, we applied a
		  state-of-the-art simulation technique, continuous constant
		  pH molecular dynamics (CpHMD) with the hybrid-solvent
		  scheme and pH-based replica-exchange protocol, to study the
		  de novo self-assembly of 30 and 40 lauric acids, a simple
		  model titratable surfactant. We observed the formation of a
		  gel-state bilayer at low and intermediate pH and a
		  spherical micelle at high pH, with the phase transition
		  starting at 20-30\% ionization and being completed at 50\%.
		  The degree of cooperativity for the transition increases
		  from the 30-mer to the 40mer. The calculated apparent or
		  bulk pKa value is 7.0 for the 30-mer and 7.5 for the
		  40-mer. Congruent with experiment, these data demonstrate
		  that CpHMD is capable of accurately modeling large
		  conformational transitions of surfactant systems while
		  allowing the simultaneous proton titration of constituent
		  molecules. We suggest that CpHMD simulations may become a
		  useful tool in aiding in the design and development of
		  pH-sensitive nanocarriers for a variety of biomedical and
		  technological applications.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/G5CKZS46/Morrow et al. - 2013 -
		  Self-Assembly and Bilayer–Micelle Transition of Fa.pdf}
}

@Article{	  Morrow_Shen_2015_J.Am.Chem.Soc.,
  title		= {{{pH}}-{{Responsive Self}}-{{Assembly}} of
		  {{Polysaccharide}} through a {{Rugged Energy Landscape}}},
  author	= {Morrow, Brian H. and Payne, Gregory F. and Shen, Jana},
  year		= {2015},
  month		= oct,
  journal	= {J. Am. Chem. Soc.},
  volume	= {137},
  number	= {40},
  pages		= {13024--13030},
  issn		= {0002-7863, 1520-5126},
  doi		= {10.1021/jacs.5b07761},
  abstract	= {Self-assembling polysaccharides can form complex networks
		  with structures and properties highly dependent on the
		  sequence of triggering cues. Controlling the emergence of
		  such networks provides an opportunity to create soft matter
		  with unique features; however, it requires a detailed
		  understanding of the subtle balance between the attractive
		  and repulsive forces that drives the stimuli-induced
		  self-assembly. Here we employ all-atom molecular dynamics
		  simulations on the order of 100 ns to study the mechanisms
		  of the pHresponsive gelation of the weakly basic
		  aminopolysaccharide chitosan. We find that low pH induces a
		  sharp transition from gel to soluble state, analogous to
		  pH-dependent folding of proteins, while at neutral and high
		  pH self-assembly occurs via a rugged energy landscape,
		  reminiscent of RNA folding. A surprising role of salt is to
		  lubricate the conformational search for the
		  thermodynamically stable states. Although our simulations
		  represent the early events in the self-assembly process of
		  chitosan, which may take seconds or minutes to complete,
		  the atomically detailed insights are consistent with recent
		  experimental observations and provide a basis for
		  understanding how environmental conditions modulate the
		  structure and mechanical properties of the self-assembled
		  polysaccharide systems. The ability to control structure
		  and properties via modification of process conditions will
		  aid in the technological efforts to create complex soft
		  matter with applications ranging from bioelectronics to
		  regenerative medicine.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/P8LUGDF6/Morrow_JAmChemSoc_2015_v137_p13024.pdf}
}

@Article{	  Shen_Shen_2010_J.Am.Chem.Soc.,
  title		= {A {{Method To Determine Residue}}-{{Specific
		  Unfolded}}-{{State}} pKa
		  {{Values}} from {{Analysis}} of {{Stability Changes}} in
		  {{Single Mutant Cycles}}},
  author	= {Shen, Jana K.},
  year		= {2010},
  month		= jun,
  journal	= {J. Am. Chem. Soc.},
  volume	= {132},
  number	= {21},
  pages		= {7258--7259},
  issn		= {0002-7863, 1520-5126},
  doi		= {10.1021/ja101761m},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/TQEAGD87/Shen - 2010 - A Method
		  To Determine Residue-Specific Unfolded-St.pdf}
}

@Article{	  Shi_Shen_2012_Biophys.J.,
  title		= {Thermodynamic {{Coupling}} of {{Protonation}} and
		  {{Conformational Equilibria}} in {{Proteins}}: {{Theory}}
		  and {{Simulation}}},
  shorttitle	= {Thermodynamic {{Coupling}} of {{Protonation}} and
		  {{Conformational Equilibria}} in {{Proteins}}},
  author	= {Shi, Chuanyin and Wallace, Jason A. and Shen, Jana K.},
  year		= {2012},
  month		= apr,
  journal	= {Biophys. J.},
  volume	= {102},
  number	= {7},
  pages		= {1590--1597},
  issn		= {00063495},
  doi		= {10.1016/j.bpj.2012.02.021},
  abstract	= {Ionization-coupled conformational phenomena are ubiquitous
		  in biology. However, quantitative characterization of the
		  underlying thermodynamic cycle comprised of protonation and
		  conformational equilibria has remained an elusive goal.
		  Here we use theory and continuous constant pH molecular
		  dynamics (CpHMD) simulations to provide a thermodynamic
		  description for the coupling of proton titration and
		  conformational exchange between two distinct states of a
		  protein. CpHMD simulations with a hybrid-solvent scheme and
		  the pH-based replica-exchange (REX) protocol are applied to
		  obtain the equilibrium constants and atomic details of the
		  ionization-coupled conformational exchange between open and
		  closed states of an engineered mutant of staphylococcal
		  nuclease. Although the coupling of protonation and
		  conformational equilibria is not exact in the simulation,
		  the results are encouraging. They demonstrate that
		  REX-CpHMD simulations can be used to study thermodynamics
		  of ionization-coupled conformational processes\textemdash
		  which has not possible using present experimental
		  techniques or traditional simulations based on fixed
		  protonation states.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/7X244B64/Shi_BiophysJ_2012_v102_p1590.pdf}
}

@Article{	  Tsai_Shen_2018_Chem.Mater.,
  title		= {Exploring {{pH}}-{{Responsive}}, {{Switchable Crosslinking
		  Mechanisms}} for {{Programming Reconfigurable Hydrogels
		  Based}} on {{Aminopolysaccharides}}},
  author	= {Tsai, Cheng-Chieh and Payne, Gregory F. and Shen, Jana},
  year		= {2018},
  month		= dec,
  journal	= {Chem. Mater.},
  volume	= {30},
  number	= {23},
  pages		= {8597--8605},
  issn		= {0897-4756, 1520-5002},
  doi		= {10.1021/acs.chemmater.8b03753},
  abstract	= {Dynamic, stimuli-responsive, reconfigurable materials are
		  finding growing interest and applications. A recent
		  experiment (He et al., Adv Funct Matter., 2017)
		  demonstrated a pH-responsive, reconfigurable hydrogel film
		  based on a single biopolymer chitosan and two physical
		  cross-linking mechanisms. Here, we use state-of-the-art
		  molecular dynamics simulations to gain atomically detailed
		  insights into the three salient features of this
		  experimental system: (1) a pHresponsive switch between the
		  crystalline network junctions formed by intermolecular
		  hydrogen bonding between chitosan chains and electrostatic
		  cross-links based on sodium dodecyl sulfate (SDS) micelles;
		  (2) viscoelastic behavior of the SDScrosslinked network;
		  and (3) a stable but erasable gradient between the two
		  cross-linked regions. Our simulations showed that the
		  electrostatic cross-links are formed through the
		  pH-dependent salt-bridge interactions between the chitosan
		  glucosamines and SDS sulfates. Interestingly, the strength
		  and directionality of the salt-bridge interactions give
		  rise to complementary shape changes, despite the intrinsic
		  stiffness of the chitosan chain or the hydrophobic forces
		  that keep the micelle intact. Additionally, the salt-bridge
		  contacts display temporal and spatial dynamics, which
		  offers a microscopic explanation of the viscoelastic
		  properties of the SDS-crosslinked network. Another
		  significant finding is the pKa difference between the
		  chitosan crystallite and the SDS-bound chitosan chain,
		  which provides a physical origin for the persistent but
		  erasable gradient in the structural and mechanical
		  properties between the two cross-linked regions. pKa
		  gradients are integral to protein structures and functions;
		  our finding suggested that they may be important for
		  polysaccharides and broadly exploited for designing
		  pH-responsive, reconfigurable, complex, multifunctional
		  materials. Our work provides a glimpse at how modern
		  computer simulations can advance the understanding and
		  potentially guide the design of novel soft matter.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/XAYWPPZU/Tsai et al. - 2018 -
		  Exploring pH-Responsive, Switchable Crosslinking M.pdf}
}

@Article{	  Tsai_Shen_2019_J.Am.Chem.Soc.,
  title		= {How {{Electrostatic Coupling Enables Conformational
		  Plasticity}} in a {{Tyrosine Kinase}}},
  author	= {Tsai, Cheng-Chieh and Yue, Zhi and Shen, Jana},
  year		= {2019},
  month		= sep,
  journal	= {J. Am. Chem. Soc.},
  volume	= {141},
  number	= {38},
  pages		= {15092--15101},
  issn		= {0002-7863, 1520-5126},
  doi		= {10.1021/jacs.9b06064},
  abstract	= {Protein kinases are important cellular signaling molecules
		  involved in cancer and a multitude of other diseases. It is
		  well-known that inactive kinases display a remarkable
		  conformational plasticity; however, the molecular
		  mechanisms remain poorly understood. Conformational
		  heterogeneity presents an opportunity but also a challenge
		  in kinase drug discovery. The ability to predictively model
		  various conformational states could accelerate selective
		  inhibitor design. Here we performed a proton-coupled
		  molecular dynamics study to explore the conformational
		  landscape of a c-Src kinase. Starting from a completely
		  inactive structure, the simulations captured all major
		  types of conformational states without the use of a target
		  structure, mutation, or bias. The simulations allowed us to
		  test the experimental hypotheses regarding the mechanism of
		  DFG flip, its coupling to the {$\alpha$}Chelix movement,
		  and the formation of regulatory spine. Perhaps the most
		  significant finding is how key titratable residues, such as
		  DFG-Asp, {$\alpha$}C-Glu, and HRD-Asp, change protonation
		  states dependent on the DFG, {$\alpha$}C, and activation
		  loop conformations. Our data offer direct evidence to
		  support a long-standing hypothesis that protonation of Asp
		  favors the DFG-out state and explain why DFG flip is also
		  possible in simulations with deprotonated Asp. The
		  simulations also revealed intermediate states, among which
		  a unique DFG-out/{$\alpha$}-C state formed as DFG-Asp is
		  moved into a back pocket forming a salt bridge with
		  catalytic Lys, which can be tested in selective inhibitor
		  design. Our finding of how proton coupling enables the
		  remarkable conformational plasticity may shift the paradigm
		  of computational studies of kinases which assume fixed
		  protonation states. Understanding proton-coupled
		  conformational dynamics may hold a key to further
		  innovation in kinase drug discovery.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/YMUX7WDI/Tsai_JAmChemSoc_2019_v141_p15092.pdf}
}

@Article{	  Verma_Shen_2020_J.Am.Chem.Soc.,
  title		= {Proton-{{Coupled Conformational Activation}} of {{SARS
		  Coronavirus Main Proteases}} and {{Opportunity}} for
		  {{Designing Small}}-{{Molecule Broad}}-{{Spectrum Targeted
		  Covalent Inhibitors}}},
  author	= {Verma, Neha and Henderson, Jack A. and Shen, Jana},
  year		= {2020},
  month		= dec,
  journal	= {J. Am. Chem. Soc.},
  pages		= {21883-21890},
  issn		= {0002-7863, 1520-5126},
  doi		= {10.1021/jacs.0c10770},
  abstract	= {The SARS coronavirus 2 (SARS-CoV-2) main protease (Mpro)
		  is an attractive broad-spectrum antiviral drug target.
		  Despite the enormous progress in structure elucidation, the
		  Mpro's structure-function relationship remains poorly
		  understood. Recently, a peptidomimetic inhibitor has
		  entered clinical trial; however, small-molecule orally
		  available antiviral drugs have yet to be developed.
		  Intrigued by a long-standing controversy regarding the
		  existence of an inactive state, we explored the
		  proton-coupled dynamics of the Mpros of SARS-CoV-2 and the
		  closely related SARS-CoV using a newly developed continuous
		  constant pH molecular dynamics (MD) method and microsecond
		  fixed-charge all-atom MD simulations. Our data supports a
		  general base mechanism for Mpro's proteolytic function. The
		  simulations revealed that protonation of His172 alters a
		  conserved interaction network that upholds the oxyanion
		  loop, leading to a partial collapse of the conserved S1
		  pocket, consistent with the first and controversial crystal
		  structure of SARS-CoV Mpro determined at pH 6.
		  Interestingly, a natural flavonoid binds SARS-CoV-2 Mpro in
		  the close proximity to a conserved cysteine (Cys44), which
		  is hyper-reactive according to the CpHMD titration. This
		  finding offers an exciting new opportunity for
		  small-molecule targeted covalent inhibitor design. Our work
		  represents a first step toward the mechanistic
		  understanding of the proton-coupled structure-
		  dynamics-function relationship of CoV Mpros; the proposed
		  strategy of designing small-molecule covalent inhibitors
		  may help accelerate the development of orally available
		  broad-spectrum antiviral drugs to stop the current pandemic
		  and prevent future outbreaks.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/ILEC97FQ/Verma et al. - 2020 -
		  Proton-Coupled Conformational Activation of SARS
		  C.pdf;/Users/jana/Zotero/storage/ZNZGN4E9/Verma et al. -
		  Supporting Information Proton-Coupled Conformatio.pdf}
}

@Article{	  Vo_Ellis_2021_Nat.Commun.,
  title		= {How {$\mu$}-Opioid Receptor Recognizes Fentanyl},
  author	= {Vo, Quynh N. and Mahinthichaichan, Paween and Shen, Jana
		  and Ellis, Christopher R.},
  year		= {2021},
  month		= dec,
  journal	= {Nat. Commun.},
  volume	= {12},
  number	= {1},
  pages		= {984},
  issn		= {2041-1723},
  doi		= {10.1038/s41467-021-21262-9},
  abstract	= {Abstract Roughly half of the drug overdose-related deaths
		  in the United States are related to synthetic opioids
		  represented by fentanyl which is a potent agonist of
		  mu-opioid receptor (mOR). In recent years, X-ray crystal
		  structures of mOR in complex with morphine derivatives have
		  been determined; however, structural basis of mOR
		  activation by fentanyl-like opioids remains lacking.
		  Exploiting the X-ray structure of BU72-bound mOR and
		  several molecular simulation techniques, we elucidated the
		  detailed binding mechanism of fentanyl. Surprisingly, in
		  addition to the salt-bridge binding mode common to
		  morphinan opiates, fentanyl can move deeper and form a
		  stable hydrogen bond with the conserved His297 6.52 , which
		  has been suggested to modulate mOR's ligand affinity and pH
		  dependence by previous mutagenesis experiments.
		  Intriguingly, this secondary binding mode is only
		  accessible when His297 6.52 adopts a neutral HID tautomer.
		  Alternative binding modes may represent a general mechanism
		  in G protein-coupled receptor-ligand recognition.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/LGVIISXM/Vo et al. - 2021 - How
		  μ-opioid receptor recognizes fentanyl.pdf}
}

@InCollection{	  Wallace_Shen_2009_MethodsEnzymol.,
  title		= {Predicting {{pKa Values}} with {{Continuous Constant pH
		  Molecular Dynamics}}},
  booktitle	= {Methods {{Enzymol}}.},
  author	= {Wallace, Jason A. and Shen, Jana K.},
  year		= {2009},
  volume	= {466},
  pages		= {455--475},
  publisher	= {{Elsevier}},
  doi		= {10.1016/S0076-6879(09)66019-5},
  isbn		= {978-0-12-374776-1},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/LPYA3TI4/Wallace_MethodsEnzymol_2009_v466_p455.pdf}
}

@Article{	  Wallace_Shen_2011_J.Chem.TheoryComput.,
  ids		= {Wallace_Shen_2011_J.Chem.TheoryComput._2617c},
  title		= {Continuous {{Constant pH Molecular Dynamics}} in
		  {{Explicit Solvent}} with {{pH}}-{{Based Replica
		  Exchange}}},
  author	= {Wallace, Jason A. and Shen, Jana K.},
  year		= {2011},
  month		= aug,
  journal	= {J. Chem. Theory Comput.},
  volume	= {7},
  number	= {8},
  pages		= {2617--2629},
  issn		= {1549-9618, 1549-9626},
  doi		= {10.1021/ct200146j},
  abstract	= {A computational tool that offers accurate pKa values and
		  atomically detailed knowledge of protonation-coupled
		  conformational dynamics is valuable for elucidating
		  mechanisms of energy transduction processes in biology,
		  such as enzyme catalysis and electron transfer as well as
		  proton and drug transport. Toward this goal we present a
		  new technique of embedding continuous constant pH molecular
		  dynamics within an explicit-solvent representation. In this
		  technique we make use of the efficiency of the
		  generalized-Born (GB) implicit-solvent model for estimating
		  the free energy of protein solvation while propagating
		  conformational dynamics using the more accurate
		  explicit-solvent model. Also, we employ a pH-based replica
		  exchange scheme to significantly enhance both protonation
		  and conformational state sampling. Benchmark data of five
		  proteins including HP36, NTL9, BBL, HEWL, and SNase yield
		  an average absolute deviation of 0.53 and a root mean
		  squared deviation of 0.74 from experimental data. This
		  level of accuracy is obtained with 1 ns simulations per
		  replica. Detailed analysis reveals that explicit-solvent
		  sampling provides increased accuracy relative to the
		  previous GB-based method by preserving the native
		  structure, providing a more realistic description of
		  conformational flexibility of the hydrophobic cluster, and
		  correctly modeling solvent mediated ion-pair interactions.
		  Thus, we anticipate that the new technique will emerge as a
		  practical tool to capture ionization equilibria while
		  enabling an intimate view of ionization coupled
		  conformational dynamics that is difficult to delineate with
		  experimental techniques alone.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/4FF85ISB/Wallace and Shen -
		  2011 - Continuous Constant pH Molecular Dynamics in
		  Expli.pdf;/Users/jana/Zotero/storage/D5VL8H2X/Wallace_JChemTheoryComput_2011_v7_p2617.pdf}
}

@Article{	  Wallace_Shen_2011_Proteins,
  title		= {Toward Accurate Prediction of {{pKa}} Values for Internal
		  Protein Residues: {{The}} Importance of Conformational
		  Relaxation and Desolvation Energy},
  shorttitle	= {Toward Accurate Prediction of {{pKa}} Values for Internal
		  Protein Residues},
  author	= {Wallace, Jason A. and Wang, Yuhang and Shi, Chuanyin and
		  Pastoor, Kevin J. and Nguyen, Bao-Linh and Xia, Kai and
		  Shen, Jana K.},
  year		= {2011},
  month		= dec,
  journal	= {Proteins},
  volume	= {79},
  number	= {12},
  pages		= {3364--3373},
  issn		= {08873585},
  doi		= {10.1002/prot.23080},
  abstract	= {Proton uptake or release controls many important
		  biological processes, such as energy transduction, virus
		  replication, and catalysis. Accurate pKa prediction informs
		  about proton pathways, thereby revealing detailed acid-base
		  mechanisms. Physics-based methods in the framework of
		  molecular dynamics simulations not only offer pKa
		  predictions but also inform about the physical origins of
		  pKa shifts and provide details of ionization-induced
		  conformational relaxation and largescale transitions. One
		  such method is the recently developed continuous constant
		  pH molecular dynamics (CPHMD) method, which has been shown
		  to be an accurate and robust pKa prediction tool for
		  naturally occurring titratable residues. To further examine
		  the accuracy and limitations of CPHMD, we blindly predicted
		  the pKa values for 87 titratable residues introduced in
		  various hydrophobic regions of staphylococcal nuclease and
		  variants. The predictions gave a root-mean-square deviation
		  of 1.69 pK units from experiment, and there were only two
		  pKa's with errors greater than 3.5 pK units. Analysis of
		  the conformational fluctuation of titrating side-chains in
		  the context of the errors of calculated pKa values indicate
		  that explicit treatment of conformational flexibility and
		  the associated dielectric relaxation gives CPHMD a distinct
		  advantage. Analysis of the sources of errors suggests that
		  more accurate pKa predictions can be obtained for the most
		  deeply buried residues by improving the accuracy in
		  calculating desolvation energies. Furthermore, it is found
		  that the generalized Born implicit-solvent model underlying
		  the current CPHMD implementation slightly distorts the
		  local conformational environment such that the inclusion of
		  an explicit-solvent representation may offer improvement of
		  accuracy.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/B6QVRTAW/Wallace_Proteins_2011_v79_p3364.pdf}
}

@Article{	  Wallace_Shen_2012_J.Chem.Phys.,
  title		= {Charge-Leveling and Proper Treatment of Long-Range
		  Electrostatics in All-Atom Molecular Dynamics at Constant
		  {{pH}}},
  author	= {Wallace, Jason A. and Shen, Jana K.},
  year		= {2012},
  month		= nov,
  journal	= {J. Chem. Phys.},
  volume	= {137},
  number	= {18},
  pages		= {184105},
  issn		= {0021-9606, 1089-7690},
  doi		= {10.1063/1.4766352},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/ZEQJKKWT/Wallace_JChemPhys_2012_v137_p184105.pdf}
}

@Article{	  Wallace_Shen_2012_J.Phys.Chem.Lett.,
  title		= {Unraveling a {{Trap}}-and-{{Trigger Mechanism}} in the
		  {{pH}}-{{Sensitive Self}}-{{Assembly}} of {{Spider Silk
		  Proteins}}},
  author	= {Wallace, Jason A. and Shen, Jana K.},
  year		= {2012},
  month		= mar,
  journal	= {J. Phys. Chem. Lett.},
  volume	= {3},
  number	= {5},
  pages		= {658--662},
  issn		= {1948-7185},
  doi		= {10.1021/jz2016846},
  abstract	= {When the major ampullate spidroins (MaSp1) are called upon
		  to form spider dragline silk, one of nature's most amazing
		  materials, a small drop in pH must occur. Using a
		  state-ofthe-art simulation technique, constant pH molecular
		  dynamics, we discovered a few residues that respond to the
		  pH signal in the dimerization of the N-terminal domain
		  (NTD) of MaSp1, which is an integral step in the fiber
		  assembly. At neutral pH, the deprotonation of Glu79 and
		  Glu119 leads to water penetration and structural changes at
		  the monomer-monomer binding interface. At strongly acidic
		  pH, the protonation of Asp39 and Asp40 weakens the
		  electrostatic attraction between the monomers. Thus, we
		  propose a ``trap-and-trigger'' mechanism whereby the
		  intermolecular salt bridges at physiologically relevant pH
		  conditions always act as a stabilizing ``trap'' favoring
		  dimerization. As the pH is lowered to about 6, Glu79 and
		  Glu119 become protonated, triggering the dimerization and
		  subsequent silk formation. We speculate that this type of
		  mechanism is operative in many other pH-sensitive
		  biological processes.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/MV82YYIF/Wallace and Shen -
		  2012 - Unraveling a Trap-and-Trigger Mechanism in the
		  pH-.pdf}
}

@Article{	  Yue_Shen_2017_J.Chem.TheoryComput.,
  title		= {Constant {{pH Molecular Dynamics Reveals How Proton
		  Release Drives}} the {{Conformational Transition}} of a
		  {{Transmembrane Efflux Pump}}},
  author	= {Yue, Zhi and Chen, Wei and Zgurskaya, Helen I. and Shen,
		  Jana},
  year		= {2017},
  month		= dec,
  journal	= {J. Chem. Theory Comput.},
  volume	= {13},
  number	= {12},
  pages		= {6405--6414},
  issn		= {1549-9618, 1549-9626},
  doi		= {10.1021/acs.jctc.7b00874},
  abstract	= {AcrB is the inner-membrane transporter of an E. coli
		  AcrAB-TolC tripartite efflux complex, which plays a major
		  role in the intrinsic resistance to clinically important
		  antibiotics. AcrB pumps a wide range of toxic substrates by
		  utilizing the proton gradient between periplasm and
		  cytoplasm. Crystal structures of AcrB revealed three
		  distinct conformational states of the transport cycle,
		  substrate access, binding, and extrusion or loose (L),
		  tight (T), and open (O) states. However, the specific
		  residue(s) responsible for proton binding/release and the
		  mechanism of proton-coupled conformational cycling remain
		  controversial. Here we use the newly developed membrane
		  hybrid-solvent continuous constant pH molecular dynamics
		  technique to explore the protonation states and
		  conformational dynamics of the transmembrane domain of
		  AcrB. Simulations show that both Asp407 and Asp408 are
		  deprotonated in the L/T states, while only Asp408 is
		  protonated in the O state. Remarkably, release of a proton
		  from Asp408 in the O state results in large conformational
		  changes, such as the lateral and vertical movement of
		  transmembrane helices as well as the salt-bridge formation
		  between Asp408 and Lys940 and other side chain
		  rearrangements among essential residues. Consistent with
		  the crystallographic differences between the O and L
		  protomers, simulations offer dynamic details of how proton
		  release drives the O-to-L transition in AcrB and address
		  the controversy regarding the proton/drug stoichiometry.
		  This work offers a significant step toward characterizing
		  the complete cycle of proton-coupled drug transport in AcrB
		  and further validates the membrane hybrid-solvent CpHMD
		  technique for studies of proton-coupled transmembrane
		  proteins which are currently poorly understood.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/T4RPRZHH/Yue_JChemTheoryComput_2017_v13_p6405.pdf}
}

@Article{	  Yue_Shen_2018_Phys.Chem.Chem.Phys.,
  title		= {{{pH}}-{{Dependent}} Cooperativity and Existence of a Dry
		  Molten Globule in the Folding of a Miniprotein {{BBL}}},
  author	= {Yue, Zhi and Shen, Jana},
  year		= {2018},
  journal	= {Phys. Chem. Chem. Phys.},
  volume	= {20},
  number	= {5},
  pages		= {3523--3530},
  issn		= {1463-9076, 1463-9084},
  doi		= {10.1039/C7CP08296G},
  abstract	= {Constant pH molecular dynamics simulations of BBL reveals
		  negligible folding free energy barrier that is pH dependent
		  and a sparsely populated dry molten globule state. ,
		  Solution pH plays an important role in protein dynamics,
		  stability, and folding; however, detailed mechanisms remain
		  poorly understood. Here we use continuous constant pH
		  molecular dynamics in explicit solvent with pH replica
		  exchange to describe the pH profile of the folding
		  cooperativity of a miniprotein BBL, which has drawn intense
		  debate in the past. Our data reconciled the two opposing
		  hypotheses (downhill vs. two-state) and uncovered a
		  sparsely populated unfolding intermediate. As pH is lowered
		  from 7 to 5, the folding barrier vanishes. As pH continues
		  to decrease, the unfolding barrier lowers and denaturation
		  is triggered by the protonation of Asp162, consistent with
		  experimental evidence. Interestingly, unfolding proceeded
		  via an intermediate, with intact secondary structure and a
		  compact, unlocked hydrophobic core shielded from solvent,
		  lending support to the recent hypothesis of a universal dry
		  molten globule in protein folding. Our work demonstrates
		  that constant pH molecular dynamics is a unique tool for
		  testing this and other hypotheses to advance the knowledge
		  in protein dynamics, stability, and folding.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/VW5QMMQ7/Yue and Shen - 2018 -
		  pH-Dependent cooperativity and existence of a dry .pdf}
}

@Article{	  Anandakrishnan_Onufriev_2012_NucleicAcidsRes.,
  ids		= {Anandakrishnan_Onufriev_2012_NucleicAcidsRes.a},
  title		= {H++ 3.0: Automating {{pK}} Prediction and the Preparation
		  of Biomolecular Structures for Atomistic Molecular Modeling
		  and Simulations},
  shorttitle	= {H++ 3.0},
  author	= {Anandakrishnan, R. and Aguilar, B. and Onufriev, A. V.},
  year		= {2012},
  month		= jul,
  journal	= {Nucleic Acids Res.},
  volume	= {40},
  number	= {W1},
  pages		= {W537-W541},
  issn		= {0305-1048, 1362-4962},
  doi		= {10.1093/nar/gks375},
  abstract	= {The accuracy of atomistic biomolecular modeling and
		  simulation studies depend on the accuracy of the input
		  structures. Preparing these structures for an atomistic
		  modeling task, such as molecular dynamics (MD) simulation,
		  can involve the use of a variety of different tools for:
		  correcting errors, adding missing atoms, filling valences
		  with hydrogens, predicting pK values for titratable amino
		  acids, assigning predefined partial charges and radii to
		  all atoms, and generating force field parameter/topology
		  files for MD. Identifying, installing and effectively using
		  the appropriate tools for each of these tasks can be
		  difficult for novice and time-consuming for experienced
		  users. H++ (http:// biophysics.cs.vt.edu/) is a free
		  open-source web server that automates the above key steps
		  in the preparation of biomolecular structures for molecular
		  modeling and simulations. H++also performs extensive error
		  and consistency checking, providing error/ warning messages
		  together with the suggested corrections. In addition to
		  numerous minor improvements, the latest version of H++
		  includes several new capabilities and options: fix
		  erroneous (flipped) side chain conformations for HIS, GLN
		  and ASN, include a ligand in the input structure, process
		  nucleic acid structures and generate a solvent box with
		  specified number of common ions for explicit solvent MD.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/HGZCXFUK/Anandakrishnan et al.
		  - 2012 - H++ 3.0 automating pK prediction and the
		  preparat.pdf;/Users/jana/Zotero/storage/RK8UMG2Y/Anandakrishnan_NucleicAcidsRes_2012_v40_pW537.pdf}
}

@Article{	  Kilambi_Gray_2012_Biophys.J.,
  title		= {Rapid {{Calculation}} of {{Protein pKa Values Using
		  Rosetta}}},
  author	= {Kilambi, Krishna Praneeth and Gray, Jeffrey J.},
  year		= {2012},
  month		= aug,
  journal	= {Biophys. J.},
  volume	= {103},
  number	= {3},
  pages		= {587--595},
  issn		= {00063495},
  doi		= {10.1016/j.bpj.2012.06.044},
  abstract	= {We developed a Rosetta-based Monte Carlo method to
		  calculate the pKa values of protein residues that commonly
		  exhibit variable protonation states (Asp, Glu, Lys, His,
		  and Tyr). We tested the technique by calculating pKa values
		  for 264 residues from 34 proteins. The standard Rosetta
		  score function, which is independent of any environmental
		  conditions, failed to capture pKa shifts. After
		  incorporating a Coulomb electrostatic potential and
		  optimizing the solvation reference energies for pKa
		  calculations, we employed a method that allowed side-chain
		  flexibility and achieved a root mean-square deviation
		  (RMSD) of 0.83 from experimental values (0.68 after
		  discounting 11 predictions with an error over 2 pH units).
		  Additional degrees of side-chain conformational freedom for
		  the proximal residues facilitated the capture of
		  charge-charge interactions in a few cases, resulting in an
		  overall RMSD of 0.85 pH units. The addition of backbone
		  flexibility increased the overall RMSD to 0.93 pH units but
		  improved relative pKa predictions for proximal catalytic
		  residues. The method also captures large pKa shifts of
		  lysine and some glutamate point mutations in staphylococcal
		  nuclease. Thus, a simple and fast method based on the
		  Rosetta score function and limited conformational sampling
		  produces pKa values that will be useful when rapid
		  estimation is essential, such as in docking, design, and
		  folding.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/X9FUUPH2/Kilambi and Gray -
		  2012 - Rapid Calculation of Protein pKa Values Using
		  Rose.pdf}
}

@Article{	  Olsson_Jensen_2011_J.Chem.TheoryComput.,
  title		= {{{PROPKA3}}: {{Consistent Treatment}} of {{Internal}} and
		  {{Surface Residues}} in {{Empirical}} pKa
		   {{Predictions}}},
  shorttitle	= {{{PROPKA3}}},
  author	= {Olsson, Mats H. M. and S{\o}ndergaard, Chresten R. and
		  Rostkowski, Michal and Jensen, Jan H.},
  year		= {2011},
  month		= feb,
  journal	= {J. Chem. Theory Comput.},
  volume	= {7},
  number	= {2},
  pages		= {525--537},
  issn		= {1549-9618, 1549-9626},
  doi		= {10.1021/ct100578z},
  abstract	= {In this study, we have revised the rules and parameters
		  for one of the most commonly used empirical pKa predictors,
		  PROPKA, based on better physical description of the
		  desolvation and dielectric response for the protein. We
		  have introduced a new and consistent approach to
		  interpolate the description between the previously distinct
		  classifications into internal and surface residues, which
		  otherwise is found to give rise to an erratic and
		  discontinuous behavior. Since the goal of this study is to
		  lay out the framework and validate the concept, it focuses
		  on Asp and Glu residues where the protein pKa values and
		  structures are assumed to be more reliable. The new and
		  improved implementation is evaluated and discussed; it is
		  found to agree better with experiment than the previous
		  implementation (in parentheses): rmsd ) 0.79 (0.91) for Asp
		  and Glu, 0.75 (0.97) for Tyr, 0.65 (0.72) for Lys, and 1.00
		  (1.37) for His residues. The most significant advance,
		  however, is in reducing the number of outliers and removing
		  unreasonable sensitivity to small structural changes that
		  arise from classifying residues as either internal or
		  surface.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/YXN3YZLP/Olsson_JChemTheoryComput_2011_v7_p525.pdf}
}

@Article{	  Persi_Ruppin_2018_Nat.Commun.,
  title		= {Systems Analysis of Intracellular {{pH}} Vulnerabilities
		  for Cancer Therapy},
  author	= {Persi, Erez and {Duran-Frigola}, Miquel and Damaghi, Mehdi
		  and Roush, William R. and Aloy, Patrick and Cleveland, John
		  L. and Gillies, Robert J. and Ruppin, Eytan},
  year		= {2018},
  month		= dec,
  journal	= {Nat. Commun.},
  volume	= {9},
  number	= {1},
  pages		= {2997},
  issn		= {2041-1723},
  doi		= {10.1038/s41467-018-05261-x},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/2GEUTIXS/s41467-018-05261-x.pdf}
}

@Article{	  Song_Gunner_2009_J.Comput.Chem.,
  title		= {{{MCCE2}}: {{Improving}} Protein pKa Calculations with Extensive Side Chain
		  Rotamer Sampling},
  shorttitle	= {{{MCCE2}}},
  author	= {Song, Yifan and Mao, Junjun and Gunner, M. R.},
  year		= {2009},
  journal	= {J. Comput. Chem.},
  volume    = {30},
  issue     = {14},
  pages		= {2231–2247},
  issn		= {01928651, 1096987X},
  doi		= {10.1002/jcc.21222},
  abstract	= {Multiconformation continuum electrostatics (MCCE) explores
		  different conformational degrees of freedom in Monte Carlo
		  calculations of protein residue and ligand pKas. Explicit
		  changes in side chain conformations throughout a titration
		  create a position dependent, heterogeneous dielectric
		  response giving a more accurate picture of coupled
		  ionization and position changes. The MCCE2 methods for
		  choosing a group of input heavy atom and proton positions
		  are described. The pKas calculated with different isosteric
		  conformers, heavy atom rotamers and proton positions, with
		  different degrees of optimization are tested against a
		  curated group of 305 experimental pKas in 33 proteins.
		  QUICK calculations, with rotation around Asn and Gln
		  termini, sampling His tautomers and torsion minimum
		  hydroxyls yield an RMSD of 1.34 with 84\% of the errors
		  being \textbackslash 1.5 pH units. FULL calculations adding
		  heavy atom rotamers and side chain optimization yield an
		  RMSD of 0.90 with 90\% of the errors \textbackslash 1.5 pH
		  unit. Good results are also found for pKas in the membrane
		  protein bacteriorhodopsin. The inclusion of extra side
		  chain positions distorts the dielectric boundary and also
		  biases the calculated pKas by creating more neutral than
		  ionized conformers. Methods for correcting these errors are
		  introduced. Calculations are compared with multiple X-ray
		  and NMR derived structures in 36 soluble proteins.
		  Calculations with X-ray structures give significantly
		  better pKas. Results with the default protein dielectric
		  constant of 4 are as good as those using a value of 8. The
		  MCCE2 program can be downloaded from
		  http://www.sci.ccny.cuny.edu/\$mcce.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/X9W99FCZ/Song et al. - 2009 -
		  MCCE2 Improving protein p K a c.pdf}
}

@Article{	  Thurlkill_Pace_2006_ProteinSci.,
  title		= {{{pK}} Values of the Ionizable Groups of Proteins},
  author	= {Thurlkill, Richard L. and Grimsley, Gerald R. and Scholtz,
		  J. Martin and Pace, C. Nick},
  year		= {2006},
  month		= may,
  journal	= {Protein Sci.},
  volume	= {15},
  number	= {5},
  pages		= {1214--1218},
  issn		= {0961-8368},
  doi		= {10.1110/ps.051840806},
  abstract	= {We have used potentiometric titrations to measure the pK
		  values of the ionizable groups of proteins in alanine
		  pentapeptides with appropriately blocked termini. These
		  pentapeptides provide an improved model for the pK values
		  of the ionizable groups in proteins. Our pK values
		  determined in 0.1 M KCl at 25\textdegree C are:
		  3.67{$\pm$}0.03 ({$\alpha$}-carboxyl), 3.67{$\pm$}0.04
		  (Asp), 4.25{$\pm$}0.05 (Glu), 6.54{$\pm$}0.04 (His),
		  8.00{$\pm$}0.03 ({$\alpha$}-amino), 8.55{$\pm$}0.03 (Cys),
		  9.84{$\pm$}0.11 (Tyr), and 10.40{$\pm$}0.08 (Lys). The pK
		  values of some groups differ from the Nozaki and Tanford
		  (N\&T) pK values often used in the literature: Asp (3.67
		  this work vs. 4.0 N\&T); His (6.54 this work vs. 6.3 N\&T);
		  {$\alpha$}-amino (8.00 this work vs. 7.5 N\&T); Cys (8.55
		  this work vs. 9.5 N\&T); and Tyr (9.84 this work vs. 9.6
		  N\&T). Our pK values will be useful to those who study pK
		  perturbations in folded and unfolded proteins, and to those
		  who use theory to gain a better understanding of the
		  factors that determine the pK values of the ionizable groups of proteins.},
  pmcid		= {PMC2242523},
  pmid		= {16597822},
  keywords	= {\#duplicate-citation-key},
  file		= {/Users/jana/Zotero/storage/ZLQFA6LD/Thurlkill_ProteinSci_2006_v15_p1214.pdf}
}

@Article{	  Unni_Baker_2011_J.Comput.Chem.,
  title		= {Web Servers and Services for Electrostatics Calculations
		  with {{APBS}} and {{PDB2PQR}}},
  author	= {Unni, Samir and Huang, Yong and Hanson, Robert M. and
		  Tobias, Malcolm and Krishnan, Sriram and Li, Wilfred W. and
		  Nielsen, Jens E. and Baker, Nathan A.},
  year		= {2011},
  month		= may,
  journal	= {J. Comput. Chem.},
  volume	= {32},
  number	= {7},
  pages		= {1488--1491},
  issn		= {01928651},
  doi		= {10.1002/jcc.21720},
  abstract	= {APBS and PDB2PQR are widely utilized free software
		  packages for biomolecular electrostatics calculations.
		  Using the Opal toolkit, we have developed a Web services
		  framework for these software packages that enables the use
		  of APBS and PDB2PQR by users who do not have local access
		  to the necessary amount of computational capabilities. This
		  not only increases accessibility of the software to a wider
		  range of scientists, educators, and students but also
		  increases the availability of electrostatics calculations
		  on portable computing platforms. Users can access this new
		  functionality in two ways. First, an Opal-enabled version
		  of APBS is provided in current distributions, available
		  freely on the web. Second, we have extended the PDB2PQR web
		  server to provide an interface for the setup, execution,
		  and visualization of electrostatic potentials as calculated
		  by APBS. This web interface also uses the Opal framework
		  which ensures the scalability needed to support the large
		  APBS user community. Both of these resources are available
		  from the APBS/PDB2PQR website:
		  http://www.poissonboltzmann.org/.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/ZKHKQWYK/Unni et al. - 2011 -
		  Web servers and services for electrostatics calcul.pdf}
}

@Article{	  Wang_Alexov_2016_Bioinformatics,
  title		= {{{DelPhiPKa}} Web Server: Predicting p {{{\emph{K}}}}
		  {\textsubscript{a}} of Proteins, {{RNAs}} and {{DNAs}}},
  shorttitle	= {{{DelPhiPKa}} Web Server},
  author	= {Wang, Lin and Zhang, Min and Alexov, Emil},
  year		= {2016},
  month		= feb,
  journal	= {Bioinformatics},
  volume	= {32},
  number	= {4},
  pages		= {614--615},
  issn		= {1367-4803, 1460-2059},
  doi		= {10.1093/bioinformatics/btv607},
  abstract	= {Summary: A new pKa prediction web server is released,
		  which implements DelPhi Gaussian dielectric function to
		  calculate electrostatic potentials generated by charges of
		  biomolecules. Topology parameters are extended to include
		  atomic information of nucleotides of RNA and DNA, which
		  extends the capability of pKa calculations beyond proteins.
		  The web server allows the end-user to protonate the
		  biomolecule at particular pH based on calculated pKa values
		  and provides the downloadable file in PQR format. Several
		  tests are performed to benchmark the accuracy and speed of
		  the protocol.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/E9I4S7F8/Wang et al. - 2016 -
		  DelPhiPKa web server predicting p K
		  a.pdf;/Users/jana/Zotero/storage/UFJ7N7A3/Wang et al. -
		  2016 - DelPhiPKa web server predicting pKa of proteins,
		  .pdf}
}

@Article{	  WarwickerJim_WarwickerJim_2011_Proteins,
  title		= {pKa Predictions with a
		  Coupled Finite Difference {{Poisson}}-{{Boltzmann}} and
		  {{Debye}}-{{H\"uckel}} Method: pKa {{Predictions}} with {{FD}}/{{DH}}},
  author	= {{Warwicker, Jim}},
  year		= {2011},
  month		= dec,
  journal	= {Proteins},
  volume	= {79},
  number	= {12},
  pages		= {3374--3380},
  issn		= {08873585},
  doi		= {10.1002/prot.23078},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/Y2JW56MJ/Jim Warwicker - 2011 -
		  p K a predictions with a coupled.pdf}
}

@Article{	  White_Barber_2017_J.CellSci.,
  title		= {Cancer Cell Behaviors Mediated by Dysregulated {{pH}}
		  Dynamics at a Glance},
  author	= {White, Katharine A. and {Grillo-Hill}, Bree K. and Barber,
		  Diane L.},
  year		= {2017},
  month		= feb,
  journal	= {J. Cell Sci.},
  volume	= {130},
  number	= {4},
  pages		= {663--669},
  issn		= {1477-9137, 0021-9533},
  doi		= {10.1242/jcs.195297},
  abstract	= {ABSTRACT Dysregulated pH is a common characteristic of
		  cancer cells, as they have an increased intracellular pH
		  (pHi) and a decreased extracellular pH (pHe) compared with
		  normal cells. Recent work has expanded our knowledge of how
		  dysregulated pH dynamics influences cancer cell behaviors,
		  including proliferation, metastasis, metabolic adaptation
		  and tumorigenesis. Emerging data suggest that the
		  dysregulated pH of cancers enables these specific cell
		  behaviors by altering the structure and function of
		  selective pH-sensitive proteins, termed pH sensors. Recent
		  findings also show that, by blocking pHi increases, cancer
		  cell behaviors can be attenuated. This suggests ion
		  transporter inhibition as an effective therapeutic
		  approach, either singly or in combination with targeted
		  therapies. In this Cell Science at a Glance article and
		  accompanying poster, we highlight the interconnected roles
		  of dysregulated pH dynamics in cancer initiation,
		  progression and adaptation.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/UP36GACC/White et al. - 2017 -
		  Cancer cell behaviors mediated by dysregulated pH .pdf}
}

@Article{	  Shimizu_Nukina_2008_Mol.CellBiol.,
  title		= {Crystal {{Structure}} of an {{Active Form}} of {{BACE1}},
		  an {{Enzyme Responsible}} for {{Amyloid}} {$\beta$}
		  {{Protein Production}}},
  author	= {Shimizu, Hideaki and Tosaki, Asako and Kaneko, Kumi and
		  Hisano, Tamao and Sakurai, Takashi and Nukina, Nobuyuki},
  year		= {2008},
  month		= jun,
  journal	= {Mol. Cell Biol.},
  volume	= {28},
  number	= {11},
  pages		= {3663--3671},
  issn		= {0270-7306, 1098-5549},
  doi		= {10.1128/MCB.02185-07},
  abstract	= {ABSTRACT BACE1 ({$\beta$}-secretase) is a transmembrane
		  aspartic protease that cleaves the {$\beta$}-amyloid
		  precursor protein and generates the amyloid {$\beta$}
		  peptide (A{$\beta$}). BACE1 cycles between the cell surface
		  and the endosomal system many times and becomes activated
		  interconvertibly during its cellular trafficking, leading
		  to the production of A{$\beta$}. Here we report the crystal
		  structure of the catalytically active form of BACE1. The
		  active form has novel structural features involving the
		  conformation of the flap and subsites that promote
		  substrate binding. The functionally essential residues and
		  water molecules are well defined and play a key role in the
		  iterative activation of BACE1. We further describe the
		  crystal structure of the dehydrated form of BACE1, showing
		  that BACE1 activity is dependent on the dynamics of a
		  catalytically required Asp-bound water molecule, which
		  directly affects its catalytic properties. These findings
		  provide insight into a novel regulation of BACE1 activity
		  and elucidate how BACE1 modulates its activity during
		  cellular trafficking.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/AXFHUBMC/Shimizu_MolCellBiol_2008_v28_p3663.pdf}
}

@Article{	  Tan_Hilgenfeld_2005_J.Mol.Biol.,
  title		= {{{pH}}-Dependent {{Conformational Flexibility}} of the
		  {{SARS}}-{{CoV Main Proteinase}} ({{Mpro}}) {{Dimer}}:
		  {{Molecular Dynamics Simulations}} and {{Multiple X}}-Ray
		  {{Structure Analyses}}},
  shorttitle	= {{{pH}}-Dependent {{Conformational Flexibility}} of the
		  {{SARS}}-{{CoV Main Proteinase}} ({{Mpro}}) {{Dimer}}},
  author	= {Tan, Jinzhi and Verschueren, Koen H.G. and Anand, Kanchan
		  and Shen, Jianhua and Yang, Maojun and Xu, Yechun and Rao,
		  Zihe and Bigalke, Janna and Heisen, Burkhard and Mesters,
		  Jeroen R. and Chen, Kaixian and Shen, Xu and Jiang,
		  Hualiang and Hilgenfeld, Rolf},
  year		= {2005},
  month		= nov,
  journal	= {J. Mol. Biol.},
  volume	= {354},
  number	= {1},
  pages		= {25--40},
  issn		= {00222836},
  doi		= {10.1016/j.jmb.2005.09.012},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/9BQAK8U4/Tan et al. - 2005 -
		  pH-dependent Conformational Flexibility of the SAR.pdf}
}

@Article{	  Arthur_Brooks_2016_J.Comput.Chem.a,
  title		= {Parallelization and Improvements of the Generalized Born
		  Model with a Simple {{sWitching}} Function for Modern
		  Graphics Processors},
  author	= {Arthur, Evan J. and Brooks, III, Charles L.},
  year		= {2016},
  month		= apr,
  journal	= {J. Comput. Chem.},
  volume	= {37},
  number	= {10},
  pages		= {927--939},
  issn		= {01928651},
  doi		= {10.1002/jcc.24280},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/6ENEFYLX/Arthur and Brooks -
		  2016 - Parallelization and improvements of the
		  generalize.pdf}
}

@Article{	  Baptista_Soares_2002_J.Chem.Phys.,
  title		= {Constant- {\emph{p}} {{H}} Molecular Dynamics Using
		  Stochastic Titration},
  author	= {Baptista, Ant{\'o}nio M. and Teixeira, Vitor H. and
		  Soares, Cl{\'a}udio M.},
  year		= {2002},
  month		= sep,
  journal	= {J. Chem. Phys.},
  volume	= {117},
  number	= {9},
  pages		= {4184--4200},
  issn		= {0021-9606, 1089-7690},
  doi		= {10.1063/1.1497164},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/XVWRQFVZ/Baptista et al. - 2002
		  - Constant- p H molecular dynamics using stoc.pdf}
}

@Article{	  Berman_Bourne_2000_NucleicAcidsRes.,
  title		= {The {{Protein Data Bank}}},
  author	= {Berman, Helen M. and Westbrook, John and Feng, Zukang and
		  Gilliland, Gary and Bhat, T. N. and Weissig, Helge and
		  Shindyalov, Ilya N. and Bourne, Philip E.},
  year		= {2000},
  month		= jan,
  journal	= {Nucleic Acids Res.},
  volume	= {28},
  number	= {1},
  pages		= {235--242},
  publisher	= {{Oxford Academic}},
  issn		= {0305-1048},
  doi		= {10.1093/nar/28.1.235},
  abstract	= {Abstract. The Protein Data Bank (PDB;
		  http://www.rcsb.org/pdb/ ) is the single worldwide archive
		  of structural data of biological macromolecules. This paper
		  de},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/M8NKYQMA/Berman et al. - 2000 -
		  The Protein Data
		  Bank.pdf;/Users/jana/Zotero/storage/9JSLKTK2/2384399.html}
}

@Article{	  Brooks_Karplus_2009_J.Comput.Chem.,
  title		= {{{CHARMM}}: {{The Biomolecular Simulation Program}}},
  shorttitle	= {{{CHARMM}}},
  author	= {Brooks, B.R. and Brooks, III, C.L. and MacKerell, Jr., A.D. and
		  Nilsson, L. and Petrella, R.J. and Roux, B. and Won, Y. and
		  Archontis, G. and Bartels, C. and Boresch, S. and Caflisch,
		  A. and Caves, L. and Cui, Q. and Dinner, A.R. and Feig, M.
		  and Fischer, S. and Gao, J. and Hodoscek, M. and Im, W. and
		  Kuczera, K. and Lazaridis, T. and Ma, J. and Ovchinnikov,
		  V. and Paci, E. and Pastor, R.W. and Post, C.B. and Pu,
		  J.Z. and Schaefer, M. and Tidor, B. and Venable, R. M. and
		  Woodcock, H. L. and Wu, X. and Yang, W. and York, D.M. and
		  Karplus, M.},
  year		= {2009},
  month		= jul,
  journal	= {J. Comput. Chem.},
  volume	= {30},
  number	= {10},
  pages		= {1545--1614},
  issn		= {0192-8651},
  doi		= {10.1002/jcc.21287},
  abstract	= {CHARMM (Chemistry at HARvard Molecular Mechanics) is a
		  highly versatile and widely used molecular simulation
		  program. It has been developed over the last three decades
		  with a primary focus on molecules of biological interest,
		  including proteins, peptides, lipids, nucleic acids,
		  carbohydrates and small molecule ligands, as they occur in
		  solution, crystals, and membrane environments. For the
		  study of such systems, the program provides a large suite
		  of computational tools that include numerous conformational
		  and path sampling methods, free energy estimators,
		  molecular minimization, dynamics, and analysis techniques,
		  and model-building capabilities. In addition, the CHARMM
		  program is applicable to problems involving a much broader
		  class of many-particle systems. Calculations with CHARMM
		  can be performed using a number of different energy
		  functions and models, from mixed quantum
		  mechanical-molecular mechanical force fields, to all-atom
		  classical potential energy functions with explicit solvent
		  and various boundary conditions, to implicit solvent and
		  membrane models. The program has been ported to numerous
		  platforms in both serial and parallel architectures. This
		  paper provides an overview of the program as it exists
		  today with an emphasis on developments since the
		  publication of the original CHARMM paper in 1983.},
  pmcid		= {PMC2810661},
  pmid		= {19444816},
  file		= {/Users/jana/Zotero/storage/QKLLTJX6/Brooks et al. - 2009 -
		  CHARMM The Biomolecular Simulation Program.pdf}
}

@Article{	  Brunger_Karplus_1988_Proteins,
  title		= {Polar Hydrogen Positions in Proteins: {{Empirical}} Energy
		  Placement and Neutron Diffraction Comparison},
  shorttitle	= {Polar Hydrogen Positions in Proteins},
  author	= {Br{\"u}nger, Axel T. and Karplus, Martin},
  year		= {1988},
  journal	= {Proteins},
  volume	= {4},
  number	= {2},
  pages		= {148--156},
  issn		= {0887-3585, 1097-0134},
  doi		= {10.1002/prot.340040208},
  abstract	= {A method for the prediction of hydrogen positions in
		  proteins is presented. The method is based on the knowledge
		  of the heavy atom positions obtained, for instance, from
		  X-ray crystallography. It employs an energy minimization
		  limited to the environment of the hydrogen atoms bound to a
		  common heavy atom or to a single water molecule. The method
		  is not restricted to proteins and can be applied without
		  modification to nonpolar hydrogens and to nucleic acids.
		  The method has been applied to the neutron diffraction
		  structures of trypsin, ribonuclease A, and bovine
		  pancreatic trypsin inhibitor. A comparison of the
		  constructed and the observed hydrogen positions shows few
		  deviations except in situations in which several
		  energetically similar conformations are possible. Analysis
		  of the potential energy of rotation of Lys amino and Ser,
		  Thr, Tyr hydroxyl groups reveals that the conformations of
		  lowest intrinsic torsion energies are statistically favored
		  in both the crystal and the constructed structures.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/QHVFFWEG/Brünger and Karplus -
		  1988 - Polar hydrogen positions in proteins Empirical
		  en.pdf}
}

@Manual{	  Case_Kollman_2018,
  type		= {Software Manual},
  title		= {{{AMBER}} 2018},
  author	= {Case, D. A. and {Ben-Shalom}, I. Y. and Brozell, S. R. and
		  Cerutti, D. S. and Cheatham, III, T.E. and Cruzeiro, V. W.
		  D. and Darden, T. A. and Duke, R. E. and Ghoreishi, D. and
		  Gilson, M. K. and Gohlke, H. and Goetz, A. W. and Greene,
		  D. and Harris, R.C. and Homeyer, N. and Huang, Y. and
		  Izadi, S. and Kovalenko, A. and Kurtzman, T. and Lee, T. S.
		  and LeGrand, S. and Li, P. and Lin, C. and Liu, J. and
		  Luchko, T. and Luo, R. and Mermelstein, D. J. and Merz, K.
		  M. and Miao, Y. and Monard, G. and Nguyen, C. and Nguyen,
		  H. and Omelyan, I. and Onufriev, A. and Pan, F. and Qi, R.
		  and Roe, D. R. and Roitberg, A. and Sagui, C. and
		  {Schott-Verdugo}, S. and Shen, J. and Simmerling, C. L. and
		  Smith, J. and {Salomon-Ferrer}, R. and Swails, J. and
		  Walker, R. C. and Wang, J. and Wei, H. and Wolf, R. M. and
		  Wu, X. and Xiao, L. and York, D. M. and Kollman, P. A.},
  year		= {2018},
  address	= {{San Francisco}},
  institution	= {{University of California San Francisco}},
  file		= {/Users/jana/Zotero/storage/4QYBV68D/Amber18.pdf}
}

@Manual{	  Case_Kollman_2022,
  type		= {Software Manual},
  title		= {{{AMBER}} 2022},
  author	= {Case, D. A. and {Ben-Shalom}, I. Y. and Brozell, S. R. and
		  Cerutti, D. S. and Cheatham, III, T.E. and Cruzeiro, V. W.
		  D. and Darden, T. A. and Duke, R. E. and Ghoreishi, D. and
		  Gilson, M. K. and Gohlke, H. and Goetz, A. W. and Greene,
		  D. and Harris, R.C. and Homeyer, N. and Huang, Y. and
		  Izadi, S. and Kovalenko, A. and Kurtzman, T. and Lee, T. S.
		  and LeGrand, S. and Li, P. and Lin, C. and Liu, J. and
		  Luchko, T. and Luo, R. and Mermelstein, D. J. and Merz, K.
		  M. and Miao, Y. and Monard, G. and Nguyen, C. and Nguyen,
		  H. and Omelyan, I. and Onufriev, A. and Pan, F. and Qi, R.
		  and Roe, D. R. and Roitberg, A. and Sagui, C. and
		  {Schott-Verdugo}, S. and Shen, J. and Simmerling, C. L. and
		  Smith, J. and {Salomon-Ferrer}, R. and Swails, J. and
		  Walker, R. C. and Wang, J. and Wei, H. and Wolf, R. M. and
		  Wu, X. and Xiao, L. and York, D. M. and Kollman, P. A.},
  year		= {2018},
  address	= {{San Francisco}},
  institution	= {{University of California San Francisco}},
  file		= {/Users/jana/Zotero/storage/4QYBV68D/Amber18.pdf}
}

@Article{	  Chen_Roux_2015_J.Chem.TheoryComput.,
  title		= {Constant-{{pH Hybrid Nonequilibrium Molecular
		  Dynamics}}\textendash{{Monte Carlo Simulation Method}}},
  author	= {Chen, Yunjie and Roux, Beno{\^i}t},
  year		= {2015},
  month		= aug,
  journal	= {J. Chem. Theory Comput.},
  volume	= {11},
  number	= {8},
  pages		= {3919--3931},
  issn		= {1549-9618, 1549-9626},
  doi		= {10.1021/acs.jctc.5b00261},
  abstract	= {A computational method is developed to carry out explicit
		  solvent simulations of complex molecular systems under
		  conditions of constant pH. In constant-pH simulations,
		  preidentified ionizable sites are allowed to spontaneously
		  protonate and deprotonate as a function of time in response
		  to the environment and the imposed pH. The method, based on
		  a hybrid scheme originally proposed by H. A. Stern (J.
		  Chem. Phys. 2007, 126, 164112), consists of carrying out
		  short nonequilibrium molecular dynamics (neMD) switching
		  trajectories to generate physically plausible
		  configurations with changed protonation states that are
		  subsequently accepted or rejected according to a Metropolis
		  Monte Carlo (MC) criterion. To ensure microscopic detailed
		  balance arising from such nonequilibrium switches, the
		  atomic momenta are altered according to the symmetric
		  two-ends momentum reversal prescription. To achieve higher
		  efficiency, the original neMD-MC scheme is separated into
		  two steps, reducing the need for generating a large number
		  of unproductive and costly nonequilibrium trajectories. In
		  the first step, the protonation state of a site is randomly
		  attributed via a Metropolis MC process on the basis of an
		  intrinsic pKa; an attempted nonequilibrium switch is
		  generated only if this change in protonation state is
		  accepted. This hybrid two-step inherent pKa neMD-MC
		  simulation method is tested with single amino acids in
		  solution (Asp, Glu, and His) and then applied to turkey
		  ovomucoid third domain and hen egg-white lysozyme. Because
		  of the simple linear increase in the computational cost
		  relative to the number of titratable sites, the present
		  method is naturally able to treat extremely large
		  systems.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/ZD7DAZZB/Chen and Roux - 2015 -
		  Constant-pH Hybrid Nonequilibrium Molecular Dynami.pdf}
}

@Article{	  Darden_Pedersen_1993_J.Chem.Phys.,
  title		= {Particle Mesh {{Ewald}}: {{An W}} Log({{N}}) Method for
		  {{Ewald}} Sums in Large Systems},
  author	= {Darden, Tom and York, Darrin and Pedersen, Lee},
  year		= {1993},
  journal	= {J. Chem. Phys.},
  volume	= {98},
  number	= {12},
  pages		= {4},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/JKNLZ7CJ/Darden et al. - 1993 -
		  Particle mesh Ewald An W log(N) method for Ewald .pdf},
   doi      = {10.1063/1.464397}
}

@Article{	  Donnini_Grubmuller_2016_J.Chem.TheoryComput.,
  title		= {Charge-{{Neutral Constant pH Molecular Dynamics
		  Simulations Using}} a {{Parsimonious Proton Buffer}}},
  author	= {Donnini, Serena and Ullmann, R. Thomas and Groenhof,
		  Gerrit and Grubm{\"u}ller, Helmut},
  year		= {2016},
  month		= mar,
  journal	= {J. Chem. Theory Comput.},
  volume	= {12},
  number	= {3},
  pages		= {1040--1051},
  issn		= {1549-9618, 1549-9626},
  doi		= {10.1021/acs.jctc.5b01160},
  abstract	= {In constant pH molecular dynamics simulations, the
		  protonation states of titratable sites can respond to
		  changes of the pH and of their electrostatic environment.
		  Consequently, the number of protons bound to the
		  biomolecule, and therefore the overall charge of the
		  system, fluctuates during the simulation. To avoid
		  artifacts associated with a nonneutral simulation system,
		  we introduce an approach to maintain neutrality of the
		  simulation box in constant pH molecular dynamics
		  simulations, while maintaining an accurate description of
		  all protonation fluctuations. Specifically, we introduce a
		  proton buffer that, like a buffer in experiment, can
		  exchange protons with the biomolecule enabling its charge
		  to fluctuate. To keep the total charge of the system
		  constant, the uptake and release of protons by the buffer
		  are coupled to the titration of the biomolecule with a
		  constraint. We find that, because the fluctuation of the
		  total charge (number of protons) of a typical biomolecule
		  is much smaller than the number of titratable sites of the
		  biomolecule, the number of buffer sites required to
		  maintain overall charge neutrality without compromising the
		  charge fluctuations of the biomolecule, is typically much
		  smaller than the number of titratable sites, implying
		  markedly enhanced simulation and sampling efficiency.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/6ZAW694S/Donnini_JChemTheoryComput_2016_v12_p1040.pdf}
}

@Article{	  Eastman_Pande_2017_PLoSComput.Biol.,
  title		= {{{OpenMM}} 7: {{Rapid}} Development of High Performance
		  Algorithms for Molecular Dynamics},
  shorttitle	= {{{OpenMM}} 7},
  author	= {Eastman, Peter and Swails, Jason and Chodera, John D. and
		  McGibbon, Robert T. and Zhao, Yutong and Beauchamp, Kyle A.
		  and Wang, Lee-Ping and Simmonett, Andrew C. and Harrigan,
		  Matthew P. and Stern, Chaya D. and Wiewiora, Rafal P. and
		  Brooks, Bernard R. and Pande, Vijay S.},
  editor	= {Gentleman, Robert},
  year		= {2017},
  month		= jul,
  journal	= {PLoS Comput. Biol.},
  volume	= {13},
  number	= {7},
  pages		= {e1005659},
  issn		= {1553-7358},
  doi		= {10.1371/journal.pcbi.1005659},
  abstract	= {OpenMM is a molecular dynamics simulation toolkit with a
		  unique focus on extensibility. It allows users to easily
		  add new features, including forces with novel functional
		  forms, new integration algorithms, and new simulation
		  protocols. Those features automatically work on all
		  supported hardware types (including both CPUs and GPUs) and
		  perform well on all of them. In many cases they require
		  minimal coding, just a mathematical description of the
		  desired function. They also require no modification to
		  OpenMM itself and can be distributed independently of
		  OpenMM. This makes it an ideal tool for researchers
		  developing new simulation methods, and also allows those
		  new methods to be immediately available to the larger
		  community.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/GQMLPPVD/pcbi.1005659.pdf}
}

@Article{	  Feig_Brooks_2004_J.Mol.Graph.Model.,
  title		= {{{MMTSB Tool Set}}: {{Enhanced Sampling}} and {{Multiscale
		  Modeling Methods}} for {{Applications}} in {{Structural
		  Biology}}},
  shorttitle	= {{{MMTSB Tool Set}}},
  author	= {Feig, Michael and Karanicolas, John and Brooks III,
		  Charles L.},
  year		= {2004},
  journal	= {J. Mol. Graph. Model.},
  volume	= {22},
  issue     = {5},
  pages		= {2004},
  abstract	= {html), which is a novel set of utilities and programming
		  libraries that provide new enhanced sampling and multiscale
		  modeling techniques for the simulation of proteins and
		  nucleic acids. The tool set interfaces with the existing
		  molecular modeling packages CHARMM and Amber for classical
		  all-atom simulations, and with MONSSTER for lattice-based
		  low-resolution conformational sampling. In addition, it
		  adds new functionality for the integration and translation
		  between both levels of detail. The replica exchange method
		  is implemented to allow enhanced sampling of both the
		  all-atom and low-resolution models. The tool set aims at
		  applications in structural biology that involve protein or
		  nucleic acid structure prediction, refinement, and/or
		  extended conformational sampling. With structure prediction
		  applications in mind, the tool set also implements a
		  facility that allows the control and application of
		  modeling tasks on a large set of conformations in what we
		  have termed ensemble computing. Ensemble computing
		  encompasses loosely coupled, parallel computation on
		  high-end parallel computers, clustered computational grids
		  and desktop grid environments. This paper describes the
		  design and implementation of the MMTSB Tool Set and
		  illustrates its utility with three typical
		  examples\textemdash scoring of a set of predicted protein
		  conformations in order to identify the most native-like
		  structures, ab initio folding of peptides in implicit
		  solvent with the replica exchange method, and the
		  prediction of a missing fragment in a larger protein
		  structure.},
  file		= {/Users/jana/Zotero/storage/FQZYLZ33/Feig et al. - 2004 -
		  MMTSB Tool Set enhanced sampling and multiscale m.pdf},
  doi       = {10.1016/j.jmgm.2003.12.005},
}

@Article{	  Feller_Brooks_1995_J.Chem.Phys.,
  title		= {Constant Pressure Molecular Dynamics Simulation: {{The
		  Langevin}} Piston Method},
  shorttitle	= {Constant Pressure Molecular Dynamics Simulation},
  author	= {Feller, Scott E. and Zhang, Yuhong and Pastor, Richard W.
		  and Brooks, Bernard R.},
  year		= {1995},
  month		= sep,
  journal	= {J. Chem. Phys.},
  volume	= {103},
  number	= {11},
  pages		= {4613--4621},
  issn		= {0021-9606, 1089-7690},
  doi		= {10.1063/1.470648},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/7DK5Q7PF/Feller et al. - 1995 -
		  Constant pressure molecular dynamics simulation T.pdf}
}

@Article{	  Goh_Brooks_2014_Proteins,
  title		= {Constant {{pH}} Molecular Dynamics of Proteins in Explicit
		  Solvent with Proton Tautomerism: {{Explicit Solvent CPHMD}}
		  of {{Proteins}}},
  shorttitle	= {Constant {{pH}} Molecular Dynamics of Proteins in Explicit
		  Solvent with Proton Tautomerism},
  author	= {Goh, Garrett B. and Hulbert, Benjamin S. and Zhou, Huiqing
		  and {Brooks III}, Charles L.},
  year		= {2014},
  month		= jul,
  journal	= {Proteins},
  volume	= {82},
  number	= {7},
  pages		= {1319--1331},
  issn		= {08873585},
  doi		= {10.1002/prot.24499},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/Q9KUMCDA/Goh_Proteins_2014_v82_p1319.pdf}
}

@Article{	  Hoover_Hoover_1985_Phys.Rev.Aa,
  title		= {Canonical Dynamics: {{Equilibrium}} Phase-Space
		  Distributions},
  shorttitle	= {Canonical Dynamics},
  author	= {Hoover, William G.},
  year		= {1985},
  month		= mar,
  journal	= {Phys. Rev. A},
  volume	= {31},
  number	= {3},
  pages		= {1695--1697},
  publisher	= {{American Physical Society}},
  doi		= {10.1103/PhysRevA.31.1695},
  abstract	= {Nos\'e has modified Newtonian dynamics so as to reproduce
		  both the canonical and the isothermal-isobaric probability
		  densities in the phase space of an N-body system. He did
		  this by scaling time (with s) and distance (with V1/D in D
		  dimensions) through Lagrangian equations of motion. The
		  dynamical equations describe the evolution of these two
		  scaling variables and their two conjugate momenta ps and
		  pv. Here we develop a slightly different set of equations,
		  free of time scaling. We find the dynamical steady-state
		  probability density in an extended phase space with
		  variables x, px, V, {$\epsilon\dot$}, and {$\zeta$}, where
		  the x are reduced distances and the two variables
		  {$\epsilon\dot$} and {$\zeta$} act as thermodynamic
		  friction coefficients. We find that these friction
		  coefficients have Gaussian distributions. From the
		  distributions the extent of small-system non-Newtonian
		  behavior can be estimated. We illustrate the dynamical
		  equations by considering their application to the simplest
		  possible case, a one-dimensional classical harmonic oscillator.},
  file		= {/Users/jana/Zotero/storage/4GVMUBMX/Hoover_PhysRevA_1985_v31_p1695.pdf}
}

@Article{	  Im_Brooks_2003_Biophys.J.,
  title		= {An {{Implicit Membrane Generalized Born Theory}} for the
		  {{Study}} of {{Structure}}, {{Stability}}, and
		  {{Interactions}} of {{Membrane Proteins}}},
  author	= {Im, Wonpil and Feig, Michael and Brooks, III, Charles L.},
  year		= {2003},
  month		= nov,
  journal	= {Biophys. J.},
  volume	= {85},
  number	= {5},
  pages		= {2900--2918},
  issn		= {00063495},
  doi		= {10.1016/S0006-3495(03)74712-2},
  abstract	= {Exploiting recent developments in generalized Born (GB)
		  electrostatics theory, we have reformulated the calculation
		  of the self-electrostatic solvation energy to account for
		  the influence of biological membranes. Consistent with
		  continuum Poisson-Boltzmann (PB) electrostatics, the
		  membrane is approximated as an solvent-inaccessible
		  infinite planar low-dielectric slab. The present membrane
		  GB model closely reproduces the PB electrostatic solvation
		  energy profile across the membrane. The nonpolar
		  contribution to the solvation energy is taken to be
		  proportional to the solvent-exposed surface area (SA) with
		  a phenomenological surface tension coefficient. The
		  proposed membrane GB/SA model requires minor modifications
		  of the pre-existing GB model and appears to be quite
		  efficient. By combining this implicit model for the
		  solvent/ bilayer environment with advanced computational
		  sampling methods, like replica-exchange molecular dynamics,
		  we are able to fold and assemble helical membrane peptides.
		  We examine the reliability of this model and approach by
		  applications to three membrane peptides: melittin from bee
		  venom, the transmembrane domain of the M2 protein from
		  Influenza A (M2-TMP), and the transmembrane domain of
		  glycophorin A (GpA). In the context of these proteins, we
		  explore the role of biological membranes (represented as a
		  low-dielectric medium) in affecting the conformational
		  changes in melittin, the tilt of transmembrane peptides
		  with respect to the membrane normal (M2-TMP),
		  helix-to-helix interactions in membranes (GpA), and the
		  prediction of the configuration of transmembrane helical
		  bundles (GpA). The present method is found to perform well
		  in each of these cases and is anticipated to be useful in
		  the study of folding and assembly of membrane proteins as
		  well as in structure refinement and modeling of membrane
		  proteins where a limited number of experimental observables
		  are available.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/EXGHIP72/Im_BiophysJ_2003_v85_p2900.pdf}
}

@Article{	  Im_Brooks_2003_J.Comput.Chem.,
  ids		= {Im_Brooks_2003_J.Comput.Chem._12},
  title		= {Generalized Born Model with a Simple Smoothing Function},
  author	= {Im, Wonpil and Lee, Michael S. and Brooks, III, Charles L.},
  year		= {2003},
  month		= nov,
  journal	= {J. Comput. Chem.},
  volume	= {24},
  number	= {14},
  pages		= {1691--1702},
  issn		= {0192-8651},
  doi		= {10.1002/jcc.10321},
  abstract	= {Based on recent developments in generalized Born (GB)
		  theory that employ rapid volume integration schemes (M. S.
		  Lee, F. R. Salabury, Jr., and C. L. Brooks III, J Chem Phys
		  2002, 116, 10606) we have recast the calculation of the
		  self-electrostatic solvation energy to utilize a simple
		  smoothing function at the dielectric boundary. The present
		  GB model is formulated in this manner to provide
		  consistency with the Poisson-Boltzmann (PB) theory
		  previously developed to yield numerically stable
		  electrostatic solvation forces based on finite-difference
		  methods (W. Im, D. Beglov, and B. Roux, Comp Phys Commun
		  1998, 111, 59). Our comparisons show that the present GB
		  model is indeed an efficient and accurate approach to
		  reproduce corresponding PB solvation energies and forces.
		  With only two adjustable parameters--a(0) to modulate the
		  Coulomb field term, and a(1) to include a correction term
		  beyond Coulomb field--the PB solvation energies are
		  reproduced within 1\% error on average for a variety of
		  proteins. Detailed analysis shows that the PB energy can be
		  reproduced within 2\% absolute error with a confidence of
		  about 95\%. In addition, the solvent-exposed surface area
		  of a biomolecule, as commonly used in calculations of the
		  nonpolar solvation energy, can be calculated accurately and
		  efficiently using the simple smoothing function and the
		  volume integration method. Our implicit solvent GB
		  calculations are about 4.5 times slower than the
		  corresponding vacuum calculations. Using the simple
		  smoothing function makes the present GB model roughly three
		  times faster than GB models, which attempt to mimic the
		  Lee-Richards molecular volume.},
  language	= {eng},
  pmid		= {12964188}
}

@Article{	  Jo_Im_2007_PLoSONE,
  title		= {Automated {{Builder}} and {{Database}} of
		  {{Protein}}/{{Membrane Complexes}} for {{Molecular Dynamics
		  Simulations}}},
  author	= {Jo, Sunhwan and Kim, Taehoon and Im, Wonpil},
  editor	= {Yuan, Adam},
  year		= {2007},
  month		= sep,
  journal	= {PLoS ONE},
  volume	= {2},
  number	= {9},
  pages		= {e880},
  issn		= {1932-6203},
  doi		= {10.1371/journal.pone.0000880},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/2A3V57G6/Jo et al. - 2007 -
		  Automated Builder and Database of ProteinMembrane.pdf}
}

@Article{	  Kong_Brooks_1996_J.Chem.Phys.,
  title		= {Lambda-Dynamics: {{A}} New Approach to Free Energy
		  Calculations},
  author	= {Kong, Xianjun and Brooks, III, Charles L.},
  year		= {1996},
  journal	= {J. Chem. Phys.},
  volume	= {105},
  number	= {6},
  pages		= {10},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/TGVDJGV6/Kong_JChemPhys_1996_v105_p2414.pdf},
  doi       = {10.1063/1.472109}
}

@Article{	  Lee_Brooks_2003_J.Comput.Chem.,
  title		= {New Analytic Approximation to the Standard Molecular
		  Volume Definition and Its Application to Generalized
		  {{Born}} Calculations},
  author	= {Lee, Michael S. and Feig, Michael and Salsbury, Freddie R. and Brooks, III, Charles L.},
  year		= {2003},
  month		= aug,
  journal	= {J. Comput. Chem.},
  volume	= {24},
  number	= {11},
  pages		= {1348--1356},
  issn		= {0192-8651, 1096-987X},
  doi		= {10.1002/jcc.10272},
  abstract	= {In a recent article (Lee, M. S.; Salsbury, F. R. Jr.;
		  Brooks, C. L., III. J Chem Phys 2002, 116, 10606), we
		  demonstrated that generalized Born (GB) theory provides a
		  good approximation to Poisson electrostatic solvation
		  energy calculations if one uses the same definitions of
		  molecular volume for each. In this work, we present a new
		  and improved analytic method for reproducing the
		  Lee\textendash Richards molecular volume, which is the most
		  common volume definition for Poisson calculations. Overall,
		  1\% errors are achieved for absolute solvation energies of
		  a large set of proteins and relative solvation energies of
		  protein conformations. We also introduce an accurate SASA
		  approximation that uses the same machinery employed by our
		  GB method and requires a small addition of computational
		  cost. The combined methodology is shown to yield an
		  efficient and accurate implicit solvent representation for
		  simulations of biopolymers.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/NGVR3QSG/Lee et al. - 2003 -
		  New analytic approximation to the standard molecul.pdf}
}

@Article{	  Lee_Brooks_2004_Proteins,
  title		= {Constant-{{pH}} Molecular Dynamics Using Continuous
		  Titration Coordinates},
  author	= {Lee, Michael S. and Salsbury, Freddie R. and Brooks, III,
		  Charles L.},
  year		= {2004},
  journal	= {Proteins},
  volume	= {56},
  number	= {4},
  pages		= {738--752},
  issn		= {1097-0134},
  doi		= {10.1002/prot.20128},
  abstract	= {In this work, we explore the question of whether pKa
		  calculations based on a microscopic description of the
		  protein and a macroscopic description of the solvent can be
		  implemented to examine conformationally dependent proton
		  shifts in proteins. To this end, we introduce a new method
		  for performing constant-pH molecular dynamics (PHMD)
		  simulations utilizing the generalized Born implicit solvent
		  model. This approach employs an extended Hamiltonian in
		  which continuous titration coordinates propagate
		  simultaneously with the atomic motions of the system. The
		  values adopted by these coordinates are modulated by
		  potentials of mean force of isolated titratable model
		  groups and the pH to control the proton occupation at
		  particular sites in the polypeptide. Our results for four
		  different proteins yield an absolute average error of
		  {$\sim$}1.6 pK units, and point to the role that thermally
		  driven relaxation of the protein environment in the
		  vicinity of titrating groups plays in modulating the local
		  pKa, thereby influencing the observed pK1/2 values. While
		  the accuracy of our method is not yet equivalent to methods
		  that obtain pK1/2 values through the ad hoc scaling of
		  electrostatics, the present approach and constant pH
		  methods in general provide a useful framework for studying
		  pH-dependent phenomena. Further work to improve our model
		  to approach quantitative agreement with experiment is
		  outlined. Proteins 2004. \textcopyright{} 2004 Wiley-Liss,
		  Inc.},
  copyright	= {Copyright \textcopyright{} 2004 Wiley-Liss, Inc.},
  language	= {en},
  keywords	= {BPTI,conformational change,free
		  energy,ovomucoid,pKa,proteins,RNase A},
  annotation	= {\_eprint:
		  https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.20128},
  file		= {/Users/jana/Zotero/storage/SC5MKCH4/Lee et
		  al_2004_Constant-pH molecular dynamics using continuous
		  titration coordinates.pdf}
}

@Article{	  Lomize_Mosberg_2006_Bioinformatics,
  title		= {{{OPM}}: {{Orientations}} of {{Proteins}} in {{Membranes}}
		  Database},
  shorttitle	= {{{OPM}}},
  author	= {Lomize, M. A. and Lomize, A. L. and Pogozheva, I. D. and
		  Mosberg, H. I.},
  year		= {2006},
  month		= mar,
  journal	= {Bioinformatics},
  volume	= {22},
  number	= {5},
  pages		= {623--625},
  issn		= {1367-4803, 1460-2059},
  doi		= {10.1093/bioinformatics/btk023},
  abstract	= {Summary: The Orientations of Proteins in Membranes (OPM)
		  database provides a collection of transmembrane, monotopic
		  and peripheral proteins from the Protein Data Bank whose
		  spatial arrangements in the lipid bilayer have been
		  calculated theoretically and compared with experimental
		  data. The database allows analysis, sorting and searching
		  of membrane proteins based on their structural
		  classification, species, destination membrane, numbers of
		  transmembrane segments and subunits, numbers of secondary
		  structures and the calculated hydrophobic thickness or tilt
		  angle with respect to the bilayer normal. All coordinate
		  files with the calculated membrane boundaries are available
		  for downloading.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/HV7S6VD7/Lomize et al. - 2006 -
		  OPM Orientations of Proteins in Membranes databas.pdf}
}

@Article{	  Michaud-Agrawal_Beckstein_2011_J.Comput.Chem.,
  title		= {{{MDAnalysis}}: {{A}} Toolkit for the Analysis of
		  Molecular Dynamics Simulations},
  shorttitle	= {{{MDAnalysis}}},
  author	= {{Michaud-Agrawal}, Naveen and Denning, Elizabeth J. and
		  Woolf, Thomas B. and Beckstein, Oliver},
  year		= {2011},
  journal	= {J. Comput. Chem.},
  volume	= {32},
  number	= {10},
  pages		= {2319--2327},
  issn		= {1096-987X},
  doi		= {10.1002/jcc.21787},
  abstract	= {MDAnalysis is an object-oriented library for structural
		  and temporal analysis of molecular dynamics (MD) simulation
		  trajectories and individual protein structures. It is
		  written in the Python language with some
		  performance-critical code in C. It uses the powerful NumPy
		  package to expose trajectory data as fast and efficient
		  NumPy arrays. It has been tested on systems of millions of
		  particles. Many common file formats of simulation packages
		  including CHARMM, Gromacs, Amber, and NAMD and the Protein
		  Data Bank format can be read and written. Atoms can be
		  selected with a syntax similar to CHARMM's powerful
		  selection commands. MDAnalysis enables both novice and
		  experienced programmers to rapidly write their own
		  analytical tools and access data stored in trajectories in
		  an easily accessible manner that facilitates interactive
		  explorative analysis. MDAnalysis has been tested on and
		  works for most Unix-based platforms such as Linux and Mac
		  OS X. It is freely available under the GNU General Public
		  License from http://mdanalysis.googlecode.com.
		  \textcopyright{} 2011 Wiley Periodicals, Inc. J Comput Chem
		  2011},
  language	= {en},
  keywords	= {analysis,membrane systems,molecular dynamics
		  simulations,object-oriented design,proteins,Python
		  programming language,software},
  annotation	= {\_eprint:
		  https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.21787},
  file		= {/Users/jana/Zotero/storage/WTLH9WJR/Michaud-Agrawal et al.
		  - 2011 - MDAnalysis A toolkit for the analysis of
		  molecula.pdf;/Users/jana/Zotero/storage/9PDKDZ9N/jcc.html}
}

@Article{	  Mongan_McCammon_2004_J.Comput.Chem.,
  title		= {Constant {{pH}} Molecular Dynamics in Generalized {{Born}}
		  Implicit Solvent},
  author	= {Mongan, John and Case, David A. and McCammon, J. Andrew},
  year		= {2004},
  month		= dec,
  journal	= {J. Comput. Chem.},
  volume	= {25},
  number	= {16},
  pages		= {2038--2048},
  issn		= {01928651, 1096987X},
  doi		= {10.1002/jcc.20139},
  abstract	= {A new method is proposed for constant pH molecular
		  dynamics (MD), employing generalized Born (GB)
		  electrostatics. Protonation states are modeled with
		  different charge sets, and titrating residues sample a
		  Boltzmann distribution of protonation states as the
		  simulation progresses, using Monte Carlo sampling based on
		  GB-derived energies. The method is applied to four
		  different crystal structures of hen egg-white lysozyme
		  (HEWL). pKa predictions derived from the simulations have
		  root-mean-square (RMS) error of 0.82 relative to
		  experimental values. Similarity of results between the four
		  crystal structures shows the method to be independent of
		  starting crystal structure; this is in contrast to most
		  electrostatics-only models. A strong correlation between
		  conformation and protonation state is noted and
		  quantitatively analyzed, emphasizing the importance of
		  sampling protonation states in conjunction with dynamics.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/I23F5U8I/Mongan_JComputChem_2004_v25_p2038.pdf}
}

@Article{	  Nina_Roux_1997_J.Phys.Chem.B,
  title		= {Atomic {{Radii}} for {{Continuum Electrostatics
		  Calculations Based}} on {{Molecular Dynamics Free Energy
		  Simulations}}},
  author	= {Nina, Mafalda and Beglov, Dmitri and Roux, Beno{\^i}t},
  year		= {1997},
  month		= jun,
  journal	= {J. Phys. Chem. B},
  volume	= {101},
  number	= {26},
  pages		= {5239--5248},
  issn		= {1520-6106, 1520-5207},
  doi		= {10.1021/jp970736r},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/WNWI9WKK/Nina et al. - 1997 -
		  Atomic Radii for Continuum Electrostatics Calculat.pdf}
}

@Article{	  Nose_Nose_1984_Mol.Phys.,
  title		= {A Molecular Dynamics Method for Simulations in the
		  Canonical Ensemblet},
  author	= {Nos{\'e}, Shuichi},
  year		= {1984},
  journal	= {Mol. Phys.},
  volume	= {52},
  pages		= {255--268},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/6HRLXFA5/Nosi - A molecular
		  dynamics method for simulations in the.pdf},
   doi      =  {10.1080/00268978400101201}
}

@Article{	  Onufriev_Bashford_2002_J.Comput.Chem.,
  title		= {Effective {{Born}} Radii in the Generalized {{Born}}
		  Approximation: {{The}} Importance of Being Perfect},
  shorttitle	= {Effective {{Born}} Radii in the Generalized {{Born}}
		  Approximation},
  author	= {Onufriev, Alexey and Case, David A. and Bashford, Donald},
  year		= {2002},
  month		= nov,
  journal	= {J. Comput. Chem.},
  volume	= {23},
  number	= {14},
  pages		= {1297--1304},
  issn		= {0192-8651, 1096-987X},
  doi		= {10.1002/jcc.10126},
  abstract	= {Generalized Born (GB) models provide, for many
		  applications, an accurate and computationally facile
		  estimate of the electrostatic contribution to aqueous
		  solvation. The GB models involve two main types of
		  approximations relative to the Poisson equation (PE) theory
		  on which they are based. First, the self-energy
		  contributions of individual atoms are estimated and
		  expressed as ``effective Born radii.'' Next, the atom-pair
		  contributions are estimated by an analytical function f GB
		  that depends upon the effective Born radii and interatomic
		  distance of the atom pairs. Here, the relative impacts of
		  these approximations are investigated by calculating
		  ``perfect'' effective Born radii from PE theory, and
		  enquiring as to how well the atom-pairwise energy terms
		  from a GB model using these perfect radii in the standard f
		  GB function duplicate the equivalent terms from PE theory.
		  In tests on several biological macromolecules, the use of
		  these perfect radii greatly increases the accuracy of the
		  atom-pair terms; that is, the standard form of f GB
		  performs quite well. The remaining small error has a
		  systematic and a random component. The latter cannot be
		  removed without significantly increasing the complexity of
		  the GB model, but an alternative choice of f GB can reduce
		  the systematic part. A molecular dynamics simulation using
		  a perfect-radii GB model compares favorably with
		  simulations using conventional GB, even though the radii
		  remain fixed in the former. These results quantify, for the
		  GB field, the importance of getting the effective Born
		  radii right; indeed, with perfect radii, the GB model gives
		  a very good approximation to the underlying PE theory for a
		  variety of biomacromolecular types and conformations.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/VWCT94ZL/Onufriev et al. - 2002
		  - Effective Born radii in the generalized Born appro.pdf}
}

@Article{	  Phillips_Schulten_2005_J.Comput.Chem.,
  title		= {Scalable Molecular Dynamics with {NAMD}},
  author	= {Phillips, James C. and Braun, Rosemary and Wang, Wei and
		  Gumbart, James and Tajkhorshid, Emad and Villa, Elizabeth
		  and Chipot, Christophe and Skeel, Robert D. and Kal{\'e},
		  Laxmikant and Schulten, Klaus},
  year		= {2005},
  journal	= {J. Comput. Chem.},
  volume	= {26},
  number	= {16},
  pages		= {1781--1802},
  issn		= {1096-987X},
  language	= {en},
  doi		= {10.1002/jcc.20289}
}

@Article{	  Radak_Roux_2017_J.Chem.TheoryComput.,
  title		= {Constant-{{pH Molecular Dynamics Simulations}} for {{Large
		  Biomolecular Systems}}},
  author	= {Radak, Brian K. and Chipot, Christophe and Suh, Donghyuk
		  and Jo, Sunhwan and Jiang, Wei and Phillips, James C. and
		  Schulten, Klaus and Roux, Beno{\^i}t},
  year		= {2017},
  month		= dec,
  journal	= {J. Chem. Theory Comput.},
  volume	= {13},
  number	= {12},
  pages		= {5933--5944},
  issn		= {1549-9618, 1549-9626},
  doi		= {10.1021/acs.jctc.7b00875},
  abstract	= {An increasingly important endeavor is to develop
		  computational strategies that enable molecular dynamics
		  (MD) simulations of biomolecular systems with spontaneous
		  changes in protonation states under conditions of constant
		  pH. The present work describes our efforts to implement the
		  powerful constant-pH MD simulation method, based on a
		  hybrid nonequilibrium MD/Monte Carlo (neMD/ MC) technique
		  within the highly scalable program NAMD. The constant-pH
		  hybrid neMD/MC method has several appealing features; it
		  samples the correct semigrand canonical ensemble
		  rigorously, the computational cost increases linearly with
		  the number of titratable sites, and it is applicable to
		  explicit solvent simulations. The present implementation of
		  the constant-pH hybrid neMD/MC in NAMD is designed to
		  handle a wide range of biomolecular systems with no
		  constraints on the choice of force field. Furthermore, the
		  sampling efficiency can be adaptively improved on-the-fly
		  by adjusting algorithmic parameters during the simulation.
		  Illustrative examples emphasizing medium- and large-scale
		  applications on next-generation supercomputing
		  architectures are provided.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/LVE6W3PZ/Radak_JChemTheoryComput_2017_v13_p5933.pdf}
}

@Article{	  Ryckaert_Berendsen_1977_J.Comput.Phys.,
  title		= {Numerical Integration of the Cartesian Equations of Motion
		  of a System with Constraints: Molecular Dynamics of
		  n-Alkanes},
  shorttitle	= {Numerical Integration of the Cartesian Equations of Motion
		  of a System with Constraints},
  author	= {Ryckaert, Jean-Paul and Ciccotti, Giovanni and Berendsen,
		  Herman J.C},
  year		= {1977},
  month		= mar,
  journal	= {J. Comput. Phys.},
  volume	= {23},
  number	= {3},
  pages		= {327--341},
  issn		= {0021-9991},
  doi		= {10.1016/0021-9991(77)90098-5},
  abstract	= {A numerical algorithm integrating the 3N Cartesian
		  equations of motion of a system of N points subject to
		  holonomic constraints is formulated. The rel\ldots},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/SJUH78CF/Ryckaert et al. - 1977
		  - Numerical integration of the cartesian equations o.pdf}
}

@Article{	  Spoel_Berendsen_2005_J.Comput.Chem.,
  title		= {{{GROMACS}}: {{Fast}}, Flexible, and Free},
  shorttitle	= {{{GROMACS}}},
  author	= {Spoel, David Van Der and Lindahl, Erik and Hess, Berk and
		  Groenhof, Gerrit and Mark, Alan E. and Berendsen, Herman J.
		  C.},
  year		= {2005},
  journal	= {J. Comput. Chem.},
  volume	= {26},
  number	= {16},
  pages		= {1701--1718},
  issn		= {1096-987X},
  doi		= {10.1002/jcc.20291},
  abstract	= {This article describes the software suite GROMACS
		  (Groningen MAchine for Chemical Simulation) that was
		  developed at the University of Groningen, The Netherlands,
		  in the early 1990s. The software, written in ANSI C,
		  originates from a parallel hardware project, and is well
		  suited for parallelization on processor clusters. By
		  careful optimization of neighbor searching and of inner
		  loop performance, GROMACS is a very fast program for
		  molecular dynamics simulation. It does not have a force
		  field of its own, but is compatible with GROMOS, OPLS,
		  AMBER, and ENCAD force fields. In addition, it can handle
		  polarizable shell models and flexible constraints. The
		  program is versatile, as force routines can be added by the
		  user, tabulated functions can be specified, and analyses
		  can be easily customized. Nonequilibrium dynamics and free
		  energy determinations are incorporated. Interfaces with
		  popular quantum-chemical packages (MOPAC, GAMES-UK,
		  GAUSSIAN) are provided to perform mixed MM/QM simulations.
		  The package includes about 100 utility and analysis
		  programs. GROMACS is in the public domain and distributed
		  (with source code and documentation) under the GNU General
		  Public License. It is maintained by a group of developers
		  from the Universities of Groningen, Uppsala, and Stockholm,
		  and the Max Planck Institute for Polymer Research in Mainz.
		  Its Web site is http://www.gromacs.org. \textcopyright{}
		  2005 Wiley Periodicals, Inc. J Comput Chem 26:
		  1701\textendash 1718, 2005},
  language	= {en},
  keywords	= {free energy computation,GROMACS,molecular
		  dynamics,molecular simulation software,parallel
		  computation},
  annotation	= {\_eprint:
		  https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.20291},
  file		= {/Users/jana/Zotero/storage/WEXCI54H/Spoel et al. - 2005 -
		  GROMACS Fast, flexible, and
		  free.pdf;/Users/jana/Zotero/storage/AIUHCXR5/jcc.html}
}

@Article{	  Stern_Stern_2007_J.Chem.Phys.,
  title		= {Molecular Simulation with Variable Protonation States at
		  Constant {{pH}}},
  author	= {Stern, Harry A.},
  year		= {2007},
  month		= apr,
  journal	= {J. Chem. Phys.},
  volume	= {126},
  number	= {16},
  pages		= {164112},
  issn		= {0021-9606, 1089-7690},
  doi		= {10.1063/1.2731781},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/44XDBAUT/Stern - 2007 -
		  Molecular simulation with variable protonation sta.pdf}
}

@Article{	  Swails_Roitberg_2014_J.Chem.TheoryComput.,
  title		= {Constant {{pH Replica Exchange Molecular Dynamics}} in
		  {{Explicit Solvent Using Discrete Protonation States}}:
		  {{Implementation}}, {{Testing}}, and {{Validation}}},
  shorttitle	= {Constant {{pH Replica Exchange Molecular Dynamics}} in
		  {{Explicit Solvent Using Discrete Protonation States}}},
  author	= {Swails, Jason M. and York, Darrin M. and Roitberg, Adrian
		  E.},
  year		= {2014},
  month		= mar,
  journal	= {J. Chem. Theory Comput.},
  volume	= {10},
  number	= {3},
  pages		= {1341--1352},
  issn		= {1549-9618, 1549-9626},
  doi		= {10.1021/ct401042b},
  abstract	= {By utilizing Graphics Processing Units, we show that
		  constant pH molecular dynamics simulations (CpHMD) run in
		  Generalized Born (GB) implicit solvent for long time scales
		  can yield poor pKa predictions as a result of sampling
		  unrealistic conformations. To address this shortcoming, we
		  present a method for performing constant pH molecular
		  dynamics simulations (CpHMD) in explicit solvent using a
		  discrete protonation state model. The method involves
		  standard molecular dynamics (MD) being propagated in
		  explicit solvent followed by protonation state changes
		  being attempted in GB implicit solvent at fixed intervals.
		  Replica exchange along the pH-dimension (pH-REMD) helps to
		  obtain acceptable titration behavior with the proposed
		  method. We analyzed the effects of various parameters and
		  settings on the titration behavior of CpHMD and pH-REMD in
		  explicit solvent, including the size of the simulation unit
		  cell and the length of the relaxation dynamics following
		  protonation state changes. We tested the method with the
		  amino acid model compounds, a small pentapeptide with two
		  titratable sites, and hen egg white lysozyme (HEWL). The
		  proposed method yields superior predicted pKa values for
		  HEWL over hundreds of nanoseconds of simulation relative to
		  corresponding predicted values from simulations run in
		  implicit solvent.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/WQ2TK8ZC/Swails et al. - 2014 -
		  Constant pH Replica Exchange Molecular Dynamics in.pdf}
}

@Article{	  Waterhouse_Schwede_2018_NucleicAcidsRes.,
  title		= {{{SWISS}}-{{MODEL}}: Homology Modelling of Protein
		  Structures and Complexes},
  shorttitle	= {{{SWISS}}-{{MODEL}}},
  author	= {Waterhouse, Andrew and Bertoni, Martino and Bienert,
		  Stefan and Studer, Gabriel and Tauriello, Gerardo and
		  Gumienny, Rafal and Heer, Florian T and {de Beer}, Tjaart A
		  P and Rempfer, Christine and Bordoli, Lorenza and Lepore,
		  Rosalba and Schwede, Torsten},
  year		= {2018},
  month		= jul,
  journal	= {Nucleic Acids Res.},
  volume	= {46},
  number	= {W1},
  pages		= {W296-W303},
  issn		= {0305-1048, 1362-4962},
  doi		= {10.1093/nar/gky427},
  abstract	= {Homology modelling has matured into an important technique
		  in structural biology, significantly contributing to
		  narrowing the gap between known protein sequences and
		  experimentally determined structures. Fully automated
		  workflows and servers simplify and streamline the homology
		  modelling process, also allowing users without a specific
		  computational expertise to generate reliable protein models
		  and have easy access to modelling results, their
		  visualization and interpretation. Here, we present an
		  update to the SWISS-MODEL server, which pioneered the field
		  of automated modelling 25 years ago and been continuously
		  further developed. Recently, its functionality has been
		  extended to the modelling of homo- and heteromeric
		  complexes. Starting from the amino acid sequences of the
		  interacting proteins, both the stoichiometry and the
		  overall structure of the complex are inferred by homology
		  modelling. Other major improvements include the
		  implementation of a new modelling engine, ProMod3 and the
		  introduction a new local model quality estimation method,
		  QMEANDisCo. SWISS-MODEL is freely available at
		  https://swissmodel.expasy.org.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/N7W68BKS/Waterhouse et al. -
		  2018 - SWISS-MODEL homology modelling of protein
		  structu.pdf}
}

@Article{	  Ferguson_Fersht_2005_J.Mol.Biol.,
  title		= {Ultra-Fast {{Barrier}}-Limited {{Folding}} in the
		  {{Peripheral Subunit}}-Binding {{Domain Family}}},
  author	= {Ferguson, Neil and Sharpe, Timothy D. and Schartau, Pamela
		  J. and Sato, Satoshi and Allen, Mark D. and Johnson,
		  Christopher M. and Rutherford, Trevor J. and Fersht, Alan
		  R.},
  year		= {2005},
  month		= oct,
  journal	= {J. Mol. Biol.},
  volume	= {353},
  number	= {2},
  pages		= {427--446},
  issn		= {00222836},
  doi		= {10.1016/j.jmb.2005.08.031},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/ZHK8L4RC/Ferguson et al. - 2005
		  - Ultra-fast Barrier-limited Folding in the Peripher.pdf}
}

@Article{	  Chen_Brooks_2006_J.Am.Chem.Soc.,
  title		= {Balancing {{Solvation}} and {{Intramolecular
		  Interactions}}: {{Toward}} a {{Consistent Generalized Born
		  Force Field}}},
  shorttitle	= {Balancing {{Solvation}} and {{Intramolecular
		  Interactions}}},
  author	= {Chen, Jianhan and Im, Wonpil and {Brooks III}, Charles L.},
  year		= {2006},
  month		= mar,
  journal	= {J. Am. Chem. Soc.},
  volume	= {128},
  number	= {11},
  pages		= {3728--3736},
  issn		= {0002-7863, 1520-5126},
  doi		= {10.1021/ja057216r},
  abstract	= {The efficient and accurate characterization of solvent
		  effects is a key element in the theoretical and
		  computational study of biological problems. Implicit
		  solvent models, particularly generalized Born (GB)
		  continuum electrostatics, have emerged as an attractive
		  tool to study the structure and dynamics of biomolecules in
		  various environments. Despite recent advances in this
		  methodology, there remain limitations in the
		  parametrization of many of these models. In the present
		  work, we demonstrate that it is possible to achieve a
		  balanced implicit solvent force field by further optimizing
		  the input atomic radii in combination with adjusting the
		  protein backbone torsional energetics. This parameter
		  optimization is guided by the potentials of mean force
		  (PMFs) between amino acid polar groups, calculated from
		  explicit solvent free energy simulations, and by
		  conformational equilibria of short peptides, obtained from
		  extensive folding and unfolding replica exchange molecular
		  dynamics (REX-MD) simulations. Through the application of
		  this protocol, the delicate balance between the competing
		  solvation forces and intramolecular forces appears to be
		  better captured, and correct conformational equilibria for
		  a range of both helical and {$\beta$}-hairpin peptides are
		  obtained. The same optimized force field also successfully
		  folds both beta-hairpin trpzip2 and miniprotein Trp-Cage,
		  indicating that it is quite robust. Such a balanced,
		  physics-based force field will be highly applicable to a
		  range of biological problems including protein folding and
		  protein structural dynamics.},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/G4J53YT4/Chen et al. - 2006 -
		  Balancing Solvation and Intramolecular Interaction.pdf}
}

@Article{	  Klauda_Pastor_2010_J.Phys.Chem.B,
  title		= {Update of the {{CHARMM All}}-{{Atom Additive Force Field}}
		  for {{Lipids}}: {{Validation}} on {{Six Lipid Types}}},
  author	= {Klauda, Jeffery B and Venable, Richard M and Freites, J
		  Alfredo and O'Connor, Joseph W and Tobias, Douglas J and
		  {Mondragon-Ramirez}, Carlos and Vorobyov, Igor and
		  MacKerell, Jr, Alexander D and Pastor, Richard W},
  year		= {2010},
  journal	= {J. Phys. Chem. B},
  volume	= {114},
  pages		= {7830--7843},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/BPUMCXIY/Klauda et al. - Update
		  of the CHARMM All-Atom Additive Force Field.pdf},
  doi       = {10.1021/jp101759q}
}

@Article{	  MacKerell_Brooks_2004_J.Am.Chem.Soc.,
  title		= {Improved {{Treatment}} of the {{Protein Backbone}} in
		  {{Empirical Force Fields}}},
  author	= {MacKerell, Alexander D. and Feig, Michael and Brooks, III,
		  Charles L.},
  year		= {2004},
  month		= jan,
  journal	= {J. Am. Chem. Soc.},
  volume	= {126},
  number	= {3},
  pages		= {698--699},
  issn		= {0002-7863, 1520-5126},
  doi		= {10.1021/ja036959e},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/ES6FE5SP/MacKerell et al. -
		  2004 - Improved Treatment of the Protein Backbone in
		  Empi.pdf}
}

@Article{	  MacKerell_Karplus_1998_J.Phys.Chem.B,
  title		= {All-Atom Empirical Potential for Molecular
		  Modeling and Dynamics Studies of Proteins},
  author	= {MacKerell, Jr., A. D. and Bashford, D. and Bellott, M. and
		  Dunbrack, R. L. and Evanseck, J. D. and Field, M. J. and
		  Fischer, S. and Gao, J. and Guo, H. and Ha, S. and
		  {Joseph-McCarthy}, D. and Kuchnir, L. and Kuczera, K. and
		  Lau, F. T. K. and Mattos, C. and Michnick, S. and Ngo, T.
		  and Nguyen, D. T. and Prodhom, B. and Reiher, W. E. and
		  Roux, B. and Schlenkrich, M. and Smith, J. C. and Stote, R.
		  and Straub, J. and Watanabe, M. and
		  {Wi{\'o}rkiewicz-Kuczera}, J. and Yin, D. and Karplus, M.},
  year		= {1998},
  month		= apr,
  journal	= {J. Phys. Chem. B},
  volume	= {102},
  number	= {18},
  pages		= {3586--3616},
  issn		= {1520-6106, 1520-5207},
  doi		= {10.1021/jp973084f},
  language	= {en},
  file		= {/Users/jana/Zotero/storage/CJGGT9ZC/MacKerell et al. -
		  1998 - All-Atom Empirical Potential for Molecular
		  Modelin.pdf}
}

@article{Liu_Shen_2022_RSCMed.Chem.,
  title = {Profiling {{MAP}} Kinase Cysteines for Targeted Covalent Inhibitor Design},
  author = {Liu, Ruibin and Verma, Neha and Henderson, Jack A. and Zhan, Shaoqi and Shen, Jana},
  year = {2022},
  volume = {13},
  issue = {1},
  page = {54–63},
  journal = {RSC Med. Chem.},
  publisher = {{RSC}},
  issn = {2632-8682},
  doi = {10.1039/D1MD00277E},
    langid = {english},
  file = {/Users/jana/Zotero/storage/KMRYUA75/Liu et al. - 2021 - Profiling MAP kinase cysteines for targeted covale.pdf;/Users/jana/Zotero/storage/566226AL/d1md00277e.html}
}

@article{Casey_Orlowski_2010_Nat.Rev.Mol.CellBiol.,
  title = {Sensors and Regulators of Intracellular {{pH}}},
  author = {Casey, Joseph R. and Grinstein, Sergio and Orlowski, John},
  year = {2010},
  month = jan,
  journal = {Nat. Rev. Mol. Cell Biol.},
  volume = {11},
  number = {1},
  pages = {50--61},
  issn = {1471-0072, 1471-0080},
  doi = {10.1038/nrm2820}
}

@article{Roos_Boron_1981_Physiol.Rev.,
  title = {Intracellular {{pH}}.},
  author = {Roos, A and Boron, W F},
  year = {1981},
  journal = {Physiol. Rev.},
  volume = {61},
  pages = {292--421},
  langid = {english},
  file = {../../../Zotero/storage/7K6WW99Z/physrev.1981.61.2.pdf},
  doi   = {10.1152/physrev.1981.61.2.296}
}

@article{Webb_Barber_2011_Nat.Rev.Cancer,
  title = {Dysregulated {{pH}}: A Perfect Storm for Cancer Progression},
  shorttitle = {Dysregulated {{pH}}},
  author = {Webb, Bradley A. and Chimenti, Michael and Jacobson, Matthew P. and Barber, Diane L.},
  year = {2011},
  month = sep,
  journal = {Nat. Rev. Cancer},
  volume = {11},
  number = {9},
  pages = {671--677},
  publisher = {{Nature Publishing Group}},
  issn = {1474-1768},
  doi = {10.1038/nrc3110}
}

@article{Liu_Shen_2022_J.Med.Chem.,
  title = {Reactivities of the {{Front Pocket N-Terminal Cap Cysteines}} in {{Human Kinases}}},
  author = {Liu, Ruibin and Zhan, Shaoqi and Che, Ye and Shen, Jana},
  year = {2022},
  volume = {65},
  month = oct,
  journal = {J. Med. Chem.},
  pages = {1525–1535},
  issue = {2},
  issn = {0022-2623, 1520-4804},
  doi = {10.1021/acs.jmedchem.1c01186}
}                                           

@article{Alexov_Word_2011_Proteins,
  title = {Progress in the Prediction of pKa Values in Proteins},
  author = {Alexov, Emil and Mehler, Ernest L. and Baker, Nathan and M. Baptista, Ant{\'o}nio and Huang, Yong and Milletti, Francesca and Erik Nielsen, Jens and Farrell, Damien and Carstensen, Tommy and Olsson, Mats H. M. and Shen, Jana K. and Warwicker, Jim and Williams, Sarah and Word, J. Michael},
  year = {2011},
  month = dec,
  journal = {Proteins},
  volume = {79},
  number = {12},
  pages = {3260--3275},
  issn = {08873585},
  doi = {10.1002/prot.23189},
  langid = {english},
  file = {../../../Zotero/storage/FZPW8SV7/Alexov et al. - 2011 - Progress in the prediction of p K as.pdf}
}

@article{Mahinthichaichan_Shen_2021_JACSAu,
  title = {Kinetics and {{Mechanism}} of {{Fentanyl Dissociation}} from the {$\mu$}-{{Opioid Receptor}}},
  author = {Mahinthichaichan, Paween and Vo, Quynh N. and Ellis, Christopher R. and Shen, Jana},
  year = {2021},
  month = dec,
  journal = {JACS Au},
  volume = {1},
  number = {12},
  pages = {2208--2215},
  issn = {2691-3704, 2691-3704},
  doi = {10.1021/jacsau.1c00341}
}

@article{Platzer_McIntosh_2014_J.Biomol.NMR,
  title = {{{pH-dependent}} Random Coil {{1H}}, {{13C}}, and {{15N}} Chemical Shifts of the Ionizable Amino Acids: A Guide for Protein {{pK}} a Measurements},
  shorttitle = {{{pH-dependent}} Random Coil {{1H}}, {{13C}}, and {{15N}} Chemical Shifts of the Ionizable Amino Acids},
  author = {Platzer, Gerald and Okon, Mark and McIntosh, Lawrence P.},
  year = {2014},
  month = nov,
  journal = {J. Biomol. NMR},
  volume = {60},
  number = {2-3},
  pages = {109--129},
  issn = {0925-2738, 1573-5001},
  doi = {10.1007/s10858-014-9862-y},
  langid = {english},
  file = {/Users/jana/Zotero/storage/L7IVZK4Q/Platzer_JBiomolNMR_2014_v60_p109.pdf}
}

@article{Morrow_Shen_2014_J.Chem.Phys.,
  title = {Predicting Proton Titration in Cationic Micelle and Bilayer Environments},
  author = {Morrow, Brian H. and Eike, David M. and Murch, Bruce P. and Koenig, Peter H. and Shen, Jana K.},
  year = {2014},
  month = aug,
  journal = {J. Chem. Phys.},
  volume = {141},
  number = {8},
  pages = {084714},
  issn = {0021-9606, 1089-7690},
  doi = {10.1063/1.4893439},
  langid = {english},
  file = {/Users/jana/Zotero/storage/QTKUHSSB/Morrow et al. - 2014 - Predicting proton titration in cationic micelle an.pdf}
}

@article{Burgi_vanGunsteren_2002_Proteins,
  title = {Simulating Proteins at Constant {{pH}}: {{An}} Approach Combining Molecular Dynamics and {{Monte Carlo}} Simulation},
  shorttitle = {Simulating Proteins at Constant {{pH}}},
  author = {B{\"u}rgi, Roland and Kollman, Peter A. and {van Gunsteren}, Wilfred F.},
  year = {2002},
  journal = {Proteins},
  volume = {47},
  number = {4},
  pages = {469--480},
  doi = {10.1002/prot.10046}
}

@article{Harris_Shen_Submitted,
  title = {GPU-Accelerated All-atom Particle-Mesh Ewald Continuous Constant pH Molecular Dynamics in Amber},
  author = {Harris, Julie A. and Liu, Ruibin and {Vazquez Montelongo}, Erik and {Martins de Oliveira}, Vinicius and Henderson, Jack A. and Shen, Jana},
  year = {2022},
  journal = {bioRxiv},
  doi = {10.1101/2022.06.04.494833}
}

@article{Hayes_Brooks_2021_J.Chem.TheoryComput.,
  title = {{{BLaDE}}: {{A Basic Lambda Dynamics Engine}} for {{GPU-Accelerated Molecular Dynamics Free Energy Calculations}}},
  shorttitle = {{{BLaDE}}},
  author = {Hayes, Ryan L. and Buckner, Joshua and {Brooks III}, Charles L.},
  year = {2021},
  month = nov,
  journal = {J. Chem. Theory Comput.},
  volume = {17},
  number = {11},
  pages = {6799--6807},
  doi = {10.1021/acs.jctc.1c00833}
}

@article{Knight_Brooks_2011_J.Chem.TheoryComput.,
  title = {Multisite {$\lambda$} {{Dynamics}} for {{Simulated Structure}}\textendash{{Activity Relationship Studies}}},
  author = {Knight, Jennifer L. and Brooks, Charles L.},
  year = {2011},
  month = sep,
  journal = {J. Chem. Theory Comput.},
  volume = {7},
  number = {9},
  pages = {2728--2739},
  issn = {1549-9618, 1549-9626},
  doi = {10.1021/ct200444f},
  langid = {english},
  file = {/Users/jana/Zotero/storage/3IAG3AVG/Knight_JChemTheoryComput_2011_v7_p2728.pdf}
}

@article{Donnini_Grubmuller_2011_J.Chem.TheoryComput.,
  title = {Constant {{pH Molecular Dynamics}} in {{Explicit Solvent}} with {$\lambda$}-{{Dynamics}}},
  author = {Donnini, Serena and Tegeler, Florian and Groenhof, Gerrit and Grubm{\"u}ller, Helmut},
  year = {2011},
  month = jun,
  journal = {J. Chem. Theory Comput.},
  volume = {7},
  number = {6},
  pages = {1962--1978},
  issn = {1549-9618, 1549-9626},
  doi = {10.1021/ct200061r},
  langid = {english},
  file = {/Users/jana/Zotero/storage/M3J8BGFK/Donnini_JChemTheoryComput_2011_v7_p1962.pdf}
}