skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: ff19SB: Amino-acid specific protein backbone parameters trained against quantum mechanics energy surfaces in solution

Abstract

Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled Φ/ψ parameters using 2D Φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, we have performed a total of ~5 milliseconds MD simulations in explicit solvent. Here, our results show that after amino-acid specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino acid specific Protein Data Bank (PDB) Ramachandran maps better, but alsomore » shows significantly improved capability to differentiate amino acid dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design.« less

Authors:
 [1];  [1];  [1];  [1];  [1];  [2];  [3];  [1];  [3]; ORCiD logo [4];  [1]
  1. Stony Brook Univ., Stony Brook, NY (United States). Dept. of Chemistry and Laufer Center for Physical and Quantitative Biology
  2. Stony Brook Univ., Stony Brook, NY (United States). Laufer Center for Physical and Quantitative Biology
  3. Stony Brook Univ., Stony Brook, NY (United States). Dept. of Chemistry
  4. Brookhaven National Lab. (BNL), Upton, NY (United States). Center for Functional Nanomaterials
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1574918
Report Number(s):
BNL-212345-2019-JAAM
Journal ID: ISSN 1549-9618; TRN: US2001253
Grant/Contract Number:  
SC0012704
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Chemical Theory and Computation
Additional Journal Information:
Journal Volume: 16; Journal Issue: 1; Journal ID: ISSN 1549-9618
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
77 NANOSCIENCE AND NANOTECHNOLOGY

Citation Formats

Tian, Chuan, Kasavajhala, Koushik, Belfon, Kellon A. A., Raguette, Lauren, Huang, He, Migues, Angela N., Bickel, John, Wang, Yuzhang, Pincay, Jorge, Wu, Qin, and Simmerling, Carlos. ff19SB: Amino-acid specific protein backbone parameters trained against quantum mechanics energy surfaces in solution. United States: N. p., 2019. Web. doi:10.1021/acs.jctc.9b00591.
Tian, Chuan, Kasavajhala, Koushik, Belfon, Kellon A. A., Raguette, Lauren, Huang, He, Migues, Angela N., Bickel, John, Wang, Yuzhang, Pincay, Jorge, Wu, Qin, & Simmerling, Carlos. ff19SB: Amino-acid specific protein backbone parameters trained against quantum mechanics energy surfaces in solution. United States. doi:https://doi.org/10.1021/acs.jctc.9b00591
Tian, Chuan, Kasavajhala, Koushik, Belfon, Kellon A. A., Raguette, Lauren, Huang, He, Migues, Angela N., Bickel, John, Wang, Yuzhang, Pincay, Jorge, Wu, Qin, and Simmerling, Carlos. Tue . "ff19SB: Amino-acid specific protein backbone parameters trained against quantum mechanics energy surfaces in solution". United States. doi:https://doi.org/10.1021/acs.jctc.9b00591. https://www.osti.gov/servlets/purl/1574918.
@article{osti_1574918,
title = {ff19SB: Amino-acid specific protein backbone parameters trained against quantum mechanics energy surfaces in solution},
author = {Tian, Chuan and Kasavajhala, Koushik and Belfon, Kellon A. A. and Raguette, Lauren and Huang, He and Migues, Angela N. and Bickel, John and Wang, Yuzhang and Pincay, Jorge and Wu, Qin and Simmerling, Carlos},
abstractNote = {Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled Φ/ψ parameters using 2D Φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, we have performed a total of ~5 milliseconds MD simulations in explicit solvent. Here, our results show that after amino-acid specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino acid specific Protein Data Bank (PDB) Ramachandran maps better, but also shows significantly improved capability to differentiate amino acid dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design.},
doi = {10.1021/acs.jctc.9b00591},
journal = {Journal of Chemical Theory and Computation},
number = 1,
volume = 16,
place = {United States},
year = {2019},
month = {11}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 8 works
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

How Fast-Folding Proteins Fold
journal, October 2011


Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field
journal, February 2015

  • Wang, Lingle; Wu, Yujie; Deng, Yuqing
  • Journal of the American Chemical Society, Vol. 137, Issue 7
  • DOI: 10.1021/ja512751q

Determination of Electrostatic Parameters for a Polarizable Force Field Based on the Classical Drude Oscillator
journal, October 2004

  • Anisimov, Victor M.; Lamoureux, Guillaume; Vorobyov, Igor V.
  • Journal of Chemical Theory and Computation, Vol. 1, Issue 1
  • DOI: 10.1021/ct049930p

A simple polarizable model of water based on classical Drude oscillators
journal, September 2003

  • Lamoureux, Guillaume; MacKerell, Alexander D.; Roux, Benoı̂t
  • The Journal of Chemical Physics, Vol. 119, Issue 10
  • DOI: 10.1063/1.1598191

Current Status of the AMOEBA Polarizable Force Field
journal, March 2010

  • Ponder, Jay W.; Wu, Chuanjie; Ren, Pengyu
  • The Journal of Physical Chemistry B, Vol. 114, Issue 8
  • DOI: 10.1021/jp910674d

The Amber biomolecular simulation programs
journal, January 2005

  • Case, David A.; Cheatham, Thomas E.; Darden, Tom
  • Journal of Computational Chemistry, Vol. 26, Issue 16
  • DOI: 10.1002/jcc.20290

Comparison of multiple Amber force fields and development of improved protein backbone parameters
journal, November 2006

  • Hornak, Viktor; Abel, Robert; Okur, Asim
  • Proteins: Structure, Function, and Bioinformatics, Vol. 65, Issue 3
  • DOI: 10.1002/prot.21123

A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules
journal, May 1995

  • Cornell, Wendy D.; Cieplak, Piotr; Bayly, Christopher I.
  • Journal of the American Chemical Society, Vol. 117, Issue 19
  • DOI: 10.1021/ja00124a002

Using PC clusters to evaluate the transferability of molecular mechanics force fields for proteins
journal, December 2002

  • Okur, Asim; Strockbine, Bentley; Hornak, Viktor
  • Journal of Computational Chemistry, Vol. 24, Issue 1
  • DOI: 10.1002/jcc.10184

 -Helical stabilization by side chain shielding of backbone hydrogen bonds
journal, February 2002

  • Garcia, A. E.; Sanbonmatsu, K. Y.
  • Proceedings of the National Academy of Sciences, Vol. 99, Issue 5
  • DOI: 10.1073/pnas.042496899

Accurate ab Initio Quantum Chemical Determination of the Relative Energetics of Peptide Conformations and Assessment of Empirical Force Fields
journal, June 1997

  • Beachy, Michael D.; Chasman, David; Murphy, Robert B.
  • Journal of the American Chemical Society, Vol. 119, Issue 25
  • DOI: 10.1021/ja962310g

Residue-Specific α-Helix Propensities from Molecular Simulation
journal, March 2012


ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB
journal, July 2015

  • Maier, James A.; Martinez, Carmenza; Kasavajhala, Koushik
  • Journal of Chemical Theory and Computation, Vol. 11, Issue 8
  • DOI: 10.1021/acs.jctc.5b00255

Molecular dynamics simulation of triclinic lysozyme in a crystal lattice: Molecular Dynamics of Crystal Lysozyme
journal, June 2015

  • Janowski, Pawel A.; Liu, Chunmei; Deckman, Jason
  • Protein Science, Vol. 25, Issue 1
  • DOI: 10.1002/pro.2713

Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone ϕ, ψ and Side-Chain χ 1 and χ 2 Dihedral Angles
journal, August 2012

  • Best, Robert B.; Zhu, Xiao; Shim, Jihyun
  • Journal of Chemical Theory and Computation, Vol. 8, Issue 9
  • DOI: 10.1021/ct300400x

Optimized Molecular Dynamics Force Fields Applied to the Helix−Coil Transition of Polypeptides
journal, July 2009

  • Best, Robert B.; Hummer, Gerhard
  • The Journal of Physical Chemistry B, Vol. 113, Issue 26
  • DOI: 10.1021/jp901540t

Balanced Protein–Water Interactions Improve Properties of Disordered Proteins and Non-Specific Protein Association
journal, October 2014

  • Best, Robert B.; Zheng, Wenwei; Mittal, Jeetain
  • Journal of Chemical Theory and Computation, Vol. 10, Issue 11
  • DOI: 10.1021/ct500569b

Are Current Molecular Dynamics Force Fields too Helical?
journal, July 2008


A Test on Peptide Stability of AMBER Force Fields with Implicit Solvation
journal, June 2008

  • Shell, M. Scott; Ritterson, Ryan; Dill, Ken A.
  • The Journal of Physical Chemistry B, Vol. 112, Issue 22
  • DOI: 10.1021/jp800282x

All-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins
journal, April 1998

  • MacKerell, A. D.; Bashford, D.; Bellott, M.
  • The Journal of Physical Chemistry B, Vol. 102, Issue 18
  • DOI: 10.1021/jp973084f

Balancing Solvation and Intramolecular Interactions:  Toward a Consistent Generalized Born Force Field
journal, March 2006

  • Chen, Jianhan; Im, Wonpil; Brooks, Charles L.
  • Journal of the American Chemical Society, Vol. 128, Issue 11
  • DOI: 10.1021/ja057216r

Development of an improved four-site water model for biomolecular simulations: TIP4P-Ew
journal, May 2004

  • Horn, Hans W.; Swope, William C.; Pitera, Jed W.
  • The Journal of Chemical Physics, Vol. 120, Issue 20
  • DOI: 10.1063/1.1683075

Further along the Road Less Traveled: AMBER ff15ipq, an Original Protein Force Field Built on a Self-Consistent Physical Model
journal, July 2016

  • Debiec, Karl T.; Cerutti, David S.; Baker, Lewis R.
  • Journal of Chemical Theory and Computation, Vol. 12, Issue 8
  • DOI: 10.1021/acs.jctc.6b00567

Water Model Tuning for Improved Reproduction of Rotational Diffusion and NMR Spectral Density
journal, May 2012

  • Takemura, Kazuhiro; Kitao, Akio
  • The Journal of Physical Chemistry B, Vol. 116, Issue 22
  • DOI: 10.1021/jp301100g

Structural Ensembles of Intrinsically Disordered Proteins Depend Strongly on Force Field: A Comparison to Experiment
journal, October 2015

  • Rauscher, Sarah; Gapsys, Vytautas; Gajda, Michal J.
  • Journal of Chemical Theory and Computation, Vol. 11, Issue 11
  • DOI: 10.1021/acs.jctc.5b00736

Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulations
journal, February 2014

  • Piana, Stefano; Klepeis, John L.; Shaw, David E.
  • Current Opinion in Structural Biology, Vol. 24
  • DOI: 10.1016/j.sbi.2013.12.006

New Force Field on Modeling Intrinsically Disordered Proteins
journal, July 2014

  • Wang, Wei; Ye, Wei; Jiang, Cheng
  • Chemical Biology & Drug Design, Vol. 84, Issue 3
  • DOI: 10.1111/cbdd.12314

Developing a molecular dynamics force field for both folded and disordered protein states
journal, May 2018

  • Robustelli, Paul; Piana, Stefano; Shaw, David E.
  • Proceedings of the National Academy of Sciences, Vol. 115, Issue 21
  • DOI: 10.1073/pnas.1800690115

Molecular Dynamics Simulations of Intrinsically Disordered Proteins: Force Field Evaluation and Comparison with Experiment
journal, June 2015

  • Henriques, João; Cragnell, Carolina; Skepö, Marie
  • Journal of Chemical Theory and Computation, Vol. 11, Issue 7
  • DOI: 10.1021/ct501178z

Water Dispersion Interactions Strongly Influence Simulated Structural Properties of Disordered Protein States
journal, April 2015

  • Piana, Stefano; Donchev, Alexander G.; Robustelli, Paul
  • The Journal of Physical Chemistry B, Vol. 119, Issue 16
  • DOI: 10.1021/jp508971m

Are Current Atomistic Force Fields Accurate Enough to Study Proteins in Crowded Environments?
journal, May 2014


Building Water Models: A Different Approach
journal, October 2014

  • Izadi, Saeed; Anandakrishnan, Ramu; Onufriev, Alexey V.
  • The Journal of Physical Chemistry Letters, Vol. 5, Issue 21
  • DOI: 10.1021/jz501780a

General Purpose Water Model Can Improve Atomistic Simulations of Intrinsically Disordered Proteins
journal, March 2019

  • Shabane, Parviz Seifpanahi; Izadi, Saeed; Onufriev, Alexey V.
  • Journal of Chemical Theory and Computation, Vol. 15, Issue 4
  • DOI: 10.1021/acs.jctc.8b01123

Are Protein Force Fields Getting Better? A Systematic Benchmark on 524 Diverse NMR Measurements
journal, March 2012

  • Beauchamp, Kyle A.; Lin, Yu-Shan; Das, Rhiju
  • Journal of Chemical Theory and Computation, Vol. 8, Issue 4
  • DOI: 10.1021/ct2007814

Anton, a special-purpose machine for molecular dynamics simulation
journal, July 2008

  • Shaw, David E.; Chao, Jack C.; Eastwood, Michael P.
  • Communications of the ACM, Vol. 51, Issue 7
  • DOI: 10.1145/1364782.1364802

Folding Simulations for Proteins with Diverse Topologies Are Accessible in Days with a Physics-Based Force Field and Implicit Solvent
journal, August 2014

  • Nguyen, Hai; Maier, James; Huang, He
  • Journal of the American Chemical Society, Vol. 136, Issue 40
  • DOI: 10.1021/ja5032776

CHARMM36m: an improved force field for folded and intrinsically disordered proteins
journal, November 2016

  • Huang, Jing; Rauscher, Sarah; Nawrocki, Grzegorz
  • Nature Methods, Vol. 14, Issue 1
  • DOI: 10.1038/nmeth.4067

The penultimate rotamer library
journal, January 2000


Structure and Dynamics of the Homologous Series of Alanine Peptides:  A Joint Molecular Dynamics/NMR Study
journal, February 2007

  • Graf, Jürgen; Nguyen, Phuong H.; Stock, Gerhard
  • Journal of the American Chemical Society, Vol. 129, Issue 5
  • DOI: 10.1021/ja0660406

The IDP-Specific Force Field ff14IDPSFF Improves the Conformer Sampling of Intrinsically Disordered Proteins
journal, May 2017

  • Song, Dong; Luo, Ray; Chen, Hai-Feng
  • Journal of Chemical Information and Modeling, Vol. 57, Issue 5
  • DOI: 10.1021/acs.jcim.7b00135

An Improved Empirical Potential Energy Function for Molecular Simulations of Phospholipids
journal, August 2000

  • Feller, Scott E.; MacKerell, Alexander D.
  • The Journal of Physical Chemistry B, Vol. 104, Issue 31
  • DOI: 10.1021/jp0007843

A new force field for molecular mechanical simulation of nucleic acids and proteins
journal, February 1984

  • Weiner, Scott J.; Kollman, Peter A.; Case, David A.
  • Journal of the American Chemical Society, Vol. 106, Issue 3
  • DOI: 10.1021/ja00315a051

An all atom force field for simulations of proteins and nucleic acids: An All Atom Force Field
journal, April 1986

  • Weiner, Scott J.; Kollman, Peter A.; Nguyen, Dzung T.
  • Journal of Computational Chemistry, Vol. 7, Issue 2
  • DOI: 10.1002/jcc.540070216

A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules J . Am . Chem . Soc . 1995 , 117 , 5179−5197
journal, January 1996

  • Cornell, Wendy D.; Cieplak, Piotr; Bayly, Christopher I.
  • Journal of the American Chemical Society, Vol. 118, Issue 9
  • DOI: 10.1021/ja955032e

A well-behaved electrostatic potential based method using charge restraints for deriving atomic charges: the RESP model
journal, October 1993

  • Bayly, Christopher I.; Cieplak, Piotr; Cornell, Wendy
  • The Journal of Physical Chemistry, Vol. 97, Issue 40
  • DOI: 10.1021/j100142a004

Importance of the CMAP Correction to the CHARMM22 Protein Force Field: Dynamics of Hen Lysozyme
journal, February 2006


Building Force Fields: An Automatic, Systematic, and Reproducible Approach
journal, May 2014

  • Wang, Lee-Ping; Martinez, Todd J.; Pande, Vijay S.
  • The Journal of Physical Chemistry Letters, Vol. 5, Issue 11
  • DOI: 10.1021/jz500737m

Empirical force fields for biological macromolecules: Overview and issues
journal, January 2004

  • Mackerell, Alexander D.
  • Journal of Computational Chemistry, Vol. 25, Issue 13
  • DOI: 10.1002/jcc.20082

A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations
journal, October 2003

  • Duan, Yong; Wu, Chun; Chowdhury, Shibasish
  • Journal of Computational Chemistry, Vol. 24, Issue 16
  • DOI: 10.1002/jcc.10349

Derivation of Fixed Partial Charges for Amino Acids Accommodating a Specific Water Model and Implicit Polarization
journal, February 2013

  • Cerutti, David S.; Rice, Julia E.; Swope, William C.
  • The Journal of Physical Chemistry B, Vol. 117, Issue 8
  • DOI: 10.1021/jp311851r

Refinement of the Cornell et al. Nucleic Acids Force Field Based on Reference Quantum Chemical Calculations of Glycosidic Torsion Profiles
journal, August 2011

  • Zgarbová, Marie; Otyepka, Michal; Šponer, Jiří
  • Journal of Chemical Theory and Computation, Vol. 7, Issue 9
  • DOI: 10.1021/ct200162x

Building a More Predictive Protein Force Field: A Systematic and Reproducible Route to AMBER-FB15
journal, April 2017

  • Wang, Lee-Ping; McKiernan, Keri A.; Gomes, Joseph
  • The Journal of Physical Chemistry B, Vol. 121, Issue 16
  • DOI: 10.1021/acs.jpcb.7b02320

The Protein Data Bank
journal, January 2000


Comparison of simple potential functions for simulating liquid water
journal, July 1983

  • Jorgensen, William L.; Chandrasekhar, Jayaraman; Madura, Jeffry D.
  • The Journal of Chemical Physics, Vol. 79, Issue 2
  • DOI: 10.1063/1.445869

Improved Generalized Born Solvent Model Parameters for Protein Simulations
journal, March 2013

  • Nguyen, Hai; Roe, Daniel R.; Simmerling, Carlos
  • Journal of Chemical Theory and Computation, Vol. 9, Issue 4
  • DOI: 10.1021/ct3010485

Generalized Born Model with a Simple, Robust Molecular Volume Correction
journal, December 2006

  • Mongan, John; Simmerling, Carlos; McCammon, J. Andrew
  • Journal of Chemical Theory and Computation, Vol. 3, Issue 1
  • DOI: 10.1021/ct600085e

Structure of ubiquitin refined at 1.8 Å resolution
journal, April 1987

  • Vijay-kumar, Senadhi; Bugg, Charles E.; Cook, William J.
  • Journal of Molecular Biology, Vol. 194, Issue 3
  • DOI: 10.1016/0022-2836(87)90679-6

Development and testing of a general amber force field
journal, January 2004

  • Wang, Junmei; Wolf, Romain M.; Caldwell, James W.
  • Journal of Computational Chemistry, Vol. 25, Issue 9
  • DOI: 10.1002/jcc.20035

Structure validation by Cα geometry: ϕ,ψ and Cβ deviation
journal, January 2003

  • Lovell, Simon C.; Davis, Ian W.; Arendall, W. Bryan
  • Proteins: Structure, Function, and Bioinformatics, Vol. 50, Issue 3
  • DOI: 10.1002/prot.10286

CHAMBER: Comprehensive support for CHARMM force fields within the AMBER software
journal, December 2009

  • Crowley, Michael F.; Williamson, Mark J.; Walker, Ross C.
  • International Journal of Quantum Chemistry, Vol. 109, Issue 15
  • DOI: 10.1002/qua.22372

Universal Solvation Model Based on Solute Electron Density and on a Continuum Model of the Solvent Defined by the Bulk Dielectric Constant and Atomic Surface Tensions
journal, May 2009

  • Marenich, Aleksandr V.; Cramer, Christopher J.; Truhlar, Donald G.
  • The Journal of Physical Chemistry B, Vol. 113, Issue 18, p. 6378-6396
  • DOI: 10.1021/jp810292n

Continuous surface charge polarizable continuum models of solvation. I. General formalism
journal, March 2010

  • Scalmani, Giovanni; Frisch, Michael J.
  • The Journal of Chemical Physics, Vol. 132, Issue 11
  • DOI: 10.1063/1.3359469

Design of Density Functionals by Combining the Method of Constraint Satisfaction with Parametrization for Thermochemistry, Thermochemical Kinetics, and Noncovalent Interactions
journal, January 2006

  • Zhao, Yan; Schultz, Nathan E.; Truhlar, Donald G.
  • Journal of Chemical Theory and Computation, Vol. 2, Issue 2
  • DOI: 10.1021/ct0502763

A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu
journal, April 2010

  • Grimme, Stefan; Antony, Jens; Ehrlich, Stephan
  • The Journal of Chemical Physics, Vol. 132, Issue 15
  • DOI: 10.1063/1.3382344

Atomic charges derived from semiempirical methods
journal, May 1990

  • Besler, Brent H.; Merz, Kenneth M.; Kollman, Peter A.
  • Journal of Computational Chemistry, Vol. 11, Issue 4
  • DOI: 10.1002/jcc.540110404

An approach to computing electrostatic charges for molecules
journal, April 1984

  • Singh, U. Chandra; Kollman, Peter A.
  • Journal of Computational Chemistry, Vol. 5, Issue 2
  • DOI: 10.1002/jcc.540050204

Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes
journal, March 1977

  • Ryckaert, Jean-Paul; Ciccotti, Giovanni; Berendsen, Herman J. C.
  • Journal of Computational Physics, Vol. 23, Issue 3
  • DOI: 10.1016/0021-9991(77)90098-5

Towards an accurate representation of electrostatics in classical force fields: Efficient implementation of multipolar interactions in biomolecular simulations
journal, January 2004

  • Sagui, Celeste; Pedersen, Lee G.; Darden, Thomas A.
  • The Journal of Chemical Physics, Vol. 120, Issue 1
  • DOI: 10.1063/1.1630791

Long-Time-Step Molecular Dynamics through Hydrogen Mass Repartitioning
journal, March 2015

  • Hopkins, Chad W.; Le Grand, Scott; Walker, Ross C.
  • Journal of Chemical Theory and Computation, Vol. 11, Issue 4
  • DOI: 10.1021/ct5010406

PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data
journal, June 2013

  • Roe, Daniel R.; Cheatham, Thomas E.
  • Journal of Chemical Theory and Computation, Vol. 9, Issue 7
  • DOI: 10.1021/ct400341p

On the Theory of Helix—Coil Transition in Polypeptides
journal, June 1961

  • Lifson, Shneior; Roig, A.
  • The Journal of Chemical Physics, Vol. 34, Issue 6
  • DOI: 10.1063/1.1731802

Evaluating the Performance of the ff99SB Force Field Based on NMR Scalar Coupling Data
journal, August 2009


Contact Electron‐Spin Coupling of Nuclear Magnetic Moments
journal, January 1959

  • Karplus, Martin
  • The Journal of Chemical Physics, Vol. 30, Issue 1
  • DOI: 10.1063/1.1729860

Modification of the Generalized Born Model Suitable for Macromolecules
journal, April 2000

  • Onufriev, Alexey; Bashford, Donald; Case, David A.
  • The Journal of Physical Chemistry B, Vol. 104, Issue 15
  • DOI: 10.1021/jp994072s

Constant pH Replica Exchange Molecular Dynamics in Explicit Solvent Using Discrete Protonation States: Implementation, Testing, and Validation
journal, February 2014

  • Swails, Jason M.; York, Darrin M.; Roitberg, Adrian E.
  • Journal of Chemical Theory and Computation, Vol. 10, Issue 3
  • DOI: 10.1021/ct401042b

Model-free approach to the interpretation of nuclear magnetic resonance relaxation in macromolecules. 2. Analysis of experimental results
journal, August 1982

  • Lipari, Giovanni; Szabo, Attila
  • Journal of the American Chemical Society, Vol. 104, Issue 17
  • DOI: 10.1021/ja00381a010

Exploring Multiple Timescale Motions in Protein GB3 Using Accelerated Molecular Dynamics and NMR Spectroscopy
journal, April 2007

  • Markwick, Phineus R. L.; Bouvignies, Guillaume; Blackledge, Martin
  • Journal of the American Chemical Society, Vol. 129, Issue 15
  • DOI: 10.1021/ja0687668

MolProbity: More and better reference data for improved all-atom structure validation: PROTEIN SCIENCE.ORG
journal, November 2017

  • Williams, Christopher J.; Headd, Jeffrey J.; Moriarty, Nigel W.
  • Protein Science, Vol. 27, Issue 1
  • DOI: 10.1002/pro.3330

Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features
journal, December 1983


Biopython: freely available Python tools for computational molecular biology and bioinformatics
journal, March 2009


Rotamers: To be or not to be?
journal, March 1993

  • Schrauber, Hannelore; Eisenhaber, Frank; Argos, Patrick
  • Journal of Molecular Biology, Vol. 230, Issue 2
  • DOI: 10.1006/jmbi.1993.1172

A Helix Propensity Scale Based on Experimental Studies of Peptides and Proteins
journal, July 1998


The relation between the divergence of sequence and structure in proteins.
journal, April 1986


Protein Simulations with an Optimized Water Model: Cooperative Helix Formation and Temperature-Induced Unfolded State Collapse
journal, November 2010

  • Best, Robert B.; Mittal, Jeetain
  • The Journal of Physical Chemistry B, Vol. 114, Issue 46
  • DOI: 10.1021/jp108618d

A general purpose model for the condensed phases of water: TIP4P/2005
journal, December 2005

  • Abascal, J. L. F.; Vega, C.
  • The Journal of Chemical Physics, Vol. 123, Issue 23
  • DOI: 10.1063/1.2121687

Improved side-chain torsion potentials for the Amber ff99SB protein force field
journal, January 2010

  • Lindorff-Larsen, Kresten; Piana, Stefano; Palmo, Kim
  • Proteins: Structure, Function, and Bioinformatics
  • DOI: 10.1002/prot.22711

Secondary Structure Bias in Generalized Born Solvent Models:  Comparison of Conformational Ensembles and Free Energy of Solvent Polarization from Explicit and Implicit Solvation
journal, February 2007

  • Roe, Daniel R.; Okur, Asim; Wickstrom, Lauren
  • The Journal of Physical Chemistry B, Vol. 111, Issue 7
  • DOI: 10.1021/jp066831u

    Works referencing / citing this record:

    Bayesian-Maximum-Entropy Reweighting of IDP Ensembles Based on NMR Chemical Shifts
    journal, September 2019

    • Crehuet, Ramon; Buigues, Pedro J.; Salvatella, Xavier
    • Entropy, Vol. 21, Issue 9
    • DOI: 10.3390/e21090898

    Blinded prediction of protein–ligand binding affinity using Amber thermodynamic integration for the 2018 D3R grand challenge 4
    journal, September 2019

    • Zou, Junjie; Tian, Chuan; Simmerling, Carlos
    • Journal of Computer-Aided Molecular Design, Vol. 33, Issue 12
    • DOI: 10.1007/s10822-019-00223-x