Literature DB >> 28306259

Building a More Predictive Protein Force Field: A Systematic and Reproducible Route to AMBER-FB15.

Lee-Ping Wang1, Keri A McKiernan2, Joseph Gomes2, Kyle A Beauchamp3, Teresa Head-Gordon4,5, Julia E Rice6, William C Swope6, Todd J Martínez2,7,8, Vijay S Pande2,9.   

Abstract

The increasing availability of high-quality experimental data and first-principles calculations creates opportunities for developing more accurate empirical force fields for simulation of proteins. We developed the AMBER-FB15 protein force field by building a high-quality quantum chemical data set consisting of comprehensive potential energy scans and employing the ForceBalance software package for parameter optimization. The optimized potential surface allows for more significant thermodynamic fluctuations away from local minima. In validation studies where simulation results are compared to experimental measurements, AMBER-FB15 in combination with the updated TIP3P-FB water model predicts equilibrium properties with equivalent accuracy, and temperature dependent properties with significantly improved accuracy, in comparison with published models. We also discuss the effect of changing the protein force field and water model on the simulation results.

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Year:  2017        PMID: 28306259     DOI: 10.1021/acs.jpcb.7b02320

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  57 in total

1.  Toward Learned Chemical Perception of Force Field Typing Rules.

Authors:  Camila Zanette; Caitlin C Bannan; Christopher I Bayly; Josh Fass; Michael K Gilson; Michael R Shirts; John D Chodera; David L Mobley
Journal:  J Chem Theory Comput       Date:  2018-12-24       Impact factor: 6.006

2.  AMOEBA+ Classical Potential for Modeling Molecular Interactions.

Authors:  Chengwen Liu; Jean-Philip Piquemal; Pengyu Ren
Journal:  J Chem Theory Comput       Date:  2019-06-11       Impact factor: 6.006

Review 3.  Force field development and simulations of intrinsically disordered proteins.

Authors:  Jing Huang; Alexander D MacKerell
Journal:  Curr Opin Struct Biol       Date:  2017-11-05       Impact factor: 6.809

Review 4.  Force field development phase II: Relaxation of physics-based criteria… or inclusion of more rigorous physics into the representation of molecular energetics.

Authors:  A T Hagler
Journal:  J Comput Aided Mol Des       Date:  2018-11-30       Impact factor: 3.686

5.  Driving torsion scans with wavefront propagation.

Authors:  Yudong Qiu; Daniel G A Smith; Chaya D Stern; Mudong Feng; Hyesu Jang; Lee-Ping Wang
Journal:  J Chem Phys       Date:  2020-06-28       Impact factor: 3.488

6.  A physically grounded damped dispersion model with particle mesh Ewald summation.

Authors:  Joshua A Rackers; Chengwen Liu; Pengyu Ren; Jay W Ponder
Journal:  J Chem Phys       Date:  2018-08-28       Impact factor: 3.488

7.  Dissecting the Energetics of Intrinsically Disordered Proteins via a Hybrid Experimental and Computational Approach.

Authors:  Junjie Zou; Carlos Simmerling; Daniel P Raleigh
Journal:  J Phys Chem B       Date:  2019-12-03       Impact factor: 2.991

8.  Computational structural enzymology methodologies for the study and engineering of fatty acid synthases, polyketide synthases and nonribosomal peptide synthetases.

Authors:  Andrew J Schaub; Gabriel O Moreno; Shiji Zhao; Hau V Truong; Ray Luo; Shiou-Chuan Tsai
Journal:  Methods Enzymol       Date:  2019-04-22       Impact factor: 1.600

Review 9.  Whole-Cell Models and Simulations in Molecular Detail.

Authors:  Michael Feig; Yuji Sugita
Journal:  Annu Rev Cell Dev Biol       Date:  2019-07-12       Impact factor: 13.827

10.  Escaping Atom Types in Force Fields Using Direct Chemical Perception.

Authors:  David L Mobley; Caitlin C Bannan; Andrea Rizzi; Christopher I Bayly; John D Chodera; Victoria T Lim; Nathan M Lim; Kyle A Beauchamp; David R Slochower; Michael R Shirts; Michael K Gilson; Peter K Eastman
Journal:  J Chem Theory Comput       Date:  2018-10-30       Impact factor: 6.006

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