title: Building a More Predictive Protein Force Field: A Systematic and Reproducible Route to AMBER-FB15.
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.
authors.affiliation: Department of Chemistry, University of California, Davis , Davis, California 95616, United States.
authors.forename: Lee-Ping
authors.identifier: 0000-0003-3072-9946
authors.initials: LP
authors.lastname: Wang
authors.affiliation: Department of Chemistry, Stanford University , Stanford, California 94305, United States.
authors.forename: Keri A
authors.initials: KA
authors.lastname: McKiernan
authors.affiliation: Department of Chemistry, Stanford University , Stanford, California 94305, United States.
authors.forename: Joseph
authors.initials: J
authors.lastname: Gomes
authors.affiliation: Counsyl, Inc. , South San Francisco, California 94080, United States.
authors.forename: Kyle A
authors.initials: KA
authors.lastname: Beauchamp
authors.affiliation: Departments of Chemistry, Bioengineering, Chemical and Biomolecular Engineering, and Kenneth S. Pitzer Center for Theoretical Chemistry, University of California, Berkeley , Berkeley, California 94720, United States.|Chemical Sciences Division, Physical Biosciences Division, Lawrence Berkeley National Laboratory , Berkeley, California 94720, United States.
authors.forename: Teresa
authors.identifier: 0000-0003-0025-8987
authors.initials: T
authors.lastname: Head-Gordon
authors.affiliation: IBM Almaden Research Center, IBM Research , San Jose, California 95120, United States.
authors.forename: Julia E
authors.initials: JE
authors.lastname: Rice
authors.affiliation: IBM Almaden Research Center, IBM Research , San Jose, California 95120, United States.
authors.forename: William C
authors.identifier: 0000-0002-5299-4145
authors.initials: WC
authors.lastname: Swope
authors.affiliation: Department of Chemistry, Stanford University , Stanford, California 94305, United States.|PULSE Institute, Stanford University , Stanford, California 94305, United States.|SLAC National Accelerator Laboratory , Menlo Park, California 94025, United States.
authors.forename: Todd J
authors.identifier: 0000-0002-4798-8947
authors.initials: TJ
authors.lastname: Martínez
authors.affiliation: Department of Chemistry, Stanford University , Stanford, California 94305, United States.|Departments of Computer Science, Structural Biology, and Program in Biophysics, Stanford University , Stanford, California 94305, United States.
authors.forename: Vijay S
authors.initials: VS
authors.lastname: Pande
mesh_terms: D030562:Databases, Protein; D056004:Molecular Dynamics Simulation; D011489:Protein Denaturation; D011506:Proteins / Q000737:chemistry*; D011789:Quantum Theory; D012984:Software; D013816:Thermodynamics; D014867:Water / Q000737:chemistry
chemical_list: D011506:Proteins; D014867:Water