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Building a More Predictive Protein Force Field: A Systematic and Reproducible Route to AMBER-FB15
Journal article   Open access   Peer reviewed

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

Lee-Ping Wang, Keri A McKiernan, Joseph Gomes, Kyle A Beauchamp, Teresa Head-Gordon, Julia E Rice, William C Swope, Todd J Martínez and Vijay S Pande
The journal of physical chemistry. B, Vol.121(16), pp.4023-4039
04/27/2017
DOI: 10.1021/acs.jpcb.7b02320
PMID: 28306259
url
https://www.ncbi.nlm.nih.gov/pmc/articles/9724927View
Open Access

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.
Software Thermodynamics Databases, Protein Molecular Dynamics Simulation Protein Denaturation Proteins - chemistry Quantum Theory Water - chemistry

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