title: Optimization of the GBMV2 implicit solvent force field for accurate simulation of protein conformational equilibria.
abstract: Accurate treatment of solvent environment is critical for reliable simulations of protein conformational equilibria. Implicit treatment of solvation, such as using the generalized Born (GB) class of models arguably provides an optimal balance between computational efficiency and physical accuracy. Yet, GB models are frequently plagued by a tendency to generate overly compact structures. The physical origins of this drawback are relatively well understood, and the key to a balanced implicit solvent protein force field is careful optimization of physical parameters to achieve a sufficient level of cancellation of errors. The latter has been hampered by the difficulty of generating converged conformational ensembles of non-trivial model proteins using the popular replica exchange sampling technique. Here, we leverage improved sampling efficiency of a newly developed multi-scale enhanced sampling technique to re-optimize the generalized-Born with molecular volume (GBMV2) implicit solvent model with the CHARMM36 protein force field. Recursive optimization of key GBMV2 parameters (such as input radii) and protein torsion profiles (via the CMAP torsion cross terms) has led to a more balanced GBMV2 protein force field that recapitulates the structures and stabilities of both helical and β-hairpin model peptides. Importantly, this force field appears to be free of the over-compaction bias, and can generate structural ensembles of several intrinsically disordered proteins of various lengths that seem highly consistent with available experimental data. © 2017 Wiley Periodicals, Inc.
authors.affiliation: Department of Biochemistry and Molecular Biophysics, Kansas State University, Manhattan, Kansas, 66506.
authors.forename: Kuo Hao
authors.initials: KH
authors.lastname: Lee
authors.affiliation: Department of Biochemistry and Molecular Biophysics, Kansas State University, Manhattan, Kansas, 66506.
authors.forename: Jianhan
authors.identifier: 0000-0002-5281-1150
authors.initials: J
authors.lastname: Chen
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry; D003198:Computer Simulation; D008958:Models, Molecular; D010455:Peptides / Q000737:chemistry*; D055585:Physical Phenomena; D017510:Protein Folding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D012997:Solvents / Q000737:chemistry*; D013816:Thermodynamics
chemical_list: D000596:Amino Acids; D010455:Peptides; D011506:Proteins; D012997:Solvents
keywords: continuum electrostatics; enhanced sampling; generalized Born; intrinsically disordered proteins; nonpolar solvation; protein folding