Anisotropic Coarse-Grained Model for Proteins Based On Gay–Berne and Electric Multipole Potentials
Author(s) -
Hujun Shen,
Yan Li,
Pengyu Ren,
Dinglin Zhang,
Guohui Li
Publication year - 2014
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/ct400974z
Subject(s) - multipole expansion , dipole , electrostatics , anisotropy , force field (fiction) , electric field , statistical physics , molecular dynamics , moment (physics) , physics , intermolecular force , chemical physics , chemistry , classical mechanics , computational chemistry , molecule , quantum mechanics
Gay-Berne anisotropic potential has been widely used to evaluate the non-bonded interactions between coarse-grained particles being described as elliptical rigid bodies. In this paper, we are presenting a coarse-grained model for twenty kinds of amino acids and proteins, based on the anisotropic Gay-Berne and point electric multipole (EMP) potentials. We demonstrate that the anisotropic coarse-grained model, namely GBEMP model, is able to reproduce many key features observed from experimental protein structures (Dunbrack Library) as well as from atomistic force field simulations (using AMOEBA, AMBER and CHARMM force fields) while saving the computational cost by a factor of about 10~200 depending on specific cases and atomistic models. More importantly, unlike other coarse-grained approaches, our framework is based on the fundamental intermolecular forces with explicit treatment of electrostatic and repulsion-dispersion forces. As a result, the coarse-grained protein model presented an accurate description of non-bonded interactions (particularly electrostatic component) between hetero-/homo-dimers (such as peptide-peptide, peptide-water). In addition, the encouraging performance of the model was reflected by the excellent correlation between GBEMP and AMOEBA models in the calculations of the dipole moment of peptides. In brief, the GBEMP model given here is general and transferable, suitable for simulating complex biomolecular systems.
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