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A rapid solvent accessible surface area estimator for coarse grained molecular simulations
Author(s) -
Wei Shuai,
Brooks Charles L.,
Frank Aaron T.
Publication year - 2017
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.24709
Subject(s) - sasa , accessible surface area , solvent models , solvation , estimator , computer science , molecular dynamics , protein folding , solvent , biological system , biomolecule , chemistry , computational science , computational chemistry , mathematics , paleontology , biochemistry , statistics , organic chemistry , biology
The rapid and accurate calculation of solvent accessible surface area (SASA) is extremely useful in the energetic analysis of biomolecules. For example, SASA models can be used to estimate the transfer free energy associated with biophysical processes, and when combined with coarse-grained simulations, can be particularly useful for accounting for solvation effects within the framework of implicit solvent models. In such cases, a fast and accurate, residue-wise SASA predictor is highly desirable. Here, we develop a predictive model that estimates SASAs based on Cα-only protein structures. Through an extensive comparison between this method and a comparable method, POPS-R, we demonstrate that our new method, Protein-C α Solvent Accessibilities or PCASA, shows better performance, especially for unfolded conformations of proteins. We anticipate that this model will be quite useful in the efficient inclusion of SASA-based solvent free energy estimations in coarse-grained protein folding simulations. PCASA is made freely available to the academic community at https://github.com/atfrank/PCASA. © 2017 Wiley Periodicals, Inc.