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Comparison of implicit solvent models for the simulation of protein–surface interactions
Author(s) -
Sun Yu,
Latour Robert A.
Publication year - 2006
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.20488
Subject(s) - solvation , force field (fiction) , implicit solvation , molecular dynamics , solvent models , density functional theory , surface (topology) , materials science , computational chemistry , statistical physics , field (mathematics) , thermodynamics , chemical physics , computer science , molecule , chemistry , physics , mathematics , organic chemistry , geometry , artificial intelligence , pure mathematics
Empirical force field‐based molecular simulations can provide valuable atomistic‐level insights into protein–surface interactions in aqueous solution. While the implicit treatment of solvation effects is desired as a means of improving simulation efficiency, existing implicit solvent models were primarily developed for the simulation of peptide or protein behavior in solution alone, and thus may not be appropriate for protein interactions with synthetic material surfaces. The objective of this research was to calculate the change in free energy as a function of surface–separation distance for peptide–surface interactions using different empirical force field‐based implicit solvation models (ACE, ASP, EEF1, and RDIE with the CHARMM 19 force field), and to compare these results with the same calculations conducted using density functional theory (DFT) combined with the self‐consistent reaction field (SCRF) implicit solvation model. These comparisons show that distinctly different types of behavior are predicted with each implicit solvation method, with ACE providing the best overall agreement with DFT/SCRF calculations. These results also identify areas where ACE is in need of improvement for this application and provide a basis for subsequent parameter refinement. © 2006 Wiley Periodicals, Inc. J Comput Chem, 2006