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Variational Optimization of an All-Atom Implicit Solvent Force Field To Match Explicit Solvent Simulation Data

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journal contribution
posted on 10.12.2013, 00:00 by Sandro Bottaro, Kresten Lindorff-Larsen, Robert B. Best
The development of accurate implicit solvation models with low computational cost is essential for addressing many large-scale biophysical problems. Here, we present an efficient solvation term based on a Gaussian solvent-exclusion model (EEF1) for simulations of proteins in aqueous environment, with the primary aim of having a good overlap with explicit solvent simulations, particularly for unfolded and disordered states – as would be needed for multiscale applications. In order to achieve this, we have used a recently proposed coarse-graining procedure based on minimization of an entropy-related objective function to train the model to reproduce the equilibrium distribution obtained from explicit water simulations. Via this methodology, we have optimized both a charge screening parameter and a backbone torsion term against explicit solvent simulations of an α-helical and a β-stranded peptide. The performance of the resulting effective energy function, termed EEF1-SB, is tested with respect to the properties of folded proteins, the folding of small peptides or fast-folding proteins, and NMR data for intrinsically disordered proteins. The results show that EEF1-SB provides a reasonable description of a wide range of systems, but its key advantage over other methods tested is that it captures very well the structure and dimensions of disordered or weakly structured peptides. EEF1-SB is thus a computationally inexpensive (∼10 times faster than Generalized-Born methods) and transferable approximation for treating solvent effects.