z-logo
Premium
Comparing pairwise‐additive and many‐body generalized Born models for acid/base calculations and protein design
Author(s) -
Villa Francesco,
Mig David,
Polydorides Savvas,
Simonson Thomas
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.24898
Subject(s) - pairwise comparison , protein design , solvent , monte carlo method , chemistry , computational chemistry , boundary (topology) , statistical physics , materials science , computer science , mathematics , protein structure , physics , mathematical analysis , organic chemistry , biochemistry , statistics , artificial intelligence
Generalized Born (GB) solvent models are common in acid/base calculations and protein design. With GB, the interaction between a pair of solute atoms depends on the shape of the protein/solvent boundary and, therefore, the positions of all solute atoms, so that GB is a many‐body potential. For compute‐intensive applications, the model is often simplified further, by introducing a mean, native‐like protein/solvent boundary, which removes the many‐body property. We investigate a method for both acid/base calculations and protein design that uses Monte Carlo simulations in which side chains can explore rotamers, bind/release protons, or mutate. The fluctuating protein/solvent dielectric boundary is treated in a way that is numerically exact (within the GB framework), in contrast to a mean boundary. Its originality is that it captures the many‐body character while retaining the residue‐pairwise complexity given by a fixed boundary. The method is implemented in the Proteus protein design software. It yields a slight but systematic improvement for acid/base constants in nine proteins and a significant improvement for the computational design of three PDZ domains. It eliminates a source of model uncertainty, which will facilitate the analysis of other model limitations. © 2017 Wiley Periodicals, Inc.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom