Fast and accurate calculation of solvation free energies is central to many applications, such as rational drug design. In this study, we present a grid-based molecular surface implementation of an "R6" flavor of the generalized Born (GB) implicit solvent model, named GBNSR6. The speed, accuracy and sensitivity to grid surface parameters are tested on a set of 15 small protein-ligand complexes, and a set of biomolecules in the range of 268 to 25099 atoms. Our results demonstrate that the proposed model provides a relatively successful compromise between the speed and accuracy of computing polar components of the solvation free energies (△Gpol ) , and binding free energies (△△Gpol). The model tolerates a relatively coarse grid size h = 0.5 Å where the grid artifact error in computing △△Gpol remains in the range of kBT ∼ 0.6. The estimated △△Gpol are well correlated (r2 =0.97) with the numerical Poisson-Boltzmann reference, while showing virtually no systematic bias and RMSE=1.43 kcal/mol. The grid-based GBNSR6 model is available in AMBER (AmberTools) package of molecular simulation programs. Implications for fast estimates of protein-ligand binding energies are discussed.

Grid-based molecular surface generalized Born (GB) model for single-point calculations of electrostatic solvation free energies

254th National Meeting (2017)

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