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Accelerating the Generalized Born with Molecular Volume and Solvent Accessible Surface Area Implicit Solvent Model Using Graphics Processing Units
Author(s) -
Gong Xiping,
Chiricotto Mara,
Liu Xiaorong,
Nordquist Erik,
Feig Michael,
Brooks Charles L.,
Chen Jianhan
Publication year - 2020
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.26133
Subject(s) - cuda , accessible surface area , computer science , graphics , computational science , graphics processing unit , speedup , general purpose computing on graphics processing units , titan (rocket family) , volume (thermodynamics) , pascal (unit) , scaling , molecular dynamics , solvent , computer graphics , molecular graphics , chemistry , parallel computing , computer graphics (images) , computational chemistry , thermodynamics , physics , organic chemistry , mathematics , geometry , astronomy , programming language
The generalized Born with molecular volume and solvent accessible surface area (GBMV2/SA) implicit solvent model provides an accurate description of molecular volume and has the potential to accurately describe the conformational equilibria of structured and disordered proteins. However, its broader application has been limited by the computational cost and poor scaling in parallel computing. Here, we report an efficient implementation of both the electrostatic and nonpolar components of GBMV2/SA on graphics processing unit (GPU) within the CHARMM/OpenMM module. The GPU‐GBMV2/SA is numerically equivalent to the original CPU‐GBMV2/SA. The GPU acceleration offers ~60‐ to 70‐fold speedup on a single NVIDIA TITAN X (Pascal) graphics card for molecular dynamic simulations of both folded and unstructured proteins of various sizes. The current implementation can be further optimized to achieve even greater acceleration with minimal reduction on the numerical accuracy. The successful development of GPU‐GBMV2/SA greatly facilitates its application to biomolecular simulations and paves the way for further development of the implicit solvent methodology. © 2019 Wiley Periodicals, Inc.