Cao Xin, Hummel Michelle H, Wang Yuzhang, Simmerling Carlos, Coutsias Evangelos A
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, United States.
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States.
J Chem Theory Comput. 2024 Jun 11;20(11):4456-4468. doi: 10.1021/acs.jctc.3c01366. Epub 2024 May 23.
In this paper, we present differentiable solvent-accessible surface area (dSASA), an exact geometric method to calculate SASA analytically along with atomic derivatives on GPUs. The atoms in a molecule are first assigned to tetrahedra in groups of four atoms by Delaunay tetrahedralization adapted for efficient GPU implementation, and the SASA values for atoms and molecules are calculated based on the tetrahedralization information and inclusion-exclusion method. The SASA values from the numerical icosahedral-based method can be reproduced with >98% accuracy for both proteins and RNAs. Having been implemented on GPUs and incorporated into AMBER, we can apply dSASA to implicit solvent molecular dynamics simulations with the inclusion of this nonpolar term. The current GPU version of GB/SA simulations has been accelerated up to nearly 20-fold compared to the CPU version, outperforming LCPO, a commonly used, fast algorithm for calculating SASA, as the system size increases. While we focus on the accuracy of the SASA calculations for proteins and nucleic acids, we also demonstrate stable GB/SA MD mini-protein simulations.
在本文中,我们提出了可微溶剂可及表面积(dSASA),这是一种精确的几何方法,可在GPU上解析计算溶剂可及表面积(SASA)以及原子导数。通过适用于高效GPU实现的德劳内四面体剖分,首先将分子中的原子按四个原子一组分配到四面体中,然后根据四面体剖分信息和容斥法计算原子和分子的SASA值。基于二十面体的数值方法得到的SASA值,对于蛋白质和RNA,其重现精度均可超过98%。dSASA已在GPU上实现并整合到AMBER中,我们可以将其应用于包含该非极性项的隐式溶剂分子动力学模拟。与CPU版本相比,当前GB/SA模拟的GPU版本加速了近20倍,随着系统规模的增加,其性能优于常用的快速SASA计算算法LCPO。虽然我们专注于蛋白质和核酸SASA计算的准确性,但我们也展示了稳定的GB/SA MD小蛋白模拟。