Cao Xin, Hummel Michelle H, Wang Yuzhang, Simmerling Carlos, Coutsias Evangelos A
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, United States.
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, United States.
ArXiv. 2024 Apr 25:arXiv:2401.10462v2.
In this paper, we present dSASA (differentiable SASA), an exact geometric method to calculate solvent accessible surface area (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 tetrahedrization adapted for efficient GPU implementation and the SASA values for atoms and molecules are calculated based on the tetrahedrization information and inclusion-exclusion method. The SASA values from the numerical icosahedral-based method can be reproduced with more than 98% accuracy for both proteins and RNAs. Having been implemented on GPUs and incorporated into the software Amber, we can apply dSASA to implicit solvent molecular dynamics simulations with 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，可在图形处理器（GPU）上解析计算溶剂可及表面积（SASA）及其原子导数。分子中的原子首先通过适用于高效GPU实现的德劳内四面体剖分法以四个原子为一组分配到四面体中，然后基于四面体剖分信息和容斥法计算原子和分子的SASA值。对于蛋白质和RNA，基于数值二十面体法的SASA值能够以超过98%的准确率重现。dSASA已在GPU上实现并集成到Amber软件中，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小蛋白质模拟。
