Accelerating the Generalized Born with Molecular Volume and Solvent Accessible Surface Area Implicit Solvent Model Using Graphics Processing Units
Accelerating the Generalized Born with Molecular Volume and Solvent Accessible Surface Area Implicit Solvent Model Using Graphics Processing Units
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DOI：
10.1002/jcc.26133
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发表时间：
2019-12-24
影响因子：
3
通讯作者：
Chen, Jianhan
中科院分区：
文献类型：
--
作者：
Gong, Xiping;Chiricotto, Mara;Chen, Jianhan
广义Born分子体积和溶剂可及表面积（GBMV 2/SA）隐式溶剂模型提供了对分子体积的精确描述，并具有精确描述结构和无序蛋白质构象平衡的潜力。然而，其更广泛的应用受到并行计算的计算成本和可扩展性差的限制。在这里，我们报告的静电和非极性组件的GBMV 2/SA的图形处理单元（GPU）的CHARMM/OpenMM模块内的有效实施。GPU-GBMV 2/SA在数值上等同于原始CPU-GBMV 2/SA。GPU加速功能可在一块NVIDIA TITAN X（Pascal）显卡上提供60至70倍的加速，用于各种大小的折叠和非结构化蛋白质的分子动力学模拟。可以进一步优化当前的实现方式，以在最小的数值精度降低的情况下实现更大的加速。GPU-GBMV 2/SA的成功开发极大地促进了其在生物分子模拟中的应用，并为隐式溶剂方法的进一步发展铺平了道路。(c)2019 Wiley Periodicals，Inc.
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. (c) 2019 Wiley Periodicals, Inc.