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.

中文翻译：

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使用图形处理单元加速具有分子体积和溶剂可及表面积的隐式溶剂模型的广义出生

具有分子体积和溶剂可及表面积 (GBMV2/SA) 隐式溶剂模型的广义 Born 提供了对分子体积的准确描述，并有可能准确描述结构化和无序蛋白质的构象平衡。然而，其更广泛的应用受到并行计算计算成本和扩展性差的限制。在这里，我们报告了 GBMV2/SA 静电和非极性组件在 CHARMM/OpenMM 模块内的图形处理单元 (GPU) 上的有效实现。GPU-GBMV2/SA 在数值上等同于原始 CPU-GBMV2/SA。GPU 加速在单个 NVIDIA TITAN X (Pascal) 显卡上提供约 60 到 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。当前的实现可以进一步优化，以实现更大的加速度，同时对数值精度的降低最小。GPU-GBMV2/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。© 2019 威利期刊公司。