GPU-Accelerated Flexible Molecular Docking.

GPU-Accelerated Flexible Molecular Docking.
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GPU加速的柔性分子对接。

DOI:
10.1021/acs.jpcb.0c09051
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发表时间:
2021-02-04
影响因子:
3.3
通讯作者:
Dokholyan, Nikolay, V
Dokholyan, Nikolay, V
中科院分区:
化学3区
文献类型:
--
作者:
Fan, Mengran;Wang, Jian;Jiang, Huaipan;Feng, Yilin;Mahdavi, Mehrdad;Madduri, Kamesh;Kandemir, Mahmut T.;Dokholyan, Nikolay, V

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虚拟筛选是计算药物发现的关键推动因素,需要准确有效的基于结构的分子对接。在这项工作中,我们开发了分子对接的算法和软件构建模块,可以利用图形处理单元(GPU)。具体来说,我们专注于MedusaDock,一种灵活的蛋白质-小分子对接方法和平台。我们加快了MedusaDock的粗对接阶段的性能,因为在典型用例中,这一步占总运行时间的近70%。我们使用3875个蛋白质-配体复合物的数据集对单GPU和多GPU加速的质量和性能进行了全面评估。算法思想、数据结构设计选择和性能优化技术为其他基于结构的分子对接软件工具的GPU加速提供了启示。
Virtual screening is a key enabler of computational drug discovery and requires accurate and efficient structure-based molecular docking. In this work, we develop algorithms and software building blocks for molecular docking that can take advantage of graphics processing units (GPUs). Specifically, we focus on MedusaDock, a flexible protein-small molecule docking approach and platform. We accelerate the performance of the coarse docking phase of MedusaDock, as this step constitutes nearly 70% of total running time in typical use-cases. We perform a comprehensive evaluation of the quality and performance with single-GPU and multi-GPU acceleration using a data set of 3875 protein–ligand complexes. The algorithmic ideas, data structure design choices, and performance optimization techniques shed light on GPU acceleration of other structure-based molecular docking software tools.
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发表时间: 1995-01-06
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