| Literature DB >> 33497567 |
Mengran Fan1, Jian Wang2, Huaipan Jiang1, Yilin Feng1, Mehrdad Mahdavi1, Kamesh Madduri1, Mahmut T Kandemir1, Nikolay V Dokholyan2,3,4,5.
Abstract
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.Mesh:
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Year: 2021 PMID: 33497567 DOI: 10.1021/acs.jpcb.0c09051
Source DB: PubMed Journal: J Phys Chem B ISSN: 1520-5207 Impact factor: 2.991