文献类型：期刊文献

英文题名：Molecular Docking for Ligand-Receptor Binding Process Based on Heterogeneous Computing

作者：Li, Jianhua[1];Liu, Guanlong[1];Zhen, Zhiyuan[1];Shen, Zihao[2];Li, Shiliang[2];Li, Honglin[2]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Shanghai Key Lab New Drug Design, Sch Pharm, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China

年份：2022

卷号：2022

外文期刊名：SCIENTIFIC PROGRAMMING

收录：;EI(收录号：20220511571467);WOS:【SCI-EXPANDED(收录号:WOS:000766923500004)】；

基金：AcknowledgmentsThis work was supported by the Fundamental Research Funds for National Key R&D Program of China (under grant no. 2016YFA0502304) and the Important Drug Development Fund, the Ministry of Science and Technology of China (under grant no. 2018ZX09735002).

语种：英文

外文关键词：Chelation - Ligands - Molecular modeling - Computer graphics - Multicore programming - Parallel processing systems - Program processors - Parallel programming - Memory architecture - Computer graphics equipment - Message passing

摘要：Molecular docking aims to predict possible drug candidates for many diseases, and it is computationally intensive. Particularly, in simulating the ligand-receptor binding process, the binding pocket of the receptor is divided into subcubes, and when the ligand is docked into all cubes, there are many molecular docking tasks, which are extremely time-consuming. In this study, we propose a heterogeneous parallel scheme of molecular docking for the binding process of ligand to receptor to accelerate simulating. The parallel scheme includes two layers of parallelism, a coarse-grained layer of parallelism implemented in the message-passing interface (MPI) and a fine-grained layer of parallelism focused on the graphics processing unit (GPU). At the coarse-grain layer of parallelism, a docking task inside one lattice is assigned to one unique MPI process, and a grouped master-slave mode is used to allocate and schedule the tasks. Meanwhile, at the fine-gained layer of parallelism, GPU accelerators undertake the computationally intensive computing of scoring functions and related conformation spatial transformations in a single docking task. The results of the experiments for the ligand-receptor binding process show that on a multicore server with GPUs the parallel program has achieved a speedup ratio as high as 45 times in flexible docking and as high as 54.5 times in semiflexible docking, and on a distributed memory system, the docking time for flexible docking and that for semiflexible docking gradually decrease as the number of nodes used in the parallel program gradually increases. The scalability of the parallel program is also verified in multiple nodes on a distributed memory system and is approximately linear.