摘要
计算机辅助设计是现代药物发现的重要组成部分之一。通过使用计算方法,以提高命中识别和导联选择,提高生物利用度,并减少毒性,药物开发变得相对简便。在过去十年中积累的基因组知识的一个安装机构,为药物研究提供了巨大的机会。过去十年,基因组知识的发展为药物研究提供了巨大的机会,然而,新的挑战也出现了,因为处理这个大容量的数据需求前所未有的计算资源。另一方面,先进的异构系统提供每秒千万亿次的峰值以加速科学发现。本文回顾现代并行加速器架构,主要聚焦于英特尔Xeon Phi多核心设备。Xeon Phi是一个相对较新的平台,具有数百个计算核心和数以百计的线程。我们还讨论了针对这个加速器的常见的并行编程框架,包括MPI和OpenMP,OpenCL,HPX等。在代码开发在许多核心设备应用的最新研究进展说证明了与传统的串行计算相比异构实现的优点。本文强调选择的算法,efindsite、配体结合位点预测,用于生物分子模拟的力场和BUDE,以及基于结构的虚拟筛选机,并以此证明配备并行计算设备的异构系统可以加速药物发现的进程。
关键词: BUDE,药物的发现,efindsite,并行加速器,编程框架,Xeon Phi。
图形摘要
Current Drug Targets
Title:Structure-Based Drug Discovery Accelerated by Many-Core Devices
Volume: 17 Issue: 14
Author(s): Wei Feinstein and Michal Brylinski
Affiliation:
关键词: BUDE,药物的发现,efindsite,并行加速器,编程框架,Xeon Phi。
摘要: Computer-aided design is one of the critical components of modern drug discovery. Drug development is routinely streamlined using computational approaches to improve hit identification and lead selection, enhance bioavailability, and reduce toxicity. A mounting body of genomic knowledge accumulated during the last decade or so presents great opportunities for pharmaceutical research. However, new challenges also arose because processing this large volume of data demands unprecedented computing resources. On the other hand, the state-of-the-art heterogeneous systems deliver petaflops of peak performance to accelerate scientific discovery. In this communication, we review modern parallel accelerator architectures, mainly focusing on Intel Xeon Phi many-core devices. Xeon Phi is a relatively new platform that features tens of computing cores with hundreds of threads offering massively parallel capabilities for a broad range of application. We also discuss common parallel programming frameworks targeted to this accelerator, including OpenMP, OpenCL, MPI and HPX. Recent advances in code development for many-core devices are described to demonstrate the advantages of heterogeneous implementations over the traditional, serial computing. Finally, we highlight selected algorithms, eFindSite, a ligand binding site predictor, a force field for bio-molecular simulations, and BUDE, a structure-based virtual screening engine, to demonstrate how modern drug discovery is accelerated by heterogeneous systems equipped with parallel computing devices.
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Cite this article as:
Wei Feinstein and Michal Brylinski , Structure-Based Drug Discovery Accelerated by Many-Core Devices, Current Drug Targets 2016; 17 (14) . https://dx.doi.org/10.2174/1389450117666160112112854
DOI https://dx.doi.org/10.2174/1389450117666160112112854 |
Print ISSN 1389-4501 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-5592 |
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