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现代药物发现中的分布式计算进展。

Advances in distributed computing with modern drug discovery.

机构信息

a Bioinformatics and High Performance Computing Research Group (BIO-HPC) , Universidad Católica de Murcia (UCAM) , Murcia , Spain.

b Center for Research Computing , University of Notre Dame , Notre Dame , IN , USA.

出版信息

Expert Opin Drug Discov. 2019 Jan;14(1):9-22. doi: 10.1080/17460441.2019.1552936. Epub 2018 Dec 13.

DOI:10.1080/17460441.2019.1552936
PMID:30484337
Abstract

Computational chemistry dramatically accelerates the drug discovery process and high-performance computing (HPC) can be used to speed up the most expensive calculations. Supporting a local HPC infrastructure is both costly and time-consuming, and, therefore, many research groups are moving from in-house solutions to remote-distributed computing platforms. Areas covered: The authors focus on the use of distributed technologies, solutions, and infrastructures to gain access to HPC capabilities, software tools, and datasets to run the complex simulations required in computational drug discovery (CDD). Expert opinion: The use of computational tools can decrease the time to market of new drugs. HPC has a crucial role in handling the complex algorithms and large volumes of data required to achieve specificity and avoid undesirable side-effects. Distributed computing environments have clear advantages over in-house solutions in terms of cost and sustainability. The use of infrastructures relying on virtualization reduces set-up costs. Distributed computing resources can be difficult to access, although web-based solutions are becoming increasingly available. There is a trade-off between cost-effectiveness and accessibility in using on-demand computing resources rather than free/academic resources. Graphics processing unit computing, with its outstanding parallel computing power, is becoming increasingly important.

摘要

计算化学极大地加速了药物发现过程,而高性能计算 (HPC) 可用于加速最昂贵的计算。支持本地 HPC 基础架构既昂贵又耗时,因此,许多研究小组正在从内部解决方案转向远程分布式计算平台。涵盖领域:作者专注于使用分布式技术、解决方案和基础架构来访问 HPC 功能、软件工具和数据集,以运行计算药物发现 (CDD) 所需的复杂模拟。专家意见:使用计算工具可以缩短新药上市的时间。HPC 在处理处理复杂算法和大量数据方面发挥着至关重要的作用,这些数据是实现特异性和避免不良副作用所必需的。分布式计算环境在成本和可持续性方面具有明显优于内部解决方案的优势。依靠虚拟化的基础设施的使用可以降低设置成本。尽管基于网络的解决方案越来越多,但分布式计算资源的访问可能会很困难。在使用按需计算资源而不是免费/学术资源时,需要在成本效益和可访问性之间进行权衡。具有出色并行计算能力的图形处理单元计算正变得越来越重要。

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