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大规模云端对接。

Large-Scale Docking in the Cloud.

机构信息

Department of Pharmaceutical Chemistry, University of California San Francisco, 1700 4th Street, MC 2550, San Francisco, California 94158-2330, United States.

出版信息

J Chem Inf Model. 2023 May 8;63(9):2735-2741. doi: 10.1021/acs.jcim.3c00031. Epub 2023 Apr 18.

Abstract

Molecular docking is a pragmatic approach to exploit protein structures for new ligand discovery, but the growing size of available chemical space is increasingly challenging to screen on in-house computer clusters. We have therefore developed AWS-DOCK, a protocol for running UCSF DOCK in the AWS cloud. Our approach leverages the low cost and scalability of cloud resources combined with a low-molecule-cost docking engine to screen billions of molecules efficiently. We benchmarked our system by screening 50 million HAC 22 molecules against the DRD4 receptor with an average CPU time of around 1 s per molecule. We saw up to 3-fold variations in cost between AWS availability zones. Docking 4.5 billion lead-like molecules, a 7 week calculation on our 1000-core lab cluster, runs in about a week depending on accessible CPUs, in AWS for around $25,000, less than the cost of two new nodes. The cloud docking protocol is described in easy-to-follow steps and may be sufficiently general to be used for other docking programs. All the tools to enable AWS-DOCK are available free to everyone, while DOCK 3.8 is free for academic research.

摘要

分子对接是一种实用的方法,可以利用蛋白质结构来发现新的配体,但可用化学空间的不断增大,使得在内部计算机集群上进行筛选变得越来越具有挑战性。因此,我们开发了 AWS-DOCK,这是一种在 AWS 云中运行 UCSF DOCK 的协议。我们的方法利用了云资源的低成本和可扩展性,以及低成本的对接引擎,以有效地筛选数十亿个分子。我们通过用 DRD4 受体对 5000 万个 HAC 22 分子进行筛选来对我们的系统进行基准测试,每个分子的平均 CPU 时间约为 1 秒。我们看到 AWS 可用区之间的成本差异高达 3 倍。在我们的 1000 核实验室集群上计算 45 亿个类似先导的分子需要 7 周的时间,而在 AWS 中根据可用的 CPU 计算,大约需要一周的时间,费用约为 25000 美元,不到两个新节点的成本。云对接协议的步骤简单易懂,可能足够通用,可以用于其他对接程序。AWS-DOCK 所需的所有工具都可供所有人免费使用,而 DOCK 3.8 则可免费用于学术研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e14e/10170500/211befabe63c/ci3c00031_0002.jpg

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