A Data Management System for Pre-docking in Large-Scale Virtual Screening

Jiuqiang Chen, Ruisheng Zhang, Shilin Chen, Lian Li, Y. Zhang, Chengda Yuan, Lifen Li
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引用次数: 4

Abstract

Virtual screening is a new approach attracting increasing levels of interest in the pharmaceutical industry, as a productive and cost-effective technology in the search for novel lead compounds. The preparation of millions of small molecular compounds is the prerequisite for large-scale virtual screening, and these massive data are usually provided with different format. In addition, scientists often need to select some of them that meet certain conditions. Therefore, an efficient data management approach is playing an important role in virtual screening process for managing large-scale small molecular compounds. In this paper, we represent a comprehensive data management framework for pre-docking in large-scale virtual screening. In this framework, we construct a distributed chemical database and utilize parallel processing approach to search certain molecules from the database on the scale of at least several million. We also develop a proxy schema, which is responsible to perform the basic function (such as, splitting large-scale data, update, insert and so on) a collection of multiple, logically interrelated databases distributed over a computer network, meanwhile, we design and establish a rule of splitting large-scale data with optimization. Finally, we simulate and demonstrate a stress test of constructing and searching database. It turns out that our proposal could make the preparing phase of virtual screening process more simple and efficient.
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大型虚拟筛选预对接数据管理系统
虚拟筛选是一种新的方法,吸引了越来越多的制药行业的兴趣,作为一种高效和具有成本效益的技术,在寻找新的先导化合物。数以百万计的小分子化合物的制备是进行大规模虚拟筛选的前提,而这些海量数据通常以不同的格式提供。此外,科学家经常需要从中选择一些符合特定条件的细胞。因此,一种高效的数据管理方法在虚拟筛选过程中对管理大尺度小分子化合物起着重要的作用。本文提出了一种面向大规模虚拟筛选预对接的综合数据管理框架。在这个框架中,我们构建了一个分布式的化学数据库,并利用并行处理的方法从数据库中搜索至少几百万个规模的特定分子。我们还开发了一个代理模式,该模式负责对分布在计算机网络上的多个逻辑上相互关联的数据库集合执行基本功能(如大规模数据分割、更新、插入等),同时我们设计并建立了一个优化的大规模数据分割规则。最后,模拟并演示了数据库构建与检索的压力测试。结果表明,我们的建议可以使虚拟筛选过程的准备阶段更加简单和高效。
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