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化学文库的可视化特征描述和多样性量化:1. 限定参考化学子空间的创建。

Visual characterization and diversity quantification of chemical libraries: 1. creation of delimited reference chemical subspaces.

机构信息

Institut de Chimie Organique et Analytique (ICOA), Université d'Orléans, rue de Chartres, 45067 Orléans Cedex 2, France.

出版信息

J Chem Inf Model. 2011 Aug 22;51(8):1762-74. doi: 10.1021/ci200051r. Epub 2011 Aug 3.

DOI:10.1021/ci200051r
PMID:21761916
Abstract

High-throughput screening (HTS) is a well-established technology which can test up to several million compounds in a few weeks. Despite these appealing capabilities, available resources and high costs may limit the number of molecules screened, making diversity analysis a method of choice to design and prioritize screening libraries. With a constantly increasing number of molecules available for screening, chemical space has become a key concept for visualizing, analyzing, and comparing chemical libraries. In this first article, we present a new method to build delimited reference chemical subspaces (DRCS). A set of 16 million screening compounds from 73 chemical providers has been gathered, resulting in a database of 6.63 million standardized and unique molecules. These molecules have been used to create three DRCS using three different sets of chemical descriptors. A robust principal component analysis model for each space has been obtained, whereby molecules are projected in a reduced two-dimensional viewable space. The specificity of our approach is that each reduced space has been delimited by a representative contour encompassing a very large proportion of molecules and reflecting its overall shape. The methodology is illustrated by mapping and comparing various chemical libraries. Several tools used in these studies are made freely available, thus enabling any user to compute DRCS matching specific requirements.

摘要

高通量筛选 (HTS) 是一种成熟的技术,可以在短短几周内测试多达数百万种化合物。尽管具有这些吸引人的能力,但可用资源和高成本可能会限制筛选的分子数量,这使得多样性分析成为设计和优先筛选库的首选方法。随着可用于筛选的分子数量不断增加,化学空间已成为可视化、分析和比较化学库的关键概念。在第一篇文章中,我们提出了一种构建有界参考化学子空间 (DRCS) 的新方法。从 73 家化学供应商中收集了 1600 万种筛选化合物,从而创建了一个包含 663 万个标准化和独特分子的数据库。这些分子已被用于使用三种不同的化学描述符集创建三个 DRCS。已经为每个空间获得了一个稳健的主成分分析模型,其中分子被投影到一个可视图的二维降维空间中。我们方法的独特之处在于,每个降维空间都通过一个代表性的轮廓限定,该轮廓包含很大比例的分子并反映其整体形状。通过绘制和比较各种化学库来说明该方法。这些研究中使用的几个工具是免费提供的,因此任何用户都可以计算出符合特定要求的 DRCS。

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