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一种基于试剂的大型组合文库设计策略:初步实验验证

A reagent-based strategy for the design of large combinatorial libraries: a preliminary experimental validation.

作者信息

Makara Gergely M, Nash Huw, Zheng Zhongli, Orminati Jean-Paul A, Wintner Edward A

机构信息

NeoGenesis Pharmaceuticals Inc., Cambridge, Massachusetts, USA.

出版信息

Mol Divers. 2003;7(1):3-14. doi: 10.1023/b:modi.0000006537.06541.8a.

Abstract

Combinatorial library design can be carried out at either the reagent or the product level. Various reports in the literature have come to conflicting conclusions in favor of one over the other. In this paper a reagent-based screening library design strategy is presented. The method relies on analysis of scaffolds and building blocks separately to define the overall diversity in a compound file. The primary diversity selection by properties relevant for molecular recognition and by redundancy is followed by the application of filters for molecular properties known to be relevant for drug-likeness. Filter properties are rapidly estimated at the product level using a fragmental estimation approach. Initial experimental data suggest that high diversity in vast screening libraries can be achieved by carefully applied reagent level analysis. A potential role of diverse screening libraries in chemical genomics (pharmacological knockouts) is also discussed.

摘要

组合文库设计可以在试剂或产物层面进行。文献中的各种报告得出了相互矛盾的结论,支持其中一方优于另一方。本文提出了一种基于试剂的筛选文库设计策略。该方法依赖于分别分析支架和构建模块来定义化合物文件中的整体多样性。首先根据与分子识别相关的性质和冗余性进行主要的多样性选择,然后应用已知与类药性相关的分子性质过滤器。使用片段估计方法在产物层面快速估计过滤器性质。初步实验数据表明,通过仔细应用试剂层面分析可以在大量筛选文库中实现高度多样性。还讨论了多样筛选文库在化学基因组学(药理学基因敲除)中的潜在作用。

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