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用于针对蛋白质靶点进行核磁共振筛选的分子片段文库的设计与表征。

Design and characterization of libraries of molecular fragments for use in NMR screening against protein targets.

作者信息

Baurin Nicolas, Aboul-Ela Fareed, Barril Xavier, Davis Ben, Drysdale Martin, Dymock Brian, Finch Harry, Fromont Christophe, Richardson Christine, Simmonite Heather, Hubbard Roderick E

机构信息

Vernalis (R&D) Ltd., Granta Park, Abington, Cambridge CB1 6GB, UK.

出版信息

J Chem Inf Comput Sci. 2004 Nov-Dec;44(6):2157-66. doi: 10.1021/ci049806z.

Abstract

We have designed four generations of a low molecular weight fragment library for use in NMR-based screening against protein targets. The library initially contained 723 fragments which were selected manually from the Available Chemicals Directory. A series of in silico filters and property calculations were developed to automate the selection process, allowing a larger database of 1.79 M available compounds to be searched for a further 357 compounds that were added to the library. A kinase binding pharmacophore was then derived to select 174 kinase-focused fragments. Finally, an additional 61 fragments were selected to increase the number of different pharmacophores represented within the library. All of the fragments added to the library passed quality checks to ensure they were suitable for the screening protocol, with appropriate solubility, purity, chemical stability, and unambiguous NMR spectrum. The successive generations of libraries have been characterized through analysis of structural properties (molecular weight, lipophilicity, polar surface area, number of rotatable bonds, and hydrogen-bonding potential) and by analyzing their pharmacophoric complexity. These calculations have been used to compare the fragment libraries with a drug-like reference set of compounds and a set of molecules that bind to protein active sites. In addition, an analysis of the overall results of screening the library against the ATP binding site of two protein targets (HSP90 and CDK2) reveals different patterns of fragment binding, demonstrating that the approach can find selective compounds that discriminate between related binding sites.

摘要

我们设计了四代低分子量片段库,用于基于核磁共振的蛋白质靶点筛选。该库最初包含723个片段,这些片段是从《可用化学品目录》中手动挑选出来的。我们开发了一系列计算机筛选过滤器和性质计算方法,以实现筛选过程的自动化,从而在179万个可用化合物的更大数据库中搜索,又向库中添加了357个化合物。然后推导出一种激酶结合药效团,以挑选出174个聚焦激酶的片段。最后,又挑选了61个片段,以增加库中所代表的不同药效团的数量。所有添加到库中的片段都通过了质量检查,以确保它们适合筛选方案,具有适当的溶解度、纯度、化学稳定性和明确的核磁共振谱。通过对结构性质(分子量、亲脂性、极性表面积、可旋转键的数量和氢键潜力)的分析以及对药效团复杂性的分析,对后续几代库进行了表征。这些计算被用于将片段库与一组类药参考化合物以及一组与蛋白质活性位点结合的分子进行比较。此外,对该库针对两个蛋白质靶点(HSP90和CDK2)的ATP结合位点进行筛选的总体结果分析显示出不同的片段结合模式,这表明该方法能够找到区分相关结合位点的选择性化合物。

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