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通过挖掘新兴化学模式区分生物活性和模拟化合物构象。

Distinguishing between bioactive and modeled compound conformations through mining of emerging chemical patterns.

作者信息

Auer Jens, Bajorath Jürgen

机构信息

Department of Life Science informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstrasse 2, D-53113 Bonn, Germany.

出版信息

J Chem Inf Model. 2008 Sep;48(9):1747-53. doi: 10.1021/ci8001793. Epub 2008 Aug 13.

Abstract

To systematically compare bioactive and theoretically derived compound conformations, we have analyzed 18 different sets of active small molecules with experimentally determined binding conformations and modeled conformers using a pattern recognition approach. Compound class-specific descriptor value range patterns that accurately distinguish bioactive conformations from other low-energy conformers were identified for all 18 compound classes. Discriminatory patterns were often chemically intuitive and could be well rationalized on the basis of X-ray structures of the protein-ligand complexes. Target-specific descriptor patterns can be used as filters to screen conformational ensembles for bioactive conformations.

摘要

为了系统地比较生物活性和理论推导的化合物构象,我们使用模式识别方法分析了18组不同的具有实验确定结合构象的活性小分子以及建模构象。针对所有18种化合物类别,确定了能准确区分生物活性构象与其他低能构象的化合物类别特异性描述符值范围模式。这些区分模式通常在化学上是直观的,并且可以基于蛋白质-配体复合物的X射线结构得到很好的解释。靶点特异性描述符模式可作为筛选生物活性构象的构象集合的过滤器。

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