Suppr超能文献

基于序列的G蛋白偶联受体三维药效团模型及其在虚拟筛选中的应用。

Sequence-derived three-dimensional pharmacophore models for G-protein-coupled receptors and their application in virtual screening.

作者信息

Klabunde Thomas, Giegerich Clemens, Evers Andreas

机构信息

Research & Development, Drug Design, Sanofi-Aventis Deutschland GmbH, D-65926 Frankfurt am Main, Germany.

出版信息

J Med Chem. 2009 May 14;52(9):2923-32. doi: 10.1021/jm9001346.

Abstract

G-protein-coupled receptors (GPCRs) comprise a large protein family of significant past and current interest of pharmaceutical research. X-ray crystallography and molecular modeling combined with site-directed mutagenesis studies suggest that most family A GPCRs share a small-molecule binding site located in the outer part of the seven-transmembrane (7TM) bundle. Here we describe an automated method to derive sequence-derived three-dimensional (3D) pharmacophore models capturing the key elements for addressing this binding site by a small-molecule ligand. We have generated structure-based pharmacophore models from 10 homology models and 3 X-ray structures of receptor-ligand complexes. These 13 pharmacophores have been dissected into 35 different single-feature pharmacophore elements, each associated with a sequence motif or chemoprint, describing its molecular interaction partner(s) in the receptor. Subsequently, the protein sequences of 270 GPCRs have been searched for the presence of chemoprints and the appropriate single-feature pharmacophores have been assembled into three- to seven-feature 3D-pharmacophore models for each human family A GPCR. These models can be applied for virtual screening and for the design of subfamily directed libraries. A case study demonstrates the successful application of this approach for the identification of potent agonists for the complement component 3a receptor 1 (C3AR1) by virtual screening.

摘要

G蛋白偶联受体(GPCRs)构成了一个大型蛋白质家族,在过去和现在都是药物研究的重要关注点。X射线晶体学、分子建模以及定点诱变研究表明,大多数A类GPCRs共享一个位于七跨膜(7TM)束外部的小分子结合位点。在此,我们描述了一种自动化方法,用于推导基于序列的三维(3D)药效团模型,该模型捕捉了小分子配体与该结合位点相互作用的关键要素。我们从10个同源模型和3个受体-配体复合物的X射线结构生成了基于结构的药效团模型。这13个药效团已被剖析为35种不同的单特征药效团元素,每个元素都与一个序列基序或化学印记相关联,描述了其在受体中的分子相互作用伙伴。随后,在270个GPCRs的蛋白质序列中搜索化学印记的存在情况,并将合适的单特征药效团组装成每个人类A类GPCR的三到七特征3D药效团模型。这些模型可用于虚拟筛选和亚家族定向文库的设计。一个案例研究证明了该方法通过虚拟筛选成功鉴定补体成分3a受体1(C3AR1)强效激动剂的应用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验