Kratochwil Nicole A, Malherbe Pari, Lindemann Lothar, Ebeling Martin, Hoener Marius C, Mühlemann Andreas, Porter Richard H P, Stahl Martin, Gerber Paul R
Pharmaceuticals Division, F. Hoffmann-La Roche Ltd, CH-4070 Basel, Switzerland.
J Chem Inf Model. 2005 Sep-Oct;45(5):1324-36. doi: 10.1021/ci050221u.
G protein-coupled receptors (GPCRs) share a common architecture consisting of seven transmembrane (TM) domains. Various lines of evidence suggest that this fold provides a generic binding pocket within the TM region for hosting agonists, antagonists, and allosteric modulators. Here, a comprehensive and automated method allowing fast analysis and comparison of these putative binding pockets across the entire GPCR family is presented. The method relies on a robust alignment algorithm based on conservation indices, focusing on pharmacophore-like relationships between amino acids. Analysis of conservation patterns across the GPCR family and alignment to the rhodopsin X-ray structure allows the extraction of the amino acids lining the TM binding pocket in a so-called ligand binding pocket vector (LPV). In a second step, LPVs are translated to simple 3D receptor pharmacophore models, where each amino acid is represented by a single spherical pharmacophore feature and all atomic detail is omitted. Applications of the method include the assessment of selectivity issues, support of mutagenesis studies, and the derivation of rules for focused screening to identify chemical starting points in early drug discovery projects. Because of the coarseness of this 3D receptor pharmacophore model, however, meaningful scoring and ranking procedures of large sets of molecules are not justified. The LPV analysis of the trace amine-associated receptor family and its experimental validation is discussed as an example. The value of the 3D receptor model is demonstrated for a class C GPCR family, the metabotropic glutamate receptors.
G蛋白偶联受体(GPCRs)具有由七个跨膜(TM)结构域组成的共同结构。各种证据表明,这种折叠在跨膜区域提供了一个通用的结合口袋,用于容纳激动剂、拮抗剂和变构调节剂。在此,提出了一种全面且自动化的方法,可对整个GPCR家族中的这些假定结合口袋进行快速分析和比较。该方法依赖于基于保守指数的强大比对算法,重点关注氨基酸之间类似药效团的关系。对GPCR家族的保守模式进行分析并与视紫红质X射线结构进行比对,可在所谓的配体结合口袋向量(LPV)中提取跨膜结合口袋内衬的氨基酸。在第二步中,LPV被转化为简单的三维受体药效团模型,其中每个氨基酸由单个球形药效团特征表示,所有原子细节均被省略。该方法的应用包括评估选择性问题、支持诱变研究以及推导聚焦筛选规则以在早期药物发现项目中确定化学起始点。然而,由于这种三维受体药效团模型的粗糙性,对大量分子进行有意义的评分和排名程序并不合理。以痕量胺相关受体家族的LPV分析及其实验验证为例进行了讨论。对于C类GPCR家族代谢型谷氨酸受体,展示了三维受体模型的价值。