Engel Stanislav, Skoumbourdis Amanda P, Childress John, Neumann Susanne, Deschamps Jeffrey R, Thomas Craig J, Colson Anny-Odile, Costanzi Stefano, Gershengorn Marvin C
The Clinical Endocrinology Branch and Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA.
J Am Chem Soc. 2008 Apr 16;130(15):5115-23. doi: 10.1021/ja077620l. Epub 2008 Mar 22.
Virtual screening has become a major focus of bioactive small molecule lead identification, and reports of agonists and antagonists discovered via virtual methods are becoming more frequent. G protein-coupled receptors (GPCRs) are the one class of protein targets for which success with this approach has been limited. This is likely due to the paucity of detailed experimental information describing GPCR structure and the intrinsic function-associated structural flexibility of GPCRs which present major challenges in the application of receptor-based virtual screening. Here we describe an in silico methodology that diminishes the effects of structural uncertainty, allowing for more inclusive representation of a potential docking interaction with exogenous ligands. Using this approach, we screened one million compounds from a virtual database, and a diverse subgroup of 100 compounds was selected, leading to experimental identification of five structurally diverse antagonists of the thyrotropin-releasing hormone receptors (TRH-R1 and TRH-R2). The chirality of the most potent chemotype was demonstrated to be important in its binding affinity to TRH receptors; the most potent stereoisomer was noted to have a 13-fold selectivity for TRH-R1 over TRH-R2. A comprehensive mutational analysis of key amino acid residues that form the putative binding pocket of TRH receptors further verified the binding modality of these small molecule antagonists. The described virtual screening approach may prove applicable in the search for novel small molecule agonists and antagonists of other GPCRs.
虚拟筛选已成为生物活性小分子先导物鉴定的主要焦点，通过虚拟方法发现激动剂和拮抗剂的报道也越来越频繁。G蛋白偶联受体（GPCRs）是这类蛋白质靶点中，采用这种方法取得的成功有限的一类。这可能是由于描述GPCR结构的详细实验信息匮乏，以及GPCRs固有的与功能相关的结构灵活性，这在基于受体的虚拟筛选应用中带来了重大挑战。在此，我们描述了一种计算机方法，该方法可减少结构不确定性的影响，从而更全面地呈现与外源性配体潜在的对接相互作用。使用这种方法，我们从一个虚拟数据库中筛选了100万个化合物，并选出了100个化合物组成的多样化亚组，从而通过实验鉴定出了促甲状腺激素释放激素受体（TRH-R1和TRH-R2）的5种结构不同的拮抗剂。最有效的化学类型的手性在其与TRH受体的结合亲和力中被证明很重要；最有效的立体异构体对TRH-R1的选择性比对TRH-R2高13倍。对构成TRH受体假定结合口袋的关键氨基酸残基进行的全面突变分析，进一步验证了这些小分子拮抗剂的结合模式。所描述的虚拟筛选方法可能适用于寻找其他GPCRs的新型小分子激动剂和拮抗剂。
