Feng Zhiwei, Alqarni Mohammed Hamed, Yang Peng, Tong Qin, Chowdhury Ananda, Wang Lirong, Xie Xiang-Qun
Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, ‡Computational Drug Abuse Research Center, §Drug Discovery Institute, and ∥Department of Computational Biology and Department of Structural Biology, University of Pittsburgh , Pittsburgh, Pennsylvania 15261, United States.
J Chem Inf Model. 2014 Sep 22;54(9):2483-99. doi: 10.1021/ci5002718. Epub 2014 Sep 5.
The cannabinoid receptor 2 (CB2) plays an important role in the immune system. Although a few of GPCRs crystallographic structures have been reported, it is still challenging to obtain functional transmembrane proteins and high resolution X-ray crystal structures, such as for the CB2 receptor. In the present work, we used 10 reported crystal structures of GPCRs which had high sequence identities with CB2 to construct homology-based comparative CB2 models. We applied these 10 models to perform a prescreen by using a training set consisting of 20 CB2 active compounds and 980 compounds randomly selected from the National Cancer Institute (NCI) database. We then utilized the known 170 cannabinoid receptor 1 (CB1) or CB2 selective compounds for further validation. Based on the docking results, we selected one CB2 model (constructed by β1AR) that was most consistent with the known experimental data, revealing that the defined binding pocket in our CB2 model was well-correlated with the training and testing data studies. Importantly, we identified a potential allosteric binding pocket adjacent to the orthosteric ligand-binding site, which is similar to the reported allosteric pocket for sodium ion Na(+) in the A2AAR and the δ-opioid receptor. Our studies in correlation of our data with others suggested that sodium may reduce the binding affinities of endogenous agonists or its analogs to CB2. We performed a series of docking studies to compare the important residues in the binding pockets of CB2 with CB1, including antagonist, agonist, and our CB2 neutral compound (neutral antagonist) XIE35-1001. Then, we carried out 50 ns molecular dynamics (MD) simulations for the CB2 docked with SR144528 and CP55940, respectively. We found that the conformational changes of CB2 upon antagonist/agonist binding were congruent with recent reports of those for other GPCRs. Based on these results, we further examined one known residue, Val113(3.32), and predicted two new residues, Phe183 in ECL2 and Phe281(7.35), that were important for SR144528 and CP55940 binding to CB2. We then performed site-directed mutation experimental study for these residues and validated the predictions by radiometric binding affinity assay.
大麻素受体2(CB2)在免疫系统中发挥着重要作用。尽管已经报道了一些GPCR的晶体结构,但要获得功能性跨膜蛋白和高分辨率X射线晶体结构,例如CB2受体,仍然具有挑战性。在本研究中,我们使用了10个已报道的与CB2具有高序列同一性的GPCR晶体结构来构建基于同源性的比较CB2模型。我们应用这10个模型,通过使用由20种CB2活性化合物和从美国国立癌症研究所(NCI)数据库中随机选择的980种化合物组成的训练集进行预筛选。然后,我们利用已知的170种大麻素受体1(CB1)或CB2选择性化合物进行进一步验证。基于对接结果,我们选择了一个与已知实验数据最一致的CB2模型(由β1AR构建),这表明我们CB2模型中定义的结合口袋与训练和测试数据研究具有良好的相关性。重要的是,我们在正构配体结合位点附近确定了一个潜在的变构结合口袋,这与报道的A2AAR和δ-阿片受体中钠离子Na(+)的变构口袋相似。我们将自己的数据与其他数据相关联的研究表明,钠离子可能会降低内源性激动剂或其类似物与CB2的结合亲和力。我们进行了一系列对接研究,以比较CB2与CB1结合口袋中的重要残基,包括拮抗剂、激动剂和我们的CB2中性化合物(中性拮抗剂)XIE35-1001。然后,我们分别对与SR144528和CP55940对接的CB2进行了50纳秒的分子动力学(MD)模拟。我们发现,CB2在拮抗剂/激动剂结合时的构象变化与最近关于其他GPCR的报道一致。基于这些结果,我们进一步研究了一个已知残基Val113(3.32),并预测了两个新残基,ECL2中的Phe183和Phe281(7.35),它们对SR144528和CP55940与CB2的结合很重要。然后,我们对这些残基进行了定点突变实验研究,并通过放射性结合亲和力测定验证了预测结果。