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人毒蕈碱型乙酰胆碱受体的同源建模。

Homology modeling of human muscarinic acetylcholine receptors.

机构信息

Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University (Parkville Campus) , 381 Royal Parade, Parkville, VIC 3052 Australia.

出版信息

J Chem Inf Model. 2014 Jan 27;54(1):243-53. doi: 10.1021/ci400502u. Epub 2013 Dec 23.

Abstract

We have developed homology models of the acetylcholine muscarinic receptors M₁R-M₅R, based on the β₂-adrenergic receptor crystal as the template. This is the first report of homology modeling of all five subtypes of acetylcholine muscarinic receptors with binding sites optimized for ligand binding. The models were evaluated for their ability to discriminate between muscarinic antagonists and decoy compounds using virtual screening using enrichment factors, area under the ROC curve (AUC), and an early enrichment measure, LogAUC. The models produce rational binding modes of docked ligands as well as good enrichment capacity when tested against property-matched decoy libraries, which demonstrates their unbiased predictive ability. To test the relative effects of homology model template selection and the binding site optimization procedure, we generated and evaluated a naïve M₂R model, using the M₃R crystal structure as a template. Our results confirm previous findings that binding site optimization using ligand(s) active at a particular receptor, i.e. including functional knowledge into the model building process, has a more pronounced effect on model quality than target-template sequence similarity. The optimized M₁R-M₅R homology models are made available as part of the Supporting Information to allow researchers to use these structures, compare them to their own results, and thus advance the development of better modeling approaches.

摘要

我们已经基于β₂-肾上腺素能受体晶体作为模板,开发了乙酰胆碱毒蕈碱受体 M₁R-M₅R 的同源模型。这是首次报道对乙酰胆碱毒蕈碱受体的所有五个亚型进行同源建模,并对配体结合进行了优化。使用虚拟筛选,通过富集因子、ROC 曲线下面积(AUC)和早期富集测量 LogAUC,评估了模型区分毒蕈碱拮抗剂和诱饵化合物的能力。这些模型产生了合理的对接配体结合模式,并且在针对具有匹配性质的诱饵库进行测试时具有良好的富集能力,这证明了它们具有无偏的预测能力。为了测试同源模型模板选择和结合位点优化过程的相对效果,我们使用 M₃R 晶体结构作为模板,生成并评估了一个原始的 M₂R 模型。我们的结果证实了先前的发现,即使用特定受体上的配体(即包括功能知识到模型构建过程中)进行结合位点优化,对模型质量的影响比目标-模板序列相似性更为显著。优化后的 M₁R-M₅R 同源模型作为支持信息的一部分提供,以允许研究人员使用这些结构,将它们与自己的结果进行比较,从而推进更好的建模方法的发展。

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