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解码阿片受体家族的伴侣特异性

Decoding Partner Specificity of Opioid Receptor Family.

作者信息

Barreto Carlos A V, Baptista Salete J, Preto António J, Silvério Daniel, Melo Rita, Moreira Irina S

机构信息

CNC - Center for Neuroscience and Cell Biology, University of Coimbra, Cantanhede, Portugal.

PhD Programme in Experimental Biology and Biomedicine, Institute for Interdisciplinary Research (IIIUC), University of Coimbra, Coimbra, Portugal.

出版信息

Front Mol Biosci. 2021 Sep 21;8:715215. doi: 10.3389/fmolb.2021.715215. eCollection 2021.

Abstract

This paper describes an exciting big data analysis compiled in a freely available database, which can be applied to characterize the coupling of different G-Protein coupled receptors (GPCRs) families with their intracellular partners. Opioid receptor (OR) family was used as case study in order to gain further insights into the physiological properties of these important drug targets, known to be associated with the opioid crisis, a huge socio-economic issue directly related to drug abuse. An extensive characterization of all members of the ORs family ( (MOR), (DOR), (KOR), nociceptin (NOP)) and their corresponding binding partners (ARRs: Arr2, Arr3; G-protein: G, G, G, G, G, G, G, G, G, G, G, G, G) was carried out. A multi-step approach including models' construction (multiple sequence alignment, homology modeling), complex assembling (protein complex refinement with HADDOCK and complex equilibration), and protein-protein interface characterization (including both structural and dynamics analysis) were performed. Our database can be easily applied to several GPCR sub-families, to determine the key structural and dynamical determinants involved in GPCR coupling selectivity.

摘要

本文描述了一项令人兴奋的大数据分析,该分析整合在一个免费可用的数据库中,可用于描述不同G蛋白偶联受体(GPCR)家族与其细胞内伴侣之间的偶联关系。阿片受体(OR)家族被用作案例研究,以便进一步深入了解这些重要药物靶点的生理特性,这些靶点与阿片类药物危机有关,阿片类药物危机是一个与药物滥用直接相关的巨大社会经济问题。对OR家族的所有成员(μ阿片受体(MOR)、δ阿片受体(DOR)、κ阿片受体(KOR)、孤啡肽受体(NOP))及其相应的结合伴侣( arrestin蛋白:Arr2、Arr3;G蛋白:Gαi1、Gαi2、Gαi3、Gαo、Gαq、Gα11、Gα12、Gα13、Gαs、Gαolf、Gαz)进行了广泛的表征。采用了多步骤方法,包括模型构建(多序列比对、同源建模)、复合物组装(使用HADDOCK进行蛋白质复合物优化和复合物平衡)以及蛋白质-蛋白质界面表征(包括结构和动力学分析)。我们的数据库可轻松应用于多个GPCR亚家族,以确定参与GPCR偶联选择性的关键结构和动力学决定因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2ba/8490921/2f8f6e288829/fmolb-08-715215-g001.jpg

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