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用于G蛋白偶联受体二聚化建模的计算方法。

Computational approaches for modeling GPCR dimerization.

作者信息

Meng Xuan-Yu, Mezei Mihaly, Cui Meng

机构信息

Institute of Quantitative Biology and Medicine, Jiangsu Provincial Key Laboratory of Radiation Medicine and Protection, Soochow University, Suzhou 215123, China.

出版信息

Curr Pharm Biotechnol. 2014;15(10):996-1006. doi: 10.2174/1389201015666141013102515.

Abstract

Growing experimental evidences suggest that dimerization and oligomerization are important for G Protein- Coupled Receptors (GPCRs) function. The detailed structural information of dimeric/oligomeric GPCRs would be very important to understand their function. Although it is encouraging that recently several experimental GPCR structures in oligomeric forms have appeared, experimental determination of GPCR structures in oligomeric forms is still a big challenge, especially in mimicking the membrane environment. Therefore, development of computational approaches to predict dimerization of GPCRs will be highly valuable. In this review, we summarize computational approaches that have been developed and used for modeling of GPCR dimerization. In addition, we introduce a novel two-dimensional Brownian Dynamics based protein docking approach, which we have recently adapted, for GPCR dimer prediction.

摘要

越来越多的实验证据表明,二聚化和寡聚化对于G蛋白偶联受体(GPCRs)的功能很重要。二聚体/寡聚体GPCRs的详细结构信息对于理解其功能非常重要。尽管最近出现了几个寡聚形式的实验性GPCR结构,这令人鼓舞,但寡聚形式的GPCR结构的实验测定仍然是一个巨大的挑战,尤其是在模拟膜环境方面。因此,开发预测GPCRs二聚化的计算方法将非常有价值。在这篇综述中,我们总结了已开发并用于GPCR二聚化建模的计算方法。此外,我们介绍了一种基于二维布朗动力学的新型蛋白质对接方法,这是我们最近改编用于GPCR二聚体预测的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30d7/4237661/ad63aa068b83/nihms-636694-f0001.jpg

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