GPCR-BSD: a database of binding sites of human G-protein coupled receptors under diverse states.

IF 2.9 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Fan Liu, Han Zhou, Xiaonong Li, Liangliang Zhou, Chungong Yu, Haicang Zhang, Dongbo Bu, Xinmiao Liang
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引用次数: 0

Abstract

G-protein coupled receptors (GPCRs), the largest family of membrane proteins in human body, involve a great variety of biological processes and thus have become highly valuable drug targets. By binding with ligands (e.g., drugs), GPCRs switch between active and inactive conformational states, thereby performing functions such as signal transmission. The changes in binding pockets under different states are important for a better understanding of drug-target interactions. Therefore it is critical, as well as a practical need, to obtain binding sites in human GPCR structures. We report a database (called GPCR-BSD) that collects 127,990 predicted binding sites of 803 GPCRs under active and inactive states (thus 1,606 structures in total). The binding sites were identified from the predicted GPCR structures by executing three geometric-based pocket prediction methods, fpocket, CavityPlus and GHECOM. The server provides query, visualization, and comparison of the predicted binding sites for both GPCR predicted and experimentally determined structures recorded in PDB. We evaluated the identified pockets of 132 experimentally determined human GPCR structures in terms of pocket residue coverage, pocket center distance and redocking accuracy. The evaluation showed that fpocket and CavityPlus methods performed better and successfully predicted orthosteric binding sites in over 60% of the 132 experimentally determined structures. The GPCR Binding Site database is freely accessible at https://gpcrbs.bigdata.jcmsc.cn . This study not only provides a systematic evaluation of the commonly-used fpocket and CavityPlus methods for the first time but also meets the need for binding site information in GPCR studies.

GPCR-BSD:人类 G 蛋白偶联受体在不同状态下的结合位点数据库。
G 蛋白偶联受体(GPCR)是人体内最大的膜蛋白家族,涉及多种生物过程,因此成为极具价值的药物靶标。通过与配体(如药物)结合,GPCR 在活性和非活性构象状态之间切换,从而实现信号传输等功能。不同状态下结合口袋的变化对于更好地理解药物与靶点的相互作用非常重要。因此,获取人类 GPCR 结构中的结合位点至关重要,也是实际需要。我们报告的数据库(称为 GPCR-BSD)收集了 803 个 GPCR 在活跃和非活跃状态下的 127,990 个预测结合位点(因此共有 1,606 个结构)。这些结合位点是通过三种基于几何的口袋预测方法(fpocket、CavityPlus 和 GHECOM)从预测的 GPCR 结构中确定的。该服务器可对 PDB 中记录的 GPCR 预测结构和实验测定结构的预测结合位点进行查询、可视化和比较。我们从口袋残基覆盖率、口袋中心距离和再锁定准确性等方面评估了 132 个实验测定的人类 GPCR 结构的已识别口袋。评估结果表明,fpocket 和 CavityPlus 方法表现更好,在 132 个实验测定的结构中成功预测了 60% 以上的正交结合位点。GPCR 结合位点数据库可在 https://gpcrbs.bigdata.jcmsc.cn 免费访问。这项研究不仅首次对常用的 fpocket 和 CavityPlus 方法进行了系统评估,而且满足了 GPCR 研究对结合位点信息的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Bioinformatics
BMC Bioinformatics 生物-生化研究方法
CiteScore
5.70
自引率
3.30%
发文量
506
审稿时长
4.3 months
期刊介绍: BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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