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蛋白质-配体结合位点的计算机模拟鉴定与表征

In silico Identification and Characterization of Protein-Ligand Binding Sites.

作者信息

Roche Daniel Barry, McGuffin Liam James

机构信息

Institut de Biologie Computationnelle, LIRMM, CNRS, Université de Montpellier, 860 rue de St Priest, 34095, Montpellier, France.

Centre de Recherche en Biologie cellulaire de Montpellier, CNRS-UMR 5237, 1919 Route de Mende, Montpellier, 34293, France.

出版信息

Methods Mol Biol. 2016;1414:1-21. doi: 10.1007/978-1-4939-3569-7_1.

Abstract

Protein-ligand binding site prediction methods aim to predict, from amino acid sequence, protein-ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein-ligand interactions has become extremely important to help determine a protein's functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein-ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein-ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein-ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

摘要

蛋白质 - 配体结合位点预测方法旨在根据氨基酸序列,利用序列信息、结构信息或两者结合来预测蛋白质 - 配体相互作用、推定配体和配体结合位点残基。蛋白质 - 配体相互作用的计算机模拟表征对于帮助确定蛋白质的功能已变得极为重要,因为基于体内的功能阐释无法跟上当前序列数据库的增长速度。此外,体外生化功能阐释耗时、成本高,且对于大规模分析(如药物发现)可能不可行。因此,必须利用蛋白质 - 配体相互作用的计算机模拟预测来辅助功能阐释。在此,我们简要讨论蛋白质功能预测、蛋白质 - 配体相互作用预测、蛋白质结构预测技术关键评估(CASP)和连续自动评估(CAMEO)竞赛,以及它们在塑造该领域中的作用。我们还详细讨论了我们用于蛋白质 - 配体相互作用结构信息预测的前沿网络服务器方法FunFOLD。此外我们提供了使用FunFOLD网络服务器和可下载应用程序FunFOLD3的分步指南,以及一些实际应用示例,其中FunFOLD方法已用于辅助功能阐释。

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