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用于预测蛋白质-RNA 界面热点的计算方法。

Computational methods for predicting hotspots at protein-RNA interfaces.

机构信息

Key Laboratory of Pesticide and Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan, China.

International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan, China.

出版信息

Wiley Interdiscip Rev RNA. 2022 Mar;13(2):e1675. doi: 10.1002/wrna.1675. Epub 2021 Jun 2.

Abstract

Protein-RNA interactions play essential roles in many critical biological events. A comprehensive understanding of the mechanisms underlying these interactions is helpful when studying cellular activities and therapeutic applications. Hotspots are a small portion of residues contributing much toward protein-RNA binding affinity. In pharmaceutical research, the hotspot residues are seen as the best option for designing small molecules to target proteins of therapeutic interest. With the accumulation of experimental data about protein-RNA interactions, computational methods have been produced for hotspot prediction on a large scale. In this review, we first present an overview of the existing databases for protein-RNA binding data. Furthermore, we outline the most adopted computational methods for hotspots prediction in protein-RNA interactions. Finally, we discuss the applications of hotspot prediction. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA Methods > RNA Analyses In Vitro and In Silico.

摘要

蛋白质与 RNA 的相互作用在许多关键的生物事件中起着至关重要的作用。全面了解这些相互作用的机制有助于研究细胞活动和治疗应用。热点残基是对蛋白质与 RNA 结合亲和力贡献较大的一小部分残基。在药物研究中,热点残基被视为设计小分子药物以靶向治疗相关蛋白的最佳选择。随着蛋白质与 RNA 相互作用的实验数据的积累,已经开发出了大规模预测热点的计算方法。在这篇综述中,我们首先介绍了现有的蛋白质 RNA 结合数据数据库概述。此外,我们还概述了蛋白质 RNA 相互作用中热点预测最常采用的计算方法。最后,我们讨论了热点预测的应用。本文属于以下类别:RNA 与蛋白质和其他分子的相互作用 > 蛋白质-RNA 识别 RNA 与蛋白质和其他分子的相互作用 > 蛋白质-RNA 相互作用:功能意义 RNA 方法 > 体外和计算机模拟的 RNA 分析。

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