Computational drug discovery under RNA times.

Q3 Biochemistry, Genetics and Molecular Biology QRB Discovery Pub Date : 2022-01-01 DOI:10.1017/qrd.2022.20
Mattia Bernetti, Riccardo Aguti, Stefano Bosio, Maurizio Recanatini, Matteo Masetti, Andrea Cavalli
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引用次数: 2

Abstract

RNA molecules play many functional and regulatory roles in cells, and hence, have gained considerable traction in recent times as therapeutic interventions. Within drug discovery, structure-based approaches have successfully identified potent and selective small-molecule modulators of pharmaceutically relevant protein targets. Here, we embrace the perspective of computational chemists who use these traditional approaches, and we discuss the challenges of extending these methods to target RNA molecules. In particular, we focus on recognition between RNA and small-molecule binders, on selectivity, and on the expected properties of RNA ligands.

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RNA时代的计算药物发现。
RNA分子在细胞中发挥着许多功能和调节作用,因此近年来作为治疗干预手段获得了相当大的关注。在药物发现中,基于结构的方法已经成功地确定了药物相关蛋白靶点的有效和选择性小分子调节剂。在这里,我们接受了使用这些传统方法的计算化学家的观点,并讨论了将这些方法扩展到靶向RNA分子的挑战。特别是,我们专注于RNA和小分子结合物之间的识别,选择性和RNA配体的预期性质。
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
QRB Discovery
QRB Discovery Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
3.60
自引率
0.00%
发文量
18
审稿时长
12 weeks
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