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解析计算自噬方法的规则,以加速药物研究。

Deciphering the Rules of in Silico Autophagy Methods for Expediting Medicinal Research.

机构信息

State Key Laboratory of Biotherapy and Cancer Center and Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy , Chengdu 610041 , China.

Center of Growth, Metabolism, and Aging, Key Laboratory of Bio-Resources and Eco-Environment, College of Life Sciences , Sichuan University , Chengdu 610064 , China.

出版信息

J Med Chem. 2019 Aug 8;62(15):6831-6842. doi: 10.1021/acs.jmedchem.8b01673. Epub 2019 Mar 28.

Abstract

Autophagy is a highly evolutionarily conserved cellular catabolic process responsible for degradation of damaged organelles and long-lived proteins. It is not surprising that scientific interest in the connection of autophagy and diseases has been growing. Over the past 2 decades, many new experimental approaches have been emerging in the field of targeting autophagy for medicinal research. Interestingly, in addition to experimental methods, a number of databases, Web servers, mathematics models, omics approaches, and systems biology network approaches related to autophagy have become available online, which may be collectively considered to be "in silico autophagy methods" for expediting current medicinal research. Thus, we have summarized a series of relevant in silico autophagy approaches for promoting the most appropriate usage of these resources for potential therapeutic purposes.

摘要

自噬是一种高度进化保守的细胞分解代谢过程,负责降解受损的细胞器和长寿蛋白质。毫不奇怪,科学界对自噬与疾病之间的联系越来越感兴趣。在过去的 20 年中,靶向自噬进行医学研究的领域涌现出许多新的实验方法。有趣的是,除了实验方法外,许多与自噬相关的数据库、Web 服务器、数学模型、组学方法和系统生物学网络方法也已经在线提供,这些方法可以被统称为“计算自噬方法”,以加速当前的医学研究。因此,我们总结了一系列相关的计算自噬方法,以促进这些资源的最恰当使用,以达到潜在的治疗目的。

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