药物再利用的计算生物学方法。

3区 生物学 Q2 Biochemistry, Genetics and Molecular Biology
Tanya Waseem, Tausif Ahmed Rajput, Muhammad Saqlain Mushtaq, Mustafeez Mujtaba Babar, Jayakumar Rajadas
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引用次数: 0

摘要

药物发现与开发(DDD)过程在很大程度上依赖于各种形式的可用数据,以便为新药设计提出假设。由于生物数据的复杂性和异质性,很难利用或收集到有意义的信息。计算生物学技术为我们提供了机会,通过将大量数据细化和组织为可操作的系统性视角,我们可以更好地理解生物系统。药物再利用方法被用来克服传统药物开发所需的漫长时间和成本。它是指发现已获批准的药物的新用途,这些药物具有既定的安全性和有效性,因此需要经过较少的开发阶段。因此,通过计算生物学进行药物再利用为药物开发提供了一种系统方法,并克服了传统流程的限制。本章介绍了计算生物学的基础知识、方法和工具,可用于有效开发已获批准药物分子的再利用概况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational biology approaches for drug repurposing.

The drug discovery and development (DDD) process greatly relies on the data available in various forms to generate hypotheses for novel drug design. The complex and heterogeneous nature of biological data makes it difficult to utilize or gather meaningful information as such. Computational biology techniques have provided us with opportunities to better understand biological systems through refining and organizing large amounts of data into actionable and systematic purviews. The drug repurposing approach has been utilized to overcome the expansive time periods and costs associated with traditional drug development. It deals with discovering new uses of already approved drugs that have an established safety and efficacy profile, thereby, requiring them to go through fewer development phases. Thus, drug repurposing through computational biology provides a systematic approach to drug development and overcomes the constraints of traditional processes. The current chapter covers the basics, approaches and tools of computational biology that can be employed to effectively develop repurposing profile of already approved drug molecules.

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来源期刊
CiteScore
5.00
自引率
0.00%
发文量
110
审稿时长
4-8 weeks
期刊介绍: Progress in Molecular Biology and Translational Science (PMBTS) provides in-depth reviews on topics of exceptional scientific importance. If today you read an Article or Letter in Nature or a Research Article or Report in Science reporting findings of exceptional importance, you likely will find comprehensive coverage of that research area in a future PMBTS volume.
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