Strategies to identify candidate repurposable drugs: COVID-19 treatment as a case example.
Strategies to identify candidate repurposable drugs: COVID-19 treatment as a case example.
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DOI：
10.1038/s41398-021-01724-w
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发表时间：
2021-11-16
影响因子：
6.8
通讯作者：
O'Donovan SM
中科院分区：
文献类型：
--
作者：
Imami AS;McCullumsmith RE;O'Donovan SM
药物再利用是一种宝贵的策略，可以确定现有药物疗法的新用途，从而克服与新药开发相关的许多时间和财务成本。 COVID-19 大流行推动了生物信息学工具的开发和使用空前激增，以识别候选可重复利用药物。我们以 COVID-19 作为案例研究，讨论了用于快速识别候选药物的机器学习和基于签名的方法的示例。基于集成网络的签名库 (LINCS) 和连接图 (CMap) 是常用的存储库，其优点是适合生物信息学培训有限的科学家使用。接下来，我们讨论生物信息学药物再利用方法的最新进展如何适用于识别中枢神经系统疾病的可再利用药物。随着成功针对神经精神和神经系统疾病病因的新疗法的开发陷入停滞，迫切需要创新策略来治疗这些复杂的脑部疾病。识别可重复利用药物的生物信息方法提供了令人兴奋的研究途径，为改善中枢神经系统疾病的治疗提供了希望。
Drug repurposing is an invaluable strategy to identify new uses for existing drug therapies that overcome many of the time and financial costs associated with novel drug development. The COVID-19 pandemic has driven an unprecedented surge in the development and use of bioinformatic tools to identify candidate repurposable drugs. Using COVID-19 as a case study, we discuss examples of machine-learning and signature-based approaches that have been adapted to rapidly identify candidate drugs. The Library of Integrated Network-based Signatures (LINCS) and Connectivity Map (CMap) are commonly used repositories and have the advantage of being amenable to use by scientists with limited bioinformatic training. Next, we discuss how these recent advances in bioinformatic drug repurposing approaches might be adapted to identify repurposable drugs for CNS disorders. As the development of novel therapies that successfully target the cause of neuropsychiatric and neurological disorders has stalled, there is a pressing need for innovative strategies to treat these complex brain disorders. Bioinformatic approaches to identify repurposable drugs provide an exciting avenue of research that offer promise for improved treatments for CNS disorders.
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