Niranjan Vidya, Setlur Anagha Shamsundar, Karunakaran Chandrashekar, Uttarkar Akshay, Kumar Kalavathi Murugan, Skariyachan Sinosh
Department of Biotechnology, RV College of Engineering, Bengaluru, Karnataka India.
Department of Bioinformatics, Pondicherry University, Chinna Kalapet, Kalapet, Puducherry, Tamil Nadu India.
Struct Chem. 2022;33(5):1585-1608. doi: 10.1007/s11224-022-02020-z. Epub 2022 Aug 3.
The unprecedented outbreak of the severe acute respiratory syndrome (SARS) Coronavirus-2, across the globe, triggered a worldwide uproar in the search for immediate treatment strategies. With no specific drug and not much data available, alternative approaches such as drug repurposing came to the limelight. To date, extensive research on the repositioning of drugs has led to the identification of numerous drugs against various important protein targets of the coronavirus strains, with hopes of the drugs working against the major variants of concerns (alpha, beta, gamma, delta, omicron) of the virus. Advancements in computational sciences have led to improved scope of repurposing via techniques such as structure-based approaches including molecular docking, molecular dynamic simulations and quantitative structure activity relationships, network-based approaches, and artificial intelligence-based approaches with other core machine and deep learning algorithms. This review highlights the various approaches to repurposing drugs from a computational biological perspective, with various mechanisms of action of the drugs against some of the major protein targets of SARS-CoV-2. Additionally, clinical trials data on potential COVID-19 repurposed drugs are also highlighted with stress on the major SARS-CoV-2 targets and the structural effect of variants on these targets. The interaction modelling of some important repurposed drugs has also been elucidated. Furthermore, the merits and demerits of drug repurposing are also discussed, with a focus on the scope and applications of the latest advancements in repurposing.
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）在全球范围内前所未有的爆发，引发了全球对立即寻找治疗策略的强烈反响。由于没有特定药物且可用数据不多，药物重新利用等替代方法备受关注。迄今为止，对药物重新定位的广泛研究已导致确定了多种针对冠状病毒株各种重要蛋白质靶点的药物，人们希望这些药物能对抗该病毒的主要关注变体（阿尔法、贝塔、伽马、德尔塔、奥密克戎）。计算科学的进步通过基于结构的方法（包括分子对接、分子动力学模拟和定量构效关系）、基于网络的方法以及基于人工智能的方法与其他核心机器学习和深度学习算法，扩大了重新利用的范围。本综述从计算生物学角度突出了药物重新利用的各种方法，以及这些药物针对SARS-CoV-2一些主要蛋白质靶点的各种作用机制。此外，还强调了潜在的COVID-19重新利用药物的临床试验数据，重点关注主要的SARS-CoV-2靶点以及变体对这些靶点的结构影响。还阐明了一些重要的重新利用药物的相互作用模型。此外，还讨论了药物重新利用的优缺点，重点是重新利用方面最新进展的范围和应用。
