School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Cai Lun Lu 1200, Shanghai 201203, China; Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Cai Lun Lu 1200, Shanghai 201203, China.
School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Cai Lun Lu 1200, Shanghai 201203, China; Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Cai Lun Lu 1200, Shanghai 201203, China.
Phytomedicine. 2022 Sep;104:154324. doi: 10.1016/j.phymed.2022.154324. Epub 2022 Jul 6.
COVID-19 highly caused contagious infections and massive deaths worldwide as well as unprecedentedly disrupting global economies and societies, and the urgent development of new antiviral medications are required. Medicinal herbs are promising resources for the discovery of prophylactic candidate against COVID-19. Considerable amounts of experimental efforts have been made on vaccines and direct-acting antiviral agents (DAAs), but neither of them was fast and fully developed.
This study examined the computational approaches that have played a significant role in drug discovery and development against COVID-19, and these computational methods and tools will be helpful for the discovery of lead compounds from phytochemicals and understanding the molecular mechanism of action of TCM in the prevention and control of the other diseases.
A search conducting in scientific databases (PubMed, Science Direct, ResearchGate, Google Scholar, and Web of Science) found a total of 2172 articles, which were retrieved via web interface of the following websites. After applying some inclusion and exclusion criteria and full-text screening, only 292 articles were collected as eligible articles.
In this review, we highlight three main categories of computational approaches including structure-based, knowledge-mining (artificial intelligence) and network-based approaches. The most commonly used database, molecular docking tool, and MD simulation software include TCMSP, AutoDock Vina, and GROMACS, respectively. Network-based approaches were mainly provided to help readers understanding the complex mechanisms of multiple TCM ingredients, targets, diseases, and networks.
Computational approaches have been broadly applied to the research of phytochemicals and TCM against COVID-19, and played a significant role in drug discovery and development in terms of the financial and time saving.
COVID-19 在全球范围内造成了高传染性感染和大量死亡，前所未有地扰乱了全球经济和社会，因此需要紧急开发新的抗病毒药物。草药是发现预防 COVID-19 的候选药物的有前途的资源。已经在疫苗和直接作用抗病毒药物 (DAA) 上进行了大量的实验努力，但它们都没有快速和完全开发。
本研究检查了在 COVID-19 药物发现和开发中发挥重要作用的计算方法，这些计算方法和工具将有助于从植物化学物质中发现先导化合物，并理解中药在预防和控制其他疾病中的作用机制。
在科学数据库（PubMed、Science Direct、ResearchGate、Google Scholar 和 Web of Science）中进行了搜索，共找到 2172 篇文章，通过以下网站的网络界面检索。在应用一些纳入和排除标准以及全文筛选后，仅收集了 292 篇符合条件的文章。
在本综述中，我们强调了包括基于结构、知识挖掘（人工智能）和基于网络的方法在内的三种主要计算方法类别。最常用的数据库、分子对接工具和 MD 模拟软件分别是 TCMSP、AutoDock Vina 和 GROMACS。基于网络的方法主要用于帮助读者理解多种中药成分、靶点、疾病和网络的复杂机制。
计算方法已广泛应用于针对 COVID-19 的植物化学物质和中药的研究，并在药物发现和开发方面节省了资金和时间，发挥了重要作用。
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