After experiencing the COVID-19 pandemic, it is widely acknowledged that a rapid drug repurposing method is highly needed. A series of useful drug repurposing tools have been developed based on data-driven modeling and network pharmacology. Based on the disease module, we identified several hub proteins that play important roles in the onset and development of the COVID-19, which are potential targets for repositioning approved drugs. Moreover, different network distance metrics were applied to quantify the relationship between drug targets and COVID-19 disease targets in the protein–protein-interaction (PPI) network and predict COVID-19 therapeutic effects of bioactive herbal ingredients and chemicals. Furthermore, the tentative mechanisms of candidates were illustrated through molecular docking and gene enrichment analysis. We obtained 15 chemical and 15 herbal ingredient candidates and found that different drugs may play different roles in the process of virus invasion and the onset and development of the COVID-19 disease. Given pandemic outbreaks, our method has an undeniable immense advantage in the feasibility analysis of drug repurposing or drug screening, especially in the analysis of herbal ingredients.

中文翻译：

---

通过网络分析和筛选化学物质和草药成分，识别 COVID-19 的潜在治疗靶点和机制

在经历了 COVID-19 大流行之后，人们普遍认识到非常需要一种快速的药物再利用方法。基于数据驱动建模和网络药理学，开发了一系列有用的药物再利用工具。基于疾病模块，我们确定了几种在 COVID-19 的发病和发展中发挥重要作用的枢纽蛋白，它们是重新定位已批准药物的潜在靶点。此外，应用不同的网络距离度量来量化蛋白质-蛋白质相互作用（PPI）网络中药物靶点和COVID-19疾病靶点之间的关系，并预测生物活性草药成分和化学品的COVID-19治疗效果。此外，通过分子对接和基因富集分析阐明了候选者的初步机制。我们获得了 15 种化学成分和 15 种草药候选成分，发现不同的药物可能在病毒入侵过程以及 COVID-19 疾病的发病和发展过程中发挥不同的作用。鉴于大流行的爆发，我们的方法在药物再利用或药物筛选的可行性分析，特别是在草药成分的分析方面具有不可否认的巨大优势。