1 Network pharmacology
In 2007, Yildirim et al analyzed the relationship between drug targets and disease genes. Although limited by the scarcity of disease and drug databases at that time and the incompleteness of the human protein interaction group spectrum, Hopkins proposed the concept of network pharmacology in November of the same year, and questioned the traditional drug strategy of single drug responding to a single target, believing that the treatment of disease should be carried out in series on multiple nodes [12,13]. With the rapid development of biotechnology and information technology, and the continuous improvement of databases. The reliability and applicability of network pharmacology will also be more powerful[14]. In addition, studies have found that for similar phenotypes of different diseases, it is often some similar genes that determine their pathological phenotypes. Network pharmacology no longer simply classifies the interaction of each node into the sum of individual parts, but emphasizes the network relevance of each part, so it is also considered the next strategy of personalized treatment. We can build a complex interaction network between disease, target, and drug through huge database screening and computer models, and understand the specific mechanisms and signal pathways between disease and target. As a new research mode of drug discovery and reuse in recent years, network pharmacology has made great progress in the redevelopment and application of traditional Chinese medicine[15,16,17]. In addition, for the treatment of complex diseases such as cancer, diabetes, cardiovascular disease, AIDS, and psychosis, multi-target or combined drug therapy is more effective and less toxic [9]. The method based on network pharmacology has also played a huge role in exploring the molecular mechanism and potential targets of coronavirus disease (COVID-19) in 2019. At the same time, it is a low-cost and efficient strategy and is also used to screen new candidate drugs for COVID-19[18,19,20]. Therefore, as a low-cost, time-consuming, and high-yield drug development method, we should re-examine this web-based drug development.