Miao Runpei, Meng Qinggang, Wang Chennan, Yuan Wenjing
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China.
Evid Based Complement Alternat Med. 2022 Jun 15;2022:1583773. doi: 10.1155/2022/1583773. eCollection 2022.
We evaluated the developmental process, research status, and existing challenges of network pharmacology. Moreover, we elucidated the corresponding solutions to improve and develop network pharmacology.
Research data for the current study were retrieved from the Web of Science. The developmental process of network pharmacology was analyzed using HisCite, whereas cooccurrence analysis of countries, institutions, keywords, and references in literature was conducted using CiteSpace.
In literature, there was a trend of annual increase of studies on network pharmacology and China was found to be the country with the most published literature on network pharmacology. The main publishing research institutions were universities of traditional Chinese medicine (TCM). The keywords with more research frequency were TCM, mechanisms, molecular docking, and quercetin, among others.
Currently, studies on network pharmacology are mainly associated with the exploration of action mechanisms of TCM. The main active ingredient in many Chinese medicines is quercetin. This ingredient may lead to deviation of research results, inability to truly analyze active ingredients, and even mislead the research direction of TCM. Such deviation may be because the database fails to reflect the content and composition changes of Chinese medicinal components. The database does not account for interactions among components, targets, and diseases, and it ignores the different pathological states of the disease. Therefore, network pharmacology should be improved from the databases and research methods.
我们评估了网络药理学的发展历程、研究现状及现存挑战。此外,我们阐明了改进和发展网络药理学的相应解决方案。
本研究的研究数据从科学网检索而来。使用HisCite分析网络药理学的发展历程,而使用CiteSpace对文献中的国家、机构、关键词和参考文献进行共现分析。
在文献中,网络药理学研究呈现出逐年增加的趋势,中国是网络药理学文献发表最多的国家。主要的发表研究机构是中医药大学。研究频率较高的关键词有中药、作用机制、分子对接和槲皮素等。
目前,网络药理学研究主要与中药作用机制的探索相关。许多中药的主要活性成分是槲皮素。这种成分可能导致研究结果出现偏差,无法真正分析活性成分,甚至误导中药的研究方向。这种偏差可能是因为数据库未能反映中药成分的含量和组成变化。数据库没有考虑成分、靶点和疾病之间的相互作用,并且忽略了疾病的不同病理状态。因此,应从数据库和研究方法方面对网络药理学进行改进。