Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
Hebei Medical University, Shijiazhuang 050017, China.
J Tradit Chin Med. 2022 Jun;42(3):479-486. doi: 10.19852/j.cnki.jtcm.20220408.003.
Traditional Chinese Medicine (TCM) has been extensively used as a mainstay for treating various pathologies. Combing the pharmacology and systems biology approaches, the network pharmacology (NP) approach was developed to predict the probable mechanism underlying the therapeutic effect of TCM. However, approaches solely based on NP cannot effectively elucidate the curative mechanism in a holistic and reliable manner due to limitations in NP-based methods and complexity of TCM components. Thus, integration strategies combining NP with other approaches are increasingly being used. Since the interdisciplinary research in TCM has received much attention in the advent of the big data era of which the NP-based integration strategy is broadly used, the strategy is clearly elaborated in the present review. We summarized several NP-based integration strategies and their applications in TCM studies, including multi-omics approach, gut microbiota study, chemical information analysis, data-mining, and network toxicology study.
中药（TCM）已被广泛用作治疗各种疾病的主要方法。结合药理学和系统生物学方法，开发了网络药理学（NP）方法来预测 TCM 治疗效果的可能机制。然而，由于 NP 方法的局限性和 TCM 成分的复杂性，仅基于 NP 的方法无法有效地以整体和可靠的方式阐明治疗机制。因此，越来越多地使用将 NP 与其他方法相结合的整合策略。由于 TCM 的跨学科研究在大数据时代受到了广泛关注，其中广泛应用了基于 NP 的整合策略，因此本综述对该策略进行了详细阐述。我们总结了几种基于 NP 的整合策略及其在 TCM 研究中的应用，包括多组学方法、肠道微生物组研究、化学信息分析、数据挖掘和网络毒理学研究。
