Gu Shuo, Pei Jianfeng
Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.
Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA.
Evid Based Complement Alternat Med. 2017;2017:7198645. doi: 10.1155/2017/7198645. Epub 2017 Jun 11.
With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.
随着化学信息学、计算生物学和系统生物学的快速发展,近年来在中药计算研究方面取得了巨大进展,对生药学有了更深入的理解。本文从计算方法、中药复方数据库和中药网络药理学等方面对这些研究进行了综述。此外,我们选择花生四烯酸代谢网络作为案例研究,以在网络层面展示中药在炎症治疗中的调节作用。最后,基于我们之前的成功应用,提出了一种基于网络的中药研究计算流程。