Li Xianhai, Tang Qiang, Meng Fanbo, Du Pufeng, Chen Wei
Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
Comput Struct Biotechnol J. 2022 Mar 10;20:1345-1351. doi: 10.1016/j.csbj.2022.03.006. eCollection 2022.
The application of network pharmacology has greatly promoted the scientific interpretation of disease treatment mechanism of traditional Chinese medicine (TCM). However, the data required by network pharmacology analysis were scattered in different resources. In the present work, by integrating and reorganizing the data from multiple resources, we developed the intelligent network pharmacology platform unique for traditional Chinese medicine, called INPUT (http://cbcb.cdutcm.edu.cn/INPUT/), for automatically performing network pharmacology analysis. Besides the curated data collected from multiple resources, a series of bioinformatics tools for network pharmacology analysis were also embedded in INPUT, which makes it become the first automatic platform able to explore the disease treatment mechanisms of TCM. With the built-in tools, researchers can also analyze their own in-house data and obtain the results of pivotal ingredients, GO and KEGG pathway, protein-protein interactions, etc. In addition, as a proof-of-principle, INPUT was applied to decipher the antidepressant mechanism of a commonly used prescription. In summary, INPUT is a powerful platform for network pharmacology analysis and will facilitate the researches on drug discovery.
网络药理学的应用极大地推动了对中药疾病治疗机制的科学阐释。然而，网络药理学分析所需的数据分散于不同资源中。在本研究中，通过整合和重组来自多种资源的数据，我们开发了独具特色的用于中药的智能网络药理学平台INPUT（http://cbcb.cdutcm.edu.cn/INPUT/），以自动进行网络药理学分析。除了从多种资源收集的经过整理的数据外，INPUT还嵌入了一系列用于网络药理学分析的生物信息学工具，这使其成为首个能够探索中药疾病治疗机制的自动化平台。借助内置工具，研究人员还可以分析自己的内部数据，并获得关键成分、基因本体（GO）和京都基因与基因组百科全书（KEGG）通路、蛋白质-蛋白质相互作用等结果。此外，作为原理验证，INPUT被应用于解读一种常用方剂的抗抑郁机制。总之，INPUT是一个强大的网络药理学分析平台，将促进药物研发研究。
