ArticleComputational and structural biotechnology journal2023
ccTCM: A quantitative component and compound platform for promoting the research of traditional Chinese medicine.
Article in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Pan-Cancer Bioinformatics-Guided Evaluation of San-Huang-Xie-Xin-Tang Identifies Kidney Renal Clear Cell Carcinoma as a Potentially Responsive Cancer Type.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Network Pharmacology and Experimental Validation Unravel How Puerarin Improves Chronic Postoperative Pain.Molecular biotechnology · 2026Article
- Online sources of health-related traditional knowledge: content for a traditional medicine library.Bulletin of the World Health Organization · 2026Review
- Comprehensive network pharmacology study on Huangjing Wan in the treatment of ischaemic stroke.Medicine · 2026Article
- Exosomes-loaded with traditional Chinese medicine constituents: a novel therapeutic avenue for aplastic anemia.Chinese medicine · 2026Review
- Bicuculline fromComputational and structural biotechnology journal · 2026Article
- MSAT: a FAERS-informed heterogeneous graph neural network for pharmacovigilance prediction of Chinese materia medica-associated adverse drug reactions.Frontiers in pharmacology · 2026Article
- HerbComb: An integrated database for the discovery of novel combinational therapies from herbal medicines.Computational and structural biotechnology journal · 2025Article
- TarKG: a comprehensive biomedical knowledge graph for target discovery.Bioinformatics (Oxford, England) · 2024Article
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Authors and funding
14 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Traditional Chinese medicine (TCM) databases play a vital role in bridging the gap between TCM and modern medicine, as well as in promoting the popularity of TCM. Elucidating the bioactive ingredients of Chinese medicinal materials is key to TCM modernization and new drug discovery. However, one drawback of current TCM databases is the lack of quantitative data on the constituents of Chinese medicinal materials. Herein, we present ccTCM, a web-based platform designed to provide a component and compound-content-based resource on TCM and analysis services for medical experts. In terms of design features, ccTCM combines resource distribution, similarity analysis, and molecular-mechanism analysis to accelerate the discovery of bioactive ingredients in TCM. ccTCM contains 273 Chinese medicinal materials commonly used in clinical settings, covering 29 functional classifications. By searching and comparing, we finally adopted 2043 studies, from which we collected the compounds contained in each TCM with content greater than 0.001 %, and a total of 1449 were extracted. Subsequently, we collected 40,767 compound-target pairs by integrating multiple databases. Taken together, ccTCM is a versatile platform that can be used by TCM scientists to perform scientific and clinical TCM studies based on quantified ingredients of Chinese medicinal materials. ccTCM is freely accessible at http://www.cctcm.org.cn.
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