title: Database of traditional Chinese medicine and its application to studies of mechanism and to prescription validation.
abstract: OBJECTIVE
  Traditional Chinese Medicine (TCM) is widely practised and is viewed as an attractive alternative to conventional medicine. Quantitative information about TCM prescriptions, constituent herbs and herbal ingredients is necessary for studying and exploring TCM.
  
  
  METHODS
  We manually collected information on TCM in books and other printed sources in Medline. The Traditional Chinese Medicine Information Database TCM-ID, at http://tcm.cz3.nus.edu.sg/group/tcm-id/tcmid.asp, was introduced for providing comprehensive information about all aspects of TCM including prescriptions, constituent herbs, herbal ingredients, molecular structure and functional properties of active ingredients, therapeutic and side effects, clinical indication and application and related matters.
  
  
  RESULTS
  TCM-ID currently contains information for 1,588 prescriptions, 1,313 herbs, 5,669 herbal ingredients, and the 3D structure of 3,725 herbal ingredients. The value of the data in TCM-ID was illustrated by using some of the data for an in-silico study of molecular mechanism of the therapeutic effects of herbal ingredients and for developing a computer program to validate TCM multi-herb preparations.
  
  
  CONCLUSIONS
  The development of systems biology has led to a new design principle for therapeutic intervention strategy, the concept of 'magic shrapnel' (rather than the 'magic bullet'), involving many drugs against multiple targets, administered in a single treatment. TCM offers an extensive source of examples of this concept in which several active ingredients in one prescription are aimed at numerous targets and work together to provide therapeutic benefit. The database and its mining applications described here represent early efforts toward exploring TCM for new theories in drug discovery.
authors.affiliation: College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, China. xinchen@zju.edu.cn
authors.forename: X
authors.initials: X
authors.lastname: Chen
authors.forename: H
authors.initials: H
authors.lastname: Zhou
authors.forename: Y B
authors.initials: YB
authors.lastname: Liu
authors.forename: J F
authors.initials: JF
authors.lastname: Wang
authors.forename: H
authors.initials: H
authors.lastname: Li
authors.forename: C Y
authors.initials: CY
authors.lastname: Ung
authors.forename: L Y
authors.initials: LY
authors.lastname: Han
authors.forename: Z W
authors.initials: ZW
authors.lastname: Cao
authors.forename: Y Z
authors.initials: YZ
authors.lastname: Chen
mesh_terms: D001185:Artificial Intelligence; D003625:Data Collection; D016208:Databases, Factual; D004338:Drug Combinations; D011307:Drug Prescriptions / Q000592:standards*; D004365:Drugs, Chinese Herbal / Q000009:adverse effects / Q000494:pharmacology / Q000592:standards*; D016239:MEDLINE; D011955:Receptors, Drug / Q000187:drug effects / Q000235:genetics; D015203:Reproducibility of Results
chemical_list: D004338:Drug Combinations; D004365:Drugs, Chinese Herbal; D011955:Receptors, Drug