Chinese Medicine as a Source of
Discovering New Drugs
Infection is a major category of diseases which caused
significant mortality and morbidity worldwide. Traditional Chinese herbs have
been used to treat infective diseases for thousands years. The numerous
clinical practices make it a large chemical resource library for drug
discovery. This study collected 1156 kinds of herbs and 22,172 traditional Chinese
medicinal compounds (Tcmcs). The chemical informatics and network pharmacology
were employed to analyze the anti-infective effects of herbs and Tcmcs. In
order to evaluate the drug likeness of Tcmcs, the molecular descriptors of Tcmcs
and FDA-approved drugs were calculated and the chemical space was constructed
on the basis of principal component analysis in the eight descriptors. On
purpose to estimate the effects of Tcmcs to the targets of FDA-approved
anti-infective or anti-inflammatory drugs, the molecular docking was employed.
After that, docking score weighted predictive models were used to predict the
anti-infective or anti-inflammatory efficacy of herbs.
The distribution of herbs in the phylogenetic tree showed
that most herbs were distributed in family of Asteraceae, Fabaceae and
Lamiaceae. Tcmcs were well coincide with drugs in chemical space, which
indicated that most Tcmcs had good drug-likeness. The predictive models
obtained good specificity and sensitivity with the AUC values above 0.8. At
last, 389 kinds of herbs were obtained which were distributed in 100 families,
by using the optimal cutoff values in ROC curves. These 389 herbs were widely
used in China for treatment of infection and inflammation. Traditional Chinese herbs
have a considerable number of drug-like natural products and predicted
activities to the targets of approved drugs, which would give us an opportunity
to use these herbs as a chemical resource library for drug discovery of anti-infective
and anti-inflammatory.
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