ABSTRACT
Aim at the two problems in the field of traditional Chinese medicine (TCM) mechanism elucidation, one is the lack of detailed biological processes information, next is the low efficient in constructing network models, we constructed an auxiliary elucidation system for the TCM mechanism and realize the automatic establishment of biological network model. This study used the Entity Grammar Systems (EGS) as the theoretical framework, integrated the data of formulae, herbs, chemical components, targets of component, biological reactions, signaling pathways and disease related proteins, established the formal models, wrote the reasoning engine, constructed the auxiliary elucidation system for the TCM mechanism elucidation. The platform provides an automatic modeling method for biological network model of TCM mechanism. It would be benefit to perform the in-depth research on TCM theory of natures and combination and provides the scientific references for R&D of TCM.
Subject(s)
Automation/methods , Drugs, Chinese Herbal/chemistry , Drugs, Chinese Herbal/pharmacology , Plants, Medicinal/chemistry , Animals , Automation/instrumentation , Databases, Factual , Gene Regulatory Networks , Humans , Medicine, Chinese TraditionalABSTRACT
ETHNOPHARMACOLOGICAL RELEVANCE: Interpreting the molecular interactions in Chinese herbal medicine will help to understand the molecular mechanisms of Traditional Chinese medicines (TCM) and predict the new pharmacological effects of TCM. Yet, we still lack a method which could integrate the concerned pieces of parsed knowledge about TCM. MATERIALS AND METHODS: To solve the problem, a new method named TCM grammar systems was proposed in the present article. The possibility to study the interactions of TCM at the molecular level using TCM grammar systems was explored using Herba Ephedrae Decoction (HED) as an example. RESULTS: A platform was established based on the formalism of TCM grammar systems. The related molecular network of Herba Ephedrae Decoction (HED) can be extracted automatically. The molecular network indicates that Beta2 adrenergic receptor, Glucocorticoid receptor and Interleukin12 are the relatively important targets for the anti-anaphylaxis asthma function of HED. Moreover, the anti-anaphylaxis asthma function of HED is also related with suppressing inflammation process. The results show the feasibility using TCM grammar systems to interpret the molecular mechanism of TCM. Although the results obtained depend on the database absolutely, recombination of existing knowledge in this method provides new insight for interpreting the molecular mechanism of TCM. CONCLUSIONS: TCM grammar systems could aid the interpretation of the molecular interactions in TCM to some extent. Moreover, it might be useful to predict the new pharmacological effects of TCM. The method is an in silico technology. In association with the experimental techniques, this method will play an important role in the understanding of the molecular mechanisms of TCM.