Establishment Of Medicinal Plant Database Based On Text Mining And Analysis Of Network Pharmacology

Plants have provided human as medicines at least from the Middle Paleolithic age some60,000years ago. Plants have formed the basis of sophisticated traditional medicine systems among which are Ayurvedic, Unani, Chinese amongst others. These systems of medicine have given rise to some important drugs which are still in use today. One might expect any bioactive compounds obtained from such plants to have low human toxicity. According to the World Health Organization (WHO), almost65%of the world’s population have incorporated into their primary modality of health care. The search for new molecules, nowadays, has taken a different route where the science of ethnobotany and ethnopharmacognosy are being used as guide to lead the chemist towards different sources and classes of compounds.The concept of overall view and dialectical view of traditional Chinese medicine and traditional Chinese medicine composition, pathways and the characteristics of low selectivity and prescriptions in fangji, achieve compatibility principle, etc., are similar to the concept of Network Pharmacology. With high throughput screening methods becoming more advanced and available, large amount of bioactive compounds have been found. Systems pharmacology is an emerging area of pharmacology which utilizes network analysis of drug action as one of its approaches to deal with such complex pharmacology system. By considering drug actions and side effects in the context of the regulatory networks within which the drug targets and disease gene products function, network analysis promises to greatly increase our knowledge of the mechanisms underlying the multiple actions of drugs. Systems pharmacology can provide new approaches for drug discovery for complex diseases. The integrated approach used in systems pharmacology can allow for drug action to be considered in the context of the whole genome. Network-based studies create drug-protein network to simulate the real multiply drug-protein interactions in human body with large drug and protein data set. However, there is no databases comprehensively included all information which network pharmacology analysis requires and it is almost impossible to undergo such analysis without data support. Therefore, we have developed MPDB, a database of traditional medicinal plants with natural compounds and their potential bio-targets information. MPDB gathered874medicinal plants from China, Japan, European and US Pharmacopoeia. By text-mining approaches and manually curated from the literature,10,296natural products and3,680potential bio-targets have been found. In addition, gene pathways, functions and phenotypes and bio-network information have been integrated in according to relevant bio-targets. These complete data may aid scientists in many areas such as new drug discovery and ethnopharmacology research.