Metagenomics Medicine mapping system (MetaMed), is a novel and integrative system-wide correlation mapping system to link bacteria functions and medicine therapeutics. In this system, a well-defined similarity score between microbial metabolite entity and medicine entity is applied to link microbiota functions and existed medicine therapeutics. We demonstrate with comprehensive and solid evidence that such a linking strategy, although straightforward while never tried before, can help to achieve accurate predictions of microbial effects on human body. The key idea behind MetaMed is to use a well-defined similarity score to measure the similarity between the metabolites derived from microbe biosynthetic gene clusters (BGCs ) and public available drugs. We leverage KEGG pathway annotations to justify our proposed MetaMed score schema, and our score can be applied to identify metabolites with potential therapeutic effects effectively. By using such a scoring system, MetaMed integrates the microbe and public medicine information from MIBiG , DrugBank , LINCS , SIDER etc., providing a comprehensive data source for the deeply investigation of the microbe impact on human body by linking the microbe metabolites to the functions of known drugs, resulting in a systematic mapping system of MetaMed including the links of microbe-drug, microbe-treatment indication, microbe-side effect and microbe-immune status transition etc. The aim of our study is to present a novel computational strategy to decipher microbial effect on human health, we validate the identified relationships with literature evidences. Future experimental validation and investigations are encouraged to perform on these derived hypotheses or predicted results.

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