About IDMM

IDMM provides consolidated cross-cultural information on each materia medica (MM), which is defined as a specific part derived from a taxonomic origin. For each MM, the database presents curated information including material names, a list of traditional medicinal systems in which the material is documented, consolidated therapeutic uses, as well as associated visual resources such as material photographs and chromatographic profiles. In addition, the database also incorporated cheminformatics-based compound category prediction framework, AgreementPred, providing confidence-ranked category annotations for each compound contained within each MM.

Data in IDMM were collected from a wide range of sources, including established publicly available databases of traditional medicinal materials, natural products, botanical organisms, and chemical information, as well as individual sources providing photographic images and analytic chromatograms. Key information on traditional medicinal materials documented in China, Japan, South Korea, and Thailand were extracted from the respective official pharmacopoeias, whereas those on Indian medicinal plants were derived from IMPPAT database and Botanical Survey of India's Medicinal Plant Database of India (MPDI) in addition to Ayurveda, Unani, and Siddha pharmacopoeias. Data on chemical constituents of the medicinal materials were obtained from several databases of medicinal materials and natural products.

Different synonyms and spelling variants of botanical origins used by various databases were unified by mapping to WCVP database, whereas all chemical compounds were mapped to Compound ID of PubChem database. Each compound included in IDMM was subjected to category prediction using the AgreementPred framework. This cheminformatics approach leverages multi-representation molecular similarity to infer compound categories based on the degree of consensus across different molecular representations. The resulting predicted categories, ranked by agreement scores, provide additional functional annotations for the compounds and offer useful guidance for downstream analyses, thereby facilitating hypothesis generation in drug discovery research as well as mechanistic study.