This randomized trial explores semantic transformation of MolMeDB data for improved interoperability, suggesting a new approach for data sharing.
Data on molecular behaviour within biological membrane models are pivotal for predictive pharmacology, particularly for modelling bioavailability and target engagement. MolMeDB provides a curated collection of such compound-membrane interaction data. To facilitate automated reasoning and data federation, we present a semantic transformation of MolMeDB into Resource Description Framework (RDF) format, exposed through a public SPARQL endpoint. The resulting schema incorporates community-standard ontologies—including those utilised by PubChem and ChEMBL—to maximise semantic interoperability and enable complex, cross-database federated queries. Scientific contribution MolMeDB RDF provides data on interactions between molecules and membranes and molecules and transporters in machine readable graph format with links to other RDF databases. SPARQL endpoint servicing this dataset enables flexible federated querying including structural queries utilizing SACHEM.
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Martinát et al. (2026) studied this question.
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