A Cheminformatic analysis of Secondary Metabolites in Jordanian Medicinal Plants and Their Potential Therapeutic Applications.

Jordan harbors a rich diversity of medicinal plants with a long history of ethnopharmacological use. However, comprehensive cheminformatic analyses of their secondary metabolites remain limited. We aim to characterize the chemical diversity and potential biological targets of secondary metabolites from Jordanian medicinal plants relative to global natural products and FDA-approved drugs. A curated dataset of 7,866 phytochemicals from 475 Jordanian medicinal plants was compiled through extensive literature mining. Physicochemical properties, Bemis–Murcko scaffolds, and molecular complexity metrics (nSPS) were computed and compared to COCONUT, LANaPDB, and FDA drug datasets. Dimensionality reduction methods (PCA, t-SNE, UMAP) visualized chemical space coverage. Ligand-based target prediction leveraging ChEMBL Actives data was performed, followed by pathway enrichment and network pharmacology analysis using Cytoscape. Jordanian phytochemicals exhibit moderate scaffold diversity and molecular complexity comparable to global natural products but distinct from FDA drugs. Chemical space analyses reveal unique clustering patterns suggestive of novel chemotypes. Ligand-based target prediction identifies multiple potential polypharmacological interactions, with several compounds showing similarity to bioactive ligands across diverse targets. Network pharmacology uncovers both established and novel compound-target-pathway associations, highlighting mechanisms related to glycoprotein processing, kinase regulation, immune modulation, and protease inhibition. This integrative computational study enriches the understanding of Jordanian medicinal plant metabolites, revealing promising chemical diversity and therapeutic potential. The findings provide a valuable resource for prioritizing candidates in natural product drug discovery.