Multiscale Interactome–Guided Prioritization of Candidate Herbs and Active Compounds for Hepatic Cirrhosis Using a Biased Random Walk Algorithm

Hepatic cirrhosis is a progressive chronic liver disease driven by sustained inflammation, cell death, and tissue remodeling, and effective disease-modifying options remain limited. Here, we applied a multiscale interactome framework to prioritize candidate herbs and active compounds for hepatic cirrhosis. Herb-compound associations were collected from the OASIS database and mapped to experimentally supported compound-target interactions (DrugBank/TTD/STITCH), while cirrhosis-related proteins were curated from DisGeNET. Using a biased random-walk algorithm, we generated disease and herb/compound diffusion profiles on the multiscale network and ranked candidates by profile similarity and target overlap. Among the top-ranked herbs, Magnoliae Cortex, Notoginseng Radix et Rhizoma, Polygoni Cuspidati Rhizoma et Radix, and Capsici Fructus were supported by prior literature, whereas several high-ranking herbs lacked curated evidence and were highlighted as underexplored candidates, including Saposhnikoviae Radix and Fritillariae Cirrhosae Bulbus. Enrichment analyses indicated convergence on inflammatory and innate-immune pathways (TNF, Toll-like receptor, NF-κB) and apoptosis-related processes, with additional signals involving HIF-1 and PI3K-Akt pathways. Disease-focused subnetworks suggested mechanistic hypotheses for evidence-lacking compounds, including bergapten, oleic acid, and octadecanoic acid. Overall, we systematically prioritize herbal candidates and provides a mechanistic basis for follow-up validation in hepatic cirrhosis.