Integrating transcriptomic data with a novel drug efficacy prediction model for TCM active compound discovery.

ABSTRACT: Identifying the active natural compounds remains a challenge for drug discovery, and new algorithms need to be developed to predict active ingredients from complex natural products. Here, we proposed Meta-DEP, a Meta-paths-based Drug Efficacy Prediction based on drug-protein-disease heterogeneity network, where Meta-paths contain all the shortest paths between drug targets and disease-related proteins in the network and drug efficacy is measured by a predictive score according to drug disease network proximity. Experiments show that Meta-DEP performs better than traditional network topology analysis on drug-disease interaction prediction task. Further investigations demonstrate that the key targets identified by Meta-DEP for drug efficacy are consistent with clinical pharmacological eviden

SUBMITTER: Li Y 

PROVIDER: S-EPMC11882833 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature