Integrated Approaches in Drug Repositioning Highlight Ouabain and Helenalin as Potential Drug Candidates for Pulmonary Fibrosis

New approaches to drug discovery are urgently needed, especially for diseases with complex molecular mechanisms where current treatments show limited efficacy. We present a data-driven workflow for drug repositioning that integrates high-throughput and virtual screening, molecular docking, and mechanistic pharmacokinetic modeling with biological validation using lung fibrosis as a model disease. High-throughput screening assays and LINCS L1000, SwissTarget, and Unified Knowledge Space (UKS) databases identified ouabain and helenalin as candidates targeting lung fibrosis-related genes. Pharmacophore modeling, docking analysis, and physiologically based pharmacokinetic modeling confirmed drug-like properties comparable to current lung fibrosis treatments. In silico findings were validated using RNA-sequencing data from idiopathic pulmonary fibrosis patients and quantitative polymerase chain reaction data from human alveolar epithelial cells exposed to profibrotic transforming growth factor-β. In vitro, helenalin and ouabain induced distinct gene expression profiles. The anti-inflammatory signature observed for helenalin points to preliminary functional potential warranting further investigation. This workflow can be generalized across diverse therapeutic areas to accelerate cost-effective drug discovery and repositioning.