Genes Dis. 2026 Mar 27;14(1):102167. doi: 10.1016/j.gendis.2026.102167. eCollection 2027 Jan.
ABSTRACT
Atherosclerosis (AS) remains a leading cause of cardiovascular morbidity and mortality worldwide, with current treatments focused primarily on reducing low-density lipoprotein levels while failing to repair damaged endothelial cells, thus highlighting the urgent need for novel therapeutic drugs. To address this challenge, we analyzed human AS patient single-cell RNA sequencing datasets to identify disease-driving genes and then employed connectivity map analysis to screen for potential therapeutic compounds. Using network pharmacology and machine learning to predict core drug targets, the study validated drug-target interactions through molecular docking, molecular dynamics simulations, and surface plasmon resonance analysis, with experimental validation conducted using endothelial cell damage models and ApoE -/- atherosclerotic mice. The integrative approach successfully identified narciclasine as a promising therapeutic compound that targets vascular cell adhesion molecule 1 and intercellular adhesion molecule-1 (VCAM-1/ICAM-1) for AS treatment, with molecular studies confirming strong binding affinity and experimental validation demonstrating significant alleviation of endothelial dysfunction through downregulation of VCAM-1/ICAM-1 expression and reduction of aortic plaque burden in mouse models. This multiplatform methodology combining single-cell sequencing, network pharmacology, machine learning, computational simulation, and experimental validation provides a robust framework for drug discovery while positioning narciclasine as a promising therapeutic candidate warranting clinical investigation for AS treatment.
PMID:42763524 | PMC:PMC13589088 | DOI:10.1016/j.gendis.2026.102167