An in silico bioinformatics framework for prioritizing candidate genes in the coronary no-reflow phenomenon

Abstract

Background: The coronary no-reflow phenomenon remains a major obstacle to optimal outcomes after primary percutaneous coronary intervention. Its mechanisms are multifactorial and not fully clarified, with genetic components increasingly recognized as important contributors. This study aims to identify key genes, characterize their biological functions, and explore in silico–based therapeutic options targeting genes implicated in this condition.

Methods: Genes related to the coronary no-reflow phenomenon were retrieved from the GeneCards database. A protein–protein interaction network was constructed using STRING, and top-ranked genes were identified via the maximal cliques centrality and maximum neighborhood component algorithms in Cytoscape. Gene ontology enrichment analysis was performed using WebGestaltR. Three-dimensional protein structures were generated with SWISS-Model and validated using ERRAT and PROCHECK.

Results: Seventy-nine genes with significant relevance were identified. Network analysis yielded 55 nodes, from which eight hub genes were identified: IL6, TNF, ICAM1, MPO, ALB, MMP9, CXCL8, and CRP. Enrichment analysis highlighted blood vessel diameter maintenance and coagulation as key biological processes, with antioxidant activity as the leading molecular function. MPO, CRP, CXCL8, and ALB demonstrated favorable structural characteristics, supporting their prioritization.

Conclusions: MPO, CRP, CXCL8, and ALB are central genes in the coronary no-reflow phenomenon and warrant further experimental validation for therapeutic development.