Integrative Bioinformatics Analysis of MicroRNA Networks in Diabetic Foot Ulcer Healing: Structure-Function Relationships and Therapeutic Target Identification

IntroductionDiabetic foot ulcers (DFU) affect 15% of diabetic patients globally. While microRNAs (miRNAs) are known regulators of wound healing, comprehensive bioinformatics analysis of their structural determinants and network interactions in DFU pathophysiology remains limited. ObjectiveTo perform integrative bioinformatics analysis of miRNA networks in DFU healing, characterizing structure-function relationships and identifying potential therapeutic targets through computational approaches. MethodsWe conducted systematic analysis using multiple bioinformatics databases and tools. MiRNA expression data were obtained from GEO datasets and literature mining. Secondary structures were predicted using RNAfold, Mfold, and RNAstructure with consensus analysis. Target prediction employed TargetScan, miRanda, and DIANA-microT. Protein-protein interaction networks were constructed using STRING. Pathway enrichment was performed with DAVID and Reactome. Pharmacophore modeling identified potential miRNA-targeting compounds using ChEMBL and PubChem databases. ResultsAnalysis identified 8 consistently dysregulated miRNAs across 15 DFU datasets (n=1,247 samples). Meta-analysis revealed miR-146a (fold-change: -3.2{+/-}0.8), miR-155 (+4.1{+/-}1.2), and miR-21 (-1.9{+/-}1.2) as key regulators. Structural analysis showed correlation between loop accessibility and target diversity (r=0.73, p<0.01). Network topology identified 3 major regulatory modules: inflammatory response (23 nodes), angiogenesis (18 nodes), and ECM remodeling (15 nodes). Drug-miRNA interaction analysis revealed 12 FDA-approved compounds with predicted miRNA-modulating activity, including metformin and curcumin analogs. ConclusionsThis comprehensive bioinformatics analysis reveals miRNA network architecture in DFU healing and identifies structure-based therapeutic targets. The integrative approach provides a computational framework for miRNA-based drug discovery in diabetic wound healing.