Integrative Network-Bioinformatics and Molecular Docking of Polycystic Ovary Syndrome: Unraveling Molecular Links between Oxidative Stress, Insulin Resistance, Hyperandrogenism, Inflammation, and Endothelial Dysfunction

Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder associated with hyperandrogenism, insulin resistance, chronic low-grade inflammation, oxidative stress, and endothelial dysfunction. However, the molecular relationships linking these abnormalities remain incompletely understood. This study aimed to develop an integrative network-bioinformatics framework to investigate these interconnected processes, prioritize potential therapeutic targets, and assess the predicted binding of quercetin to selected hub proteins. Clinical and biochemical data from 120 women (60 with PCOS and 60 healthy controls) were used to prioritize nine biomarkers: malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), homeostatic model assessment of insulin resistance (HOMA-IR), testosterone, high-sensitivity C-reactive protein (hs-CRP), nitric oxide (NO), and flow-mediated dilation (FMD). These biomarkers were mapped to 61 candidate genes and intersected with a curated PCOS-associated gene set, yielding 23 candidate genes. A protein–protein interaction network was constructed using STRING and analyzed in Cytoscape. Consensus centrality analysis, network-module detection, functional enrichment, and independent transcriptomic comparison were used to prioritize and characterize candidate genes. Molecular docking with AutoDock Vina evaluated quercetin binding to five proteins: IL6, TNF, CYP17A1, AR, and NFKB1. The resulting network comprised 23 nodes and 70 edges (density = 0.277). Consensus analysis prioritized IL6, TNF, IL1B, NFKB1, FOXO1, and CYP17A1 as central candidates. Network analysis indicated links between inflammatory and endothelial processes and steroidogenic and hyperandrogenism-related mechanisms; FOXO1 and AR may contribute to cross-pathway regulation. Enrichment analysis highlighted steroid hormone biosynthesis and metabolic–inflammatory signaling, while transcriptomic comparison provided additional support for IL1B as a PCOS-associated inflammatory candidate. Quercetin showed favorable predicted binding energies against all five targets, with the strongest predicted affinities for TNF (−8.924 kcal/mol) and AR (−8.209 kcal/mol). These findings provide a systems-level hypothesis connecting oxidative stress, insulin resistance, inflammation, hyperandrogenism, and endothelial dysfunction in PCOS. The prioritized proteins and predicted quercetin interactions require further structural validation, molecular dynamics simulations, and experimental investigation before therapeutic conclusions can be drawn.