Prostate cancer (PCa) is a major cause of cancer-related mortality in men. This study explores the anticancer potential of Quercetin, a polyphenolic compound with antioxidant and anti-inflammatory properties, by network pharmacology, molecular docking, and molecular dynamics simulation approaches. Target genes for Quercetin and PCa were identified from the bioinformatics databases MalaCards, Comparative Toxicogenomics Databases, SwissTargetPrediction, and Traditional Chinese Medicine Systems Pharmacology, and the obtained genes were matched using the Venny platform to find out the common genes. We obtained 11 preliminary genes and analyzed them in ShinyGO-0.77 databases to obtain genetic otology data. Then, we constructed a protein-protein interaction network in STRING, which enabled us to identify six hub genes AKT1, EGFR, MMP2, MMP9, PARP1, and ABCG2. Hub genes were analyzed in the TISIDB database for immune cell infiltration. Furthermore, a molecular docking study between the target proteins and Quercetin was performed in the SwissDock databases. Subsequently, we corroborated the docking with molecular dynamics studies using GROMACS software. Gene Ontology and KEGG pathway analyses revealed that Quercetin influences oxidative stress, mitochondrial function, and metalloproteinase activity. Immune cell infiltration analysis highlighted correlations between key genes and specific immune responses, suggesting a modulatory role of Quercetin in the tumor microenvironment. Finally, docking and molecular dynamics analysis showed that Quercetin has a stable interaction with the hub genes. In conclusion, these findings underline the potential of Quercetin to induce apoptosis, inhibit angiogenesis, and suppress metastasis, proposing it as a promising therapeutic tool for the treatment of PCa. However, additional experimental studies are required to translate these findings into clinical practice.