Exploring the role of hepsin in prostate cancer: bioinformatics, molecular Docking and molecular dynamics simulations

Prostate cancer (PCa) represents one of the most frequently diagnosed malignancies in men worldwide, with a high incidence and mortality rate. Although significant advances have been made in early detection, therapeutic strategies for advanced and metastatic PCa remain limited. The lack of reliable biomarkers and effective targeted therapies poses a critical challenge in clinical management. This study aims to elucidate the molecular mechanisms underlying PCa progression, focusing on identifying novel biomarkers and therapeutic targets through an integrative bioinformatics approach.

We performed a comprehensive analysis of publicly available gene expression datasets (GEO and TCGA) to identify differentially expressed genes (DEGs) associated with PCa. Using advanced computational techniques such as weighted gene co-expression network analysis (WGCNA), Lasso regression, and random forest algorithms, we pinpointed key genes involved in tumorigenesis. Further, molecular docking was employed to screen for small molecules that interact with these identified genes, followed by molecular dynamics (MD) simulations to evaluate the stability and binding affinity of the most promising compounds.

Our bioinformatics analysis revealed Hepsin (HPN) as a core gene strongly associated with PCa. We observed that HPN is closely linked to immune evasion mechanisms in the tumor microenvironment, where its expression correlates with altered immune cell infiltration, particularly T cells and macrophages. In silico screening identified Bentiromide as a potent small molecule that binds to HPN with high affinity. Molecular dynamics simulations confirmed the stability of the HPN-Bentiromide complex, showing strong non-covalent interactions, including van der Waals and electrostatic forces. The binding energy analysis further validated the potential of Bentiromide as a therapeutic candidate for PCa.

This study provides valuable insights into the molecular mechanisms of PCa, identifying HPN as a pivotal gene in cancer progression and immune evasion. We demonstrate the potential of HPN as a novel biomarker and therapeutic target for PCa. Moreover, Bentiromide emerges as a promising candidate for targeted therapy, with implications not only for PCa treatment but also for other malignancies involving immune escape mechanisms. Our findings pave the way for future experimental validation and clinical trials aimed at developing HPN-targeted therapies for cancer treatment.