ArticleDiscover oncology2025
Identification of prostate cancer potential therapeutic targets and virtual drug screening through combined Mendelian randomization study, Bayesian colocalization and molecular docking.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundProstate cancer (PCa) faces significant global challenges, including rising incidence and drug resistance. Our research aims to identify novel protein targets for innovative treatments, evaluate potential adverse effects, and find compounds with strong binding affinity.
methodsWe conducted a proteomic Mendelian randomization (MR) study to assess the causal relationship between plasma proteins and PCa risk. Plasma protein data were obtained from the UK Biobank Pharmaceutical Proteomics Project, which includes GWAS data for 2940 plasma proteins. The PCa GWAS data were sourced from the PRACTICAL Consortium me-ta-analysis, encompassing 79,148 patients and 61,106 controls. Plasma proteins with positive MR results were further analyzed for Bayesian colocalization, druggability, and stratification. We performed a phenome-wide association study (PheWAS) on first and second tier proteins and screened first tier proteins against TS Biochem's library of 2070 anti- PCa com-pounds using molecular docking.
resultsThe MR study revealed five plasma proteins as protective factors and nine as risk factors for PCa (P
conclusionOur study identified several protein biomarkers associated with PCa risk and screened potential compounds using molecular docking. These findings provide new insights and promising targets for PCa drug development, with beta-Amyrone showing strong potential as a dual-target inhibitor against both C5 and SCP2.
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