Metastatic Castration-Resistant Prostate Cancer (mCRPC) remains a significant therapeutic challenge due to its aggressive nature and resistance to conventional hormone therapies. Elevated glycolysis is a hallmark of mCRPC, presenting a potential therapeutic target. This study explores computational approaches to identify and evaluate drugs targeting metabolic pathways, specifically glycolysis, in mCRPC. Using in silico methods, we screened a library of compounds for their efficacy against glycolytic enzymes upregulated in mCRPC. Subsequent molecular docking, dynamics simulations, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling identified several promising candidates. Our findings suggest that targeting glycolysis in mCRPC could offer a novel therapeutic avenue, potentially overcoming resistance mechanisms and improving patient outcomes.
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Archives of Surgical Oncology received 37 citations as per Google Scholar report
