Anant A

How can advanced in silico methods be used to repurpose or discover more effective, selective, and potent drug therapy for EGFR-mediated lactate metabolism in cancer cells?

Started July 13, 2023

Abstract or project description

Lactate is an important metabolite in both cancer and non-cancer cells. It has been shown to mediate immunosuppression and metabolic rewiring in tumors, accelerating tumor progression. A class of enzymes known as lactate dehydrogenases, LDHs, allows cancer cells to transform excess pyruvate into lactate in anaerobic respiration, and then reconvert lactate into pyruvate for ATP production. Thus, developing new effective therapeutics against the action of LDH is critical to diminishing the energy source of cancer cells. Unfortunately, there are currently no cancer-based clinical LDH inhibitors. In this project, we aim to develop potent and safe inhibitors that outperform existing pre-clinical therapies. We use the DepMap portal to identify LDH isoforms LDHA and LDHB as potential targets for cancer therapy and show that the LDHA target has a high predictive power for prognosis across many different cancers. We then use in-silico techniques, such as virtual screening, pharmacophore modeling, protein structure analysis, and inhibitor selectivity analysis to design novel and effective small molecules that can inhibit both LDHA and LDHB, potentially addressing lactate-mediated immunosuppression and tumorigenesis. This work presents a proof-of-principle case study of an in-silico, drug discovery pipeline to identify promising therapeutics, reducing the time and resources involved in traditional trial-and-error methods for drug discovery.