Exploiting the Potential of Computational Approaches in Medicinal Chemistry: CADD of Novel eIF6 Binders for the Development of anti-HCC PROTACs

Translational control has recently proved to play a pivotal role in the regulation of gene expression. eIF6, a translation initiation factor operating downstream of the insulin pathway, has emerged as a potential drug target, since mice heterozygous for this factor reduce the upregulation of protein synthesis under postprandial conditions and exhibit reduced white fat accumulation [1]. Increased lipid accumulation in the liver leads different pathologies, including non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH) and hepatocellular carcinoma (HCC), a leading cause of cancer-related death worldwide. Recent studies have shown that genetic inhibition of eIF6 reduces lipid metabolism and impedes NAFLD to HCC progression [2]. Considering what mentioned before, inhibiting eIF6 could represent an effective strategy to prevent liver pathological conditions. To test this hypothesis, it is proposed to develop selective degraders of eIF6 by appling the emerging “proteolysis targeting chimera” (PROTAC) strategy. Considering the lack of a specific binding pocket of eIF6, in silico studies represent the approach of choice for start this novel campaign of drug discovery, both for defining a suitable binding site of the target protein but also to identify novel binders to be developed as PROTACs. By combining docking and molecular dynamics simulations approaches with biophysical assays to confirm the computational results, this work represents an interesting case study of computational studies power applied to drug discovery. References: [1] A. Scagliola et al. Nat. Commun. 2021, 12(1), 4878. [2] A. Scagliola et al. Int. J. Mol. Sci. 2022, 23(14), 7720.