Discovery of novel SND1 inhibitors by in silico-based molecular docking and dynamics simulation methods for managing hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the life-threatening cancers in the current decade. Earlier reports suggest that protein arginine methyl transferase 5 (PRMT5) is also linked with HCC, and the symmetrically dimethylated arginine marks created by PRMT5 are read by the Staphylococcal nuclease domain-containing protein 1 (SND1), which eventually can drive HCC development. Indeed, as no inhibitors have been ascertained for SND1, we aimed to screen for new inhibitors with specificity and high affinity towards the active site of SND1. In this study, we first used the Gene Set Cancer Analysis (GSCA) dataset to evaluate the expression of SND1 in HCC. Accordingly, SND1 is the highly overexpressed gene in HCC and its overexpression affects the overall survival of HCC patients. Then, we employed a virtual screening approach to identify potential inhibitors from the ASINEX database. We utilized molecular docking to single out the potential top hits based on the docking score and mode of interaction with the SND1 active site. In the prediction, we found [4-(5,6,7,8-tetrahydro-4 H-cyclohepta[c][1,2]oxazol-3-yl)piperidin-1-yl]-[4-(trifluoromethyl)phenyl]methanone (TOP1: -10.4 kcal/mol) and 1-[2-hydroxy-2-(1-methylsulfonyl-3,4-dihydro-2 H-quinolin-6-yl)ethyl]-4-(4-methylphenyl)piperidin-4-ol (TOP2: -10.3 kcal/mol) as promising candidates than reference compound (STD: -4.6 kcal/mol). Further molecular dynamics simulations and a pharmacokinetic properties study indicate that TOP2 exhibits a more stable binding with the SND1 active site and complies with Lipinski's rule of five for drug-likeness, with no observed toxicity and good pharmacokinetic properties.