ANN-QSAR, Molecular Docking, ADMET Predictions, and Molecular Dynamics Studies of Isothiazole Derivatives to Design New and Selective Inhibitors of HCV Polymerase NS5B

Abstract

<b>Background/Objectives:</b> RNA polymerase (NS5B), serves as a crucial target for pharmaceutical interventions aimed at combating the hepatitis C virus (HCV), which poses significant health challenges worldwide. The present research endeavors to explore and implement a variety of advanced molecular modeling techniques that aim to create and identify innovative and highly effective inhibitors that specifically target the RNA polymerase enzyme. <b>Methods:</b> In this study, a QSAR investigation was carried out on a set of thirty-eight isothiazole derivatives targeting NS5B inhibition and thus hepatitis C virus (HCV) treatment. The research methodology made use of various statistical techniques including multiple linear regression (MLR) and artificial neural networks (ANNs) to develop satisfactory models in terms of internal and external validation parameters, indicating their reliability in predicting the activity of new inhibitors. Accordingly, a series of potent NS5B inhibitors is designed, and their inhibitory potential is confirmed through molecular docking simulations. <b>Results:</b> These simulations showed that the interactions between these inhibitors and the active site 221 binding pocket of the NS5B protein are hydrophobic and hydrogen bond interactions, as well as carbon-hydrogen bonds and electrostatic interactions. Additionally, these newly formulated compounds displayed favorable ADMET characteristics, with molecular dynamics investigations revealing a stable energetic state and dynamic equilibrium. <b>Conclusions:</b> Our work highlights the importance of NS5B inhibition for the treatment of HCV.