Simple but Highly Effective Three-Dimensional Chemical-Feature-Based Pharmacophore Model for Diketo Acid Derivatives as Hepatitis C Virus RNA-Dependent RNA Polymerase Inhibitors

Abstract

A molecular modeling strategy using aryl diketo acid (ADK) derivatives recently reported in the literature as hepatitis C virus (HCV) polymerase inhibitors was designed. A 3D chemical-feature-based pharmacophore model was developed using Catalyst software, which produced 10 pharmacophore hypotheses. The top-ranked one (Hypo 1), characterized by a high correlation coefficient (r = 0.965), consisted of two hydrogen bond acceptors, one negative ionizable moiety, and two hydrophobic aromatics. This model was used to predict the anti-RNA-dependent RNA polymerase (anti-RdRp) activity of 6-(1-arylmethylpyrrol-2-yl)-1,4-dioxo-5-hexenoic acids and other ADK derivatives previously synthesized in our laboratories as HIV-1 integrase inhibitors. Furthermore, the experimental IC50 values of 9 compounds, tested in vitro against recombinant HCV polymerase, were compared with the corresponding values predicted using Hypo1. A good agreement between experimental and simulated data was obtained. The results demonstrate that the hypothesis derived in this study can be considered to be a useful tool in designing new leads based on ADK scaffolds as HCV RdRp inhibitors.