Computer-aided Design of Coumarin Inhibitors of Quinone Oxidoreductase-1 (NQO1) with a Favorable Pharmacokinetic Profile

Over the last ten years, cancer therapies have struggled with drug resistance. In this report, we explore new coumarin (COU) compounds designed to inhibit the enzyme NQO1, which shows potential for effective treatment due to their favorable predicted drug properties. Three-dimensional (3D) models of NQO1-COUx complexes were generated through <i>in situ</i> modifications of the crystal structure of NQO1-COU12 (PDB entry code: 3JSX), which served as the reference compound for a training set of of 22 and a validation set of 6 VCOUs with known experimental inhibitory potencies. To identify the active conformation of COU1-22, we developed a gas-phase quantitative structure-activity relationship (QSAR) model that established a linear correlation between the calculated enthalpy of NQO1-COU complex formation and the values of experimental activities. Subsequently, we screened the Virtual Compound Library (VCL) using Lipinski's Rule of Five and the PH4 model, then assessed the potency of the new COU analogues using the retained QSAR model. The pharmacokinetic profile of the analogues obtained was also evaluated using the linear correlation equation derived from the QSAR model. The coefficient of determination (R²), the Leave One Out (LOO) cross-validated Squared and the Standard error of regression <i>σ</i> for this equation are 0.91, 0.94 and 0.14, respectively, thus revealing the high predictive power of this model. Similarly, the PH4 model, with a correlation coefficient of 0.91, demonstrated robust predictive power. A comprehensive screening of the COU virtual analogue library yielded a total of 63 drug candidates with oral bioavailability, among which the most promising compounds exhibited a predicted potency of 12.22 and a favorable pharmacokinetic profile. The integration of Quantitative Structure-Activity Relationship (QSAR) techniques and in silico screening, based on the PH4 model, has enabled us to propose potent anticancer candidates with optimal pharmacokinetic profiles.