Structure-based QSAR, molecule design and bioassays of protease-activated receptor 1 inhibitors

Quantitative structure–activity relationship (QSAR) studies were performed on a series of protease-activated receptor 1 (PAR1) inhibitors to identify the key structural features responsible for their biological activity. Induced-fit docking (IFD) was used to explore the active mechanisms of all PAR1 inhibitors at the active pocket of PAR1, and the best plausible conformation was determined by IFD for further QSAR studies. Based on the best plausible conformation, structure-based descriptors and ligand descriptors incorporating the ligand–receptor interaction were calculated. The random forest method was used to select important descriptors and build the 2D-QSAR model. The results of the 2D-QSAR model gave a squared correlation coefficient (<i>R</i>²) of 0.937, a prediction squared correlation coefficient (<i>R</i>²_pred) of 0.845 and a mean square error (MSE) of 0.056. Furthermore, a 3D-QSAR model was developed via topomer comparative molecular field analysis (Topomer CoMFA), resulting in an <i>R</i>² of 0.938, a cross-validated <i>Q</i>² of 0.503 and a <i>R</i>²_pred of 0.758. Based on the developed QSAR model, Topomer search was used for virtual screening of the R2 fragment in lead-like inhibitors from the National Cancer Institute (NCI) database, which contains 260,000 molecules. Eighty-two compounds were designed with different R2 fragments, and four of these compounds were selected for further biological testing. All four compounds showed inhibitory potency against PAR1.