In silico design of ROR gamma inverse agonists based on 3D-QSAR and molecular docking

Retinoic acid receptor-related orphan receptor gamma (ROR gamma) plays an important role in castration-resistant prostate cancer (CRPC) cell proliferation, survival and migration. This makes ROR gamma a promising and emerging therapeutic target for CRPC. In this study, in order to design highly active ROR gamma inverse agonists, we explored the structure-activity relationship and the interactions between ROR gamma inverse agonists by using three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking. Both the comparative molecular field analysis (CoMFA) model (q(2) = 0.846, R-2 = 0.996, r(pred)(2) = 0.923) and the comparative molecular similarity index analysis (CoMSIA) model (q(2) = 0.807, R-2 = 0.982, r(pred)(2) = 0.942) showed that the constructed 3D-QSAR models have robust stability and predictive ability. The molecular docking results show that occupying the hydrophobic cavity surrounded by residues Tyr369, Val376, Ile400 and Phe401 contributes to the improvement of activity. Based on these results, ten novel molecules were designed in silico with high activity of ROR gamma inverse agonists (pIC(50) = 8.479-8.651 for CoMFA and pIC(50) = 7.928-8.241 for CoMSIA) and with a docking total score of 9.70-13.27. In addition, the ADME properties and drug likeness of these new compounds were also predicted. Overall, our results would provide valuable guidance for the design and development of potent ROR gamma inverse agonists for the treatment of CRPC.