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

Abstract

Retinoic acid receptor-related orphan receptor γ (RORγ) plays an important role in castration-resistant prostate cancer (CRPC) cell proliferation, survival and migration. This makes RORγ a promising and emerging therapeutic target for CRPC. In this study, in order to design highly active RORγ inverse agonists, we explored the structure–activity relationship and the interactions between RORγ inverse agonists by using three-dimensional quantitative structure–activity relationship (3D-QSAR) and molecular docking. Both the comparative molecular field analysis (CoMFA) model (q² = 0.846, R² = 0.996, r_pred² = 0.923) and the comparative molecular similarity index analysis (CoMSIA) model (q² = 0.807, R² = 0.982, r_pred² = 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 RORγ inverse agonists (pIC₅₀ = 8.479–8.651 for CoMFA and pIC₅₀ = 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 RORγ inverse agonists for the treatment of CRPC.