Design of some potent non-toxic Autoimmune disorder inhibitors based on 2D-QSAR, CoMFA, molecular docking, and molecular dynamics investigations

Abstract

Current clinical research suggests that inhibitors of protein arginine deiminase 4 (PAD4), major histocompatibility complex (MHC) class II HLA-DQ-ALPHA chain, and thyrotropin receptor (or TSH receptor) which are of biological and therapeutic interest, may show potential in treating rheumatoid arthritis, type 1 diabetes, Graves' disease and other autoimmune disorder. In the present study, a comprehensive analysis was conducted on a collection of 32 compounds concerning their anti-rheumatoid arthritis activity as inhibitors of PAD4. This analysis represents the first instance in which these compounds were computationally examined, employing an in-silico approach that considered 2D-3D QSAR modeling, and molecular docking and was further validated through molecular dynamics and ADMET properties assessment. A credible 2D QSAR (Q_LOO^2 ​= ​0.6611 and R^2 ​= ​0.7535) model was constructed and verified using an external validation test set, Y-randomization, variance inflation factor (VIF), mean effect (MF), and William's plot applicability domain (AD). Ligand-based alignment was implemented in the 3D-QSAR examination. The outcomes demonstrated that CoMFA (uvepls) (Q²LOO ​= ​0.5877; R² ​= ​0.9983) possess remarkable stability and foresight. The internal validation indicated that CoMFA (uvepls) MIFs display superior predictive capability compared to COMFA (ffdsel). Structural criteria determined by the contour maps of the model and molecular docking simulations were strategically employed to computationally develop 10 new, non-toxic autoimmune disease inhibitors with increased efficacy. Docking tests were done on the newly developed compounds to illustrate their binding mechanism and to identify critical interaction residues inside the active region of rheumatoid arthritis (PDB id: 3BLU). In addition, docking results of the selected designed compounds inside the active sites of type 1 diabetes receptor (6DFX), and Graves' disease receptor (4QT5) demonstrated their rheumatoid arthritis (PDB id: 3BLU) selectivity. A molecular dynamics simulation and binding free energy calculations using the MM/GBSA technique confirmed the stability of the proposed compound D4 inside the rheumatoid arthritis (3BLU) receptor active site. In summary, the results of our investigation might give considerable insight into the future design and development of new autoimmune disease inhibitors.