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Computational Identification of IL-17 a Small-Molecule Inhibitors as Potential Therapeutics for Plaque Psoriasis
Selvakumar Rajendran1, Anantha Krishnan Dhanabalan2, Sriram Srinivasa Raghavan3
1Department of Physics, Dhanalakshmi Srinivasan Engineering College and Technology, East Coast Road, Mamallapuram, Chennai, 603 104, India. selvakumarr.physics@dscet.ac.in.
Abstract:
Plaque psoriasis is a long-term skin disease driven by the immune system, impacting around 1-3% of people worldwide. Despite the availability of various treatment options, the limitations in effectiveness, side effects, and long-term response underscore the necessity for enhanced therapeutic strategies. Focusing on the interleukin-17 (IL-17) pathway offers a promising strategy for treating plaque psoriasis. In this research, established co-crystallized peptide-derived inhibitors (PDB IDs: 5HI3, 5HI4, and 5HI5) were utilized to create energetically optimized pharmacophore models, which were then used for virtual screening of chemical libraries, resulting in 4,923 potential hit compounds. Molecular docking based on structure and induced-fit docking were subsequently conducted on IL-17 A to pinpoint potential lead compounds exhibiting advantageous binding orientations and interactions with essential active-site residues. The selected protein-ligand complexes' stability and dynamic behavior were examined through molecular dynamics (MD) simulations, which were complemented by root mean square deviation (RMSD), radius of gyration (RoG), principal component analysis (PCA), and dynamic cross-correlation matrix (DCCM) analyses. The MD simulations revealed that the selected leads retained consistent interactions in the IL-17 A binding pocket, with C2 and C3 demonstrating especially advantageous protein structural stability, while C3 displayed the most stable ligand behavior. PCA uncovered unique collective movements within the complexes, while DCCM analysis showed specific correlated and anti-correlated residue movements linked to protein conformational dynamics. Ongoing protein-ligand interactions further confirmed the stable placement of the chosen compounds within the binding site. In summary, the combined pharmacophore-based virtual screening, molecular docking, MD, PCA, and DCCM analyses discovered promising lead compounds exhibiting advantageous binding stability and dynamic behavior, offering a structural foundation for their subsequent experimental validation and potential advancement as therapeutic candidates for plaque psoriasis.