Search

Context: Egypt has a high prevalence of the hepatitis C virus (HCV) genotype 4a (GT-4a). Unfortunately, the high resistance it exhibited still was not given the deserved attention in the scientific community. There is currently no consensus on the NS5A binding site because the crystal structure of HCV NS5A has not been resolved. The prediction of the binding modes of direct-acting antivirals (DAA) with the NS5A is a point of controversy due to the fact that several research groups presented different interaction models to elucidate the NS5A binding site. Consequently, a 3D model of HCV NS5A GT-4a was constructed and evaluated using molecular dynamics (MD) simulations. The generated model implies an intriguing new orientation of the AH relative to domain I. Additionally, the probable binding modes of marketed NS5A inhibitors were explored. MD simulations validated the stability of the predicted protein–ligand complexes. The suggested model predicts that daclatasvir and similar drugs bind symmetrically to HCV NS5A GT-4a. This will allow for the development of new NS5A-directed drugs, which may result in reduced resistance and/or a wider range of effectiveness against HCV. Methods: The 3D model of HCV NS5A GT-4a was constructed using the comparative modeling approach of the web-based application Robetta. Its stability was tested with 200-ns MD simulations using the Desmond package of Schrodinger. The OPLS2005 force field was assigned for minimization, and the RMSD, RMSF, and rGyr were tracked throughout the MD simulations. Fpocket was used to identify druggable protein pockets (cavities) over the simulation trajectories. The binding modes of marketed NS5A inhibitors were then generated and refined with the aid of docking predictions made by FRED and AutoDock Vina. The stability of these drugs in complex with GT-4a was investigated by using energetic and structural analyses over MD simulations. The Prime MM-GBSA (molecular mechanics/generalized Born surface area) method was used as a validation tool after the docking stage and for the averaged clusters after the MD simulation stage. We utilized PyMOL and VMD to visualize the data. [ABSTRACT FROM AUTHOR]