Molecular modeling and screening of antiviral peptides for Influenza A virus Polymerase basic protein 2(PB2) protein using Hpepdock software for the therapy of Influenza A

Abstract

Aim: To determine the binding affinity (kcal/mol) for various antiviral peptides to target Influenza A virus PB2 protein using Hpepdock software and comparison with the Macrocyclic iHA100 peptide (Reference peptide). Materials and methods: The three-dimensional (3D) coordinates for PB2 protein were retrieved from Protein Data Bank (PDB ID 4P1U). The structures of 16 antiviral peptides were modeled using HPEPDOCK. The Molecular docking analysis of PB2 protein with derived antiviral peptides was performed using Hpepdock software. This software employs an algorithm that generates the output complexes based on the peptide conformations and orientations. Results: Molecular docking analysis revealed that antiviral peptides, P9R Peptide 2, P9R Peptide 3 and P9R Peptide 1, could bind PB2 protein with higher affinity in comparison with the reference Macrocyclic iHA-100 peptide. The antiviral peptides of P9R Peptide 2, P9R Peptide 3 and P9R Peptide 1 with p=0.786, p>0.05 insignificant (-202.728Kcal/mol), p=0.001, p<0.05 significant (-198.255 Kcal/mol), p=0.259, p>0.05 insignificant (-195,788 Kcal/mol) showed better results in comparison to reference Macrocyclic iHA-100 peptide (-154.392 Kcal/ mol). Conclusion: The identified antiviral peptides could more effectively inhibit PB2 protein than the other available peptides on the market to treat Influenza A viral disease.