In silico homology modelling and prediction of novel epitopic peptides from P24 protein of Haemonchus contortus

Abstract

Haemonchus contortus (HC) causes Haemonchosis in sheep and goats, with high mortality and morbidity due to lack of effective vaccine and increasing resistance to anthelmintic drugs. The present study was aimed at developing the 3D model of HCP24 protein and to identify the candidate epitopic peptides for effective humoral and cell-mediated immune-response. The HCP24 protein was homology modelled using the Swiss server and developed model was validated by ERRAT, VERIFY3D, PROQ, RAMPAGE and PROCHECK servers. Linear and prominent antigenic epitopes were predicted by SVMTrip and Immuno-medicine group tool. Conformational B-cell epitopes were predicted by Ellipro. MHC-I and MHC-II binding peptides were predicted by MHCPRED2, MHC2PRED and Propred I server. Proteosomal cleavage sites were predicted by Netchop server, to assess the stability of peptides. Reverse and three frame translation was done by EMBOSS tool. Bepipred and IEDB analysis also confirmed that both the predicted peptides (pep-1 and pep-2) were important antigenic region but pep-1 should have better hydrophobicity and stability. The degree of confidence achieved on scientific validation of the generated 3D model of the protein allows us to prescribe its use for research purpose. We could determine the peptide Pep-1(EDCKCTNCVCSRDEAL) should be a conformational B cell epitope with high antigenic potential and should demonstrate good binding affinity with host MHC-II and MHC-I alleles as well as stability inside host. Thus, it could be an ideal vaccine candidate for developing sub-unit vaccine against the parasite and should be assessed for protective immune response by in vitro and in-vivo studies.