Design of novel multi-epitope vaccines against severe acute respiratory syndrome validated through multistage molecular interaction and dynamics

Abstract

Severe acute respiratory syndrome (SARS) is endemic in South China and is continuing to spread worldwide since the 2003 outbreak, affecting human population of 37 countries till present. SARS is caused by the severe acute respiratory syndrome Coronavirus (SARS-CoV). In the present study, we have designed two multi-epitope vaccines (MEVs) composed of cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B cell epitopes overlap, bearing the potential to elicit cellular as well as humoral immune response. We have used truncated (residues 10–153) Onchocerca volvulus activation-associated secreted protein-1 as molecular adjuvants at N-terminal of both the MEVs. Selected overlapping epitopes of both the MEVs were further validated for stable molecular interactions with their respective human leukocyte antigen class I and II allele binders. Moreover, CTL epitopes were further studied for their molecular interaction with transporter associated with antigen processing. Furthermore, after tertiary structure modelling, both the MEVs were validated for their stable molecular interaction with Toll-like receptors 2 and 4. Codon-optimized cDNA of both the MEVs was analysed for their potential high level of expression in the mammalian cell line (Human) needed for their further in vivo testing. Overall, the present study proposes in silico validated design of two MEVs against SARS composed of specific epitopes with the potential to cause a high level of SARS-CoV specific cellular as well as humoral immune response.

Communicated by Ramaswamy H. Sarma     

Immunoinformatics Approach to Design T-cell Epitope-Based Vaccine Against Hendra Virus

Screening of HLA class II epitope-based peptides as potential vaccine candidates is one of the most rational approach for vaccine development against Hendra virus (HeV) infection, for which currently there is no successful vaccine in practice. In this study, screening of epitopes from HeV proteins viz matrix, glycoprotein, nucleocapsid, fusion, C protein, V protein, W protein and polymerase, followed by highest binding affinity & molecular dynamic simulation of selected T-cell epitopes with their corresponding HLA class II alleles has been done. The server ProPred facilitates the binding prediction of HLA class II allele specific epitopes from the antigenic protein sequences of HeV. PEPstrMOD server was used for PDB structure modeling of the screened epitopes and MODELLER was used for HLA alleles modeling. We docked the selected T-cell epitopes with their corresponding HLA allele structures using the AutoDock 4.2 tool. Further the selected docked complex structures were optimized by NAnoscale Molecular Dynamics program (NAMD) at 5 ps, with the CHARMM-22 force field parameter incorporated in Visual Molecular Dynamics (VMD 1.9.2) and complex structure stability was evaluated by calculating RMSD values. Epitopes IRIFVPATN (Nucleocapsid), MRNLLSQSL (Nucleocapsid), VRRAGKYYS (Matrix) and VRLKCLLCG (Fusion) proteins have shown considerable binding with DRB1*0806, DRB1*1304, DRB1*0701 and DRB1*0301 HLA class II allele respectively. Toxicity, antigenicity and population coverage of epitopes IRIFVPATN, MRNLLSQSL, VRRAGKYYS and VRLKCLLCG were analyzed by Toxin Pred, Vexijen and IEDB tool, respectively. The potential T-cell epitopes can be utilized in designing comprehensive epitope-based vaccines and diagnostic kits against Hendra virus after further in-vivo studies.

     

Epitope-Based Peptides Prediction from Proteome of Nipah Virus

The identification of MHC class II epitope-based peptides are urgently needed for appropriate vaccination against Nipah virus (NiV) because there are currently no approved vaccines for human NiV infection. In the present study, prediction and modeling of T cell epitopes of NiV antigenic proteins nucleocapsid, phosphoprotein, matrix, fusion, glycoprotein, L protein, W protein, V protein and C protein followed by the binding simulation studies of predicted highest binding scores with their corresponding MHC class II alleles were done. Immunoinformatic tool ProPred was used to predict the promiscuous MHC class II epitopes of viral antigenic proteins. PEPstr server did the 3D structure models of the epitopes and Modeller 9.10 did alleles. We docked epitope with allele structure using the AutoDock 4.2 Tool. The docked peptide–allele complex structure was optimized using molecular dynamics simulation for 5 ps with the CHARMM-22 force field using NAnoscale Molecular Dynamics program incorporated in visual molecular dynamics (VMD 1.9.2) and then evaluating the stability of complex structure by calculating RMSD values. Epitope MKLQFSLGS of Matrix protein has considerable binding energy and score with DRBI*0421 MHC class II allele. This predicted peptide has potential to induce T cell-mediated immune response and is expected to useful in designing epitope-based vaccines against NiV after further testing by wet lab studies.