Immunoinformatics-Aided Design and In Vivo Validation of a Peptide-Based Multiepitope Vaccine Targeting Canine Circovirus
Gupta, Lovi Raj
Grewal, Ravneet Kaur
Shaikh, Abdul Rajjak
KAUST DepartmentPhysical Sciences and Engineering Division, Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia
Chemical Science Program
KAUST Catalysis Center (KCC)
Physical Science and Engineering (PSE) Division
Embargo End Date2023-08-03
Permanent link to this recordhttp://hdl.handle.net/10754/680137
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AbstractCanine circovirus (CanineCV) is a deadly pathogen affecting both domestic and wild carnivores including dogs. No vaccine against CanineCV is available commercially or under clinical trials. In the present study, we have designed a promising multiepitope vaccine (MEV) construct targeting multiple strains of CanineCV. A total of 545 MHCII binding CD4+T cell epitope peptides were predicted from the capsid and replicase protein from each strain of CanineCV. Five conserved epitope peptides among the three CanineCV strains were selected. The final vaccine was constructed using antigenic, nontoxic, and conserved multiple epitopes identified in silico. Further, molecular docking and molecular dynamics simulations predicted stable interactions between the predicted MEV and canine receptor TLR-5. To validate antigenicity and immunogenicity, one of the mapped epitope peptides was synthesized. In vivo analysis of the selected epitope clearly indicates CD4+T-cell-dependent generation of antibodies which further suggests that the designed MEV construct holds promise as a candidate for vaccine against CanineCV.
CitationKaushik, V., Jain, P., Akhtar, N., Joshi, A., Gupta, L. R., Grewal, R. K., Oliva, R., Shaikh, A. R., Cavallo, L., & Chawla, M. (2022). Immunoinformatics-Aided Design and In Vivo Validation of a Peptide-Based Multiepitope Vaccine Targeting Canine Circovirus. ACS Pharmacology & Translational Science. https://doi.org/10.1021/acsptsci.2c00130
SponsorsThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST). For computer time, this research used the resources of the Supercomputing Laboratory at King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. The authors would also like to acknowledge team members from STEMskills Research and Education Lab Private Limited for critical reading of the manuscript and computational support.
PublisherAmerican Chemical Society (ACS)