Revolutionizing leishmaniasis control: leveraging immunoinformatics for precision-driven in-silico vaccine design
Main Article Content
Keywords
immunoinformatics, leishmaniasis, multi-epitope vaccine pteridine reductase
Abstract
Leishmaniasis is an endemic disease in many countries that affects vulnerable populations of humans, dogs, and cats. This study employs immunoinformatics to design a multi-epitope vaccine construct for leishmaniasis by identifying vaccine targets on the protein Pteridine Reductase. T-cell and B-cell epitopes were screened for antigenicity, toxicity, and allergenicity. Shortlisted T-cell targets were confirmed to have appropriate IC values (≤ 50 nM and ≤ 500 nM for MHC I and MHC II, respectively). One B-cell epitope, six MHC class I epitopes, and 25 MHC class II epitopes were selected for inclusion in the vaccine construct, which was linked with EAAAK, CPGPG, and AAY linkers, along with a CPG Oligodeoxynucleotide adjuvant. The vaccine construct had a Ramachandran score of 89.9% and an Errat score of 98.4615. HLA alleles were predicted to produce an immune response in 81.8% of the global population, indicating encouraging potential for broad immunogenicity. Successful binding of the vaccine construct with TLR-9 was confirmed through molecular docking, and the docked complex exhibited a low eigenvalue of 2.06e-0.6 and a ΔG of -11.8 kcal mol-1, indicating stable binding and a high level of flexibility. Codon optimization was carried out, followed by in-silico cloning of the vaccine in Escherichia coli K12 strain using the vector pET-21a (+). These results suggest that the vaccine is stable and capable of eliciting a promising immune response against Leishmania, making it a favorable candidate for experimental trials.
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