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Subtractive proteomics and reverse vaccinology were employed to design a chimeric multi-epitope vaccine against melioidosis, a severe infectious disease caused by the multidrug-resistant bacterium, Burkholderia pseudomallei. From 21 non-redundant pathogen proteomes, four proteins were selected as vaccine candidates based on essentiality, virulence, non-homology to humans, structural availability, subcellular localization, and antigenicity. The major histocompatibility complex class I, II, and B-cell epitopes were predicted and evaluated for immunogenicity, solubility, allergenicity, and…mehr

Produktbeschreibung
Subtractive proteomics and reverse vaccinology were employed to design a chimeric multi-epitope vaccine against melioidosis, a severe infectious disease caused by the multidrug-resistant bacterium, Burkholderia pseudomallei. From 21 non-redundant pathogen proteomes, four proteins were selected as vaccine candidates based on essentiality, virulence, non-homology to humans, structural availability, subcellular localization, and antigenicity. The major histocompatibility complex class I, II, and B-cell epitopes were predicted and evaluated for immunogenicity, solubility, allergenicity, and hydrophilicity. A chimeric vaccine was constructed using the epitopes, adjuvants, linkers, and PADRE sequences. Docking and molecular dynamics simulations confirmed interactions between HLA alleles and TLR4, indicating the potential to elicit an immune response, demonstrating the utility of computational tools in developing vaccines against B. pseudomallei.
Autorenporträt
Dr. Mohammad Kalim Ahmad Khan, Professor of Bioinformatics at Integral University, Lucknow, India, has over 16 years of teaching experience and 85+ publications and has successfully guided six PhD scholars. His research interests include PAH-induced carcinogenesis, lifestyle diseases, and chimeric vaccine design using subtractive proteomics.