Abstract
BACKGROUND: Mycetoma is a distinct body tissue destructive and neglected tropical disease. It is endemic in many tropical and subtropical countries. Mycetoma is caused by bacterial infections (actinomycetoma) such as Streptomyces somaliensis and Nocardiae or true fungi (eumycetoma) such as Madurella mycetomatis. To date, treatments fail to cure the infection and the available marketed drugs are expensive and toxic upon prolonged usage. Moreover, no vaccine was prepared yet against mycetoma. AIM: The aim of this study is to predict effective epitope-based vaccine against fructose-bisphosphate aldolase enzymes of M. mycetomatis using immunoinformatics approaches. METHODS AND MATERIALS: Fructose-bisphosphate aldolase of M. mycetomatis sequence was retrieved from NCBI. Different prediction tools were used to analyze the nominee's epitopes in Immune Epitope Database for B-cell, T-cell MHC class II and class I. Then the proposed peptides were docked using Autodock 4.0 software program. RESULTS AND CONCLUSIONS: The proposed and promising peptides KYLQ show a potent binding affinity to B-cell, FEYARKHAF with a very strong binding affinity to MHC I alleles and FFKEHGVPL that shows a very strong binding affinity to MHC II and MHC I alleles. This indicates a strong potential to formulate a new vaccine, especially with the peptide FFKEHGVPL which is likely to be the first proposed epitope-based vaccine against fructose-bisphosphate aldolase of M. mycetomatis. This study recommends an in vivo assessment for the most promising peptides especially FFKEHGVPL.