Abstract:
Background: Mycetoma is one of the neglected tropical diseases that considered as a public health problem with socio-economic impact in several developing countries. There is no effective treatment or a vaccine for it, thus the aim of this study is to design a peptide-based vaccine against Madurella mycetomatis infection via in silico approaches, using the immunogenic site Pyruvate kinase (PK).
Material and Methods:
A sequence of Pyruvate kinase Madurella mycetomatis protein was retrieved from the National Center for Biotechnology Information (NCBI). Immunoinformatics tools were used to predict B and T-cell epitopes and to calculate the population coverage.
Result and Discussion: Three epitopes predicted for B cell (102GSYPSEAV109, 214DFTKV218, 117LKAENSIPY125) as a peptide-based vaccine. 
Four shared epitopes (117LKAENSIPY125, 197LYRGVYPFL205, 198YRGVYPFLF206, 225IKWGLSHAI233) between MHC-I and MHC-II with epitope set 94.62% Worldwide and 92.38% in Sudan. Moreover, one shared epitope (117LKAENSIPY125) predicted in B-cell, MHC-I and MHC-II with high population coverage World combined MHC-I and MHC-II 77.92% and 57.78% in Sudan. 
This is the first study was done to predict peptide-based vaccine against Pyruvate kinase of Madurella mycetomatis, so this study will provide a strong base for development of vaccine after in vivo and in vitro studies confirmation of all this candidate epitopes as effective peptide vaccine.

Vaccinomics approach for designing potentail peptide vaccine by targeting pyruvate kinase of Madurella mycetomatis