Immunoinformatics, antigenicity epitopes prediction in the solute carrier family 11 of the natural resistance associated macrophage protein 1 (nramp) related with brucellosis in cattle

Brucellosis is responsible for enormous economic losses as well as considerable human morbidity in endemic areas. The bacteria infects animals such as swine, cattle, goat, sheep, and dogs. Humans can become infected indirectly through contact with infected animals or by animal products consumption. Brucellosis occurs worldwide, but it is well controlled in most developed countries. The disease is rare in industrialized nations because of routine screening of domestic livestock and animal vaccination programmers.4 Clinical disease is still common in the Middle East, Asia, Africa, South and Central America. This review article aims to describe the prevalence of brucellosis in some countries these data are available around different regions of the world, and risk factors associated infections according to regression models.3,4 There are two species of bacterial pathogens that recorded cause brucellosis disease in cattle. Firstly, the (Brucella abortus) with genome size 3,264,306 base pairs divided into two unequal size chromosomes (https://www.ncbi.nlm.nih. gov/genome/?term=Brucella+ abortus). The whole genome that downloaded from Gen Bank of the National Center of Biotechnology and Information (NCBI), within accession numbers NC_007618.1 and NC_007624.1 for chromosome I and II respectively.5 Secondly, the (Brucella melitensis) and its genome size 3,294,931 base pairs also divide into two unequal size chromosomes (https://www. ncbi.nlm. Nih.gov/genome/?term=Brucella+melitensis). The NCBI accession numbers of whole‒genome chromosome I and II are NC_003317.1 and NC_003318.1 respectively.6 predicting the antigenic sites on proteins is of major importance for the production of synthetic artificial peptide vaccines and peptide probes of antibody structure. Many predictive methods, based on various assumptions about the nature of the antigenic response have been proposed and tested. This review will discuss the principles underlying the different approaches to predicting antigenic sites and will attempt to answer the question of how well they work. As a review of Kolaskar & Tongaonkar method which coined in 1990. Analysis of data from experimentally determined antigenic sites on proteins has revealed that the hydrophobic residues Cys, Z_XU, and Val if they occur on the surface of a protein, are more likely to be a part of antigenic sites. A semi‒empirical method which makes use of physiochemical properties of amino acid residues and their frequencies of occurrence in experimentally known segmental epitopes was developed to predict antigenic determinants on proteins. Application of this method to a large number of proteins has shown that our method can predict antigenic determinants with about 75% accuracy which is better than most of the known.7,8 In another hand, the welling method for antigenicity prediction in 1985 came in contrast. Prediction of antigenic regions in a protein will be helpful for a rational approach to the synthesis of peptides which may elicit antibodies reactive with the intact protein. Earlier methods are based