Linear B cell epitope prediction for epitope vacci

Authors: Sharat Chandra Tiratha Raj Singh

Publish Date: 2012/10/12

Volume: 1, Issue: 4, Pages: 153-159

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Abstract

Neisseria meningitidis serogroup B is predominantly known for its leading role in bacterial meningitis and septicemia worldwide Although polysaccharide conjugate vaccines have been developed and used successfully against many of the serogroups of N meningitidis such strategy has proved ineffective against group B meningococci Here we proposed to develop peptide epitopebased vaccine candidates from outer membrane OM protein contained in the outer membrane vesicles OMV based on our in silico analysis In OMV a total of 236 proteins were identified only 15 64  of which were predicted to be located in the outer membrane For the preparation of specific monoclonal antibodies against pathogenic bacterial protein identification and selection of B cell epitopes that act as a vaccine target are required We selected 13 outer membrane proteins from OMV proteins while taking into consideration the removal of crossreactivity Epitopia web server was used for the prediction of B cell epitopes Epitopes are distinguished from nonepitopes by properties such as amino acid preference on the basis of amino acid composition secondary structure composition and evolutionary conservation Predicted results were subject to verification with experimental data and we performed stringbased search through IEDB Our finding shows that epitopes have general preference for charged and polar amino acids epitopes are enriched with loop as a secondary structure element that renders them flexible and also exposes another view of antibody–antigen interactionThe interaction between an antibody and its antigen is at the heart of the humoral immune response The detection of highly immunogenic regions within a given protein specifically those that elicit a humoral immune response ie B cell epitopes is central to many immunodetection and immunotherapeutic applications Irving et al 2001 Antibodies bind to their corresponding antigens at discrete sites known as antigenic determinants of epitopes The precise localization of an epitope can be essential in the development of biomedical applications such as designed vaccines diagnostic kits and immunetherapeutics Westwood and Hay 2001 Predicting epitopes is fundamental to the understanding of the basis of immunological discrimination between self and nonself as well as for mechanisms of biorecognition in general Since proteins are one of the most abundant and diverse class of antigens antigens of infectious agents and allergens much of the interest in antigen characteristics is focused on antigenic proteins Rubinstein et al 2008B cell epitopes are classified into two different groups The first group consists of linear or continuous epitopes A continuous epitope comprises a single consecutive stretch of amino acids in the protein sequence which is specifically recognized by an antibody raised against the intact protein The second group is formed by conformational or discontinuous epitopes These are epitopes composed of residues separated in the protein sequence but in spatial proximity because of the protein fold Van Regenmortel et al 1996 It has been suggested that sequencelevel analysis at exon and peptide level can be a valuable profile Liou and Huang 2012 A specific and isolated linear peptide derived from the sequence of a given antigen was able to elicit antibodies that not only bound the peptide but also strongly crossreacted with the native antigen Peptides containing linear epitopes are considered to have a high potential for vaccines In addition to the advantages of being used for vaccines peptides are easily synthesized purified stored and handled Andersen et al 2008Neisseria meningitidis is a major cause of childhood meningitis and septicemia worldwide Meningococcal disease is associated with a high fatality rate approximately 10  and survivors may develop permanent abnormalities such as deafness seizures amputation and mental retardation Offit and Peter 2003 A Gramnegative encapsulated bacterium Neisseria meningitides is classified into groups according to the chemical composition and immunogenic properties of capsular polysaccharides Serogroups A B C W135 and Y account for 95  of the infections Capsular polysaccharide or capsular polysaccharide conjugate vaccines are available against serogroup A C Y and W135 strains Jódar et al 2002 Morley et al 2001 Rouphael and Stephens 2012 However no capsulebased vaccine is available for N meningitidis serogroup B The immune system tolerates serogroup B capsular polysaccharide because of its similarity to human carbohydrate α2 → 8Nacetyl neuraminic acid or polysialic acid both consisting of repeated units of two to eight linked sialic acid Finne et al 1983 Therefore our study is focused on proteins of the outer membrane for development of effective epitope vaccine against meningococcal diseases In our previous work we predicted and characterized the T cell epitopes for epitope vaccine design from OMV proteins of N meningitidis serogroup B Chandra et al 2010An unguided experimental search for such regions is clearly laborious and resource intensive Thus computational approaches that are able to perform this task are desired The humoral immune response is based on antibody–antigen interaction which leads to a solution of numerous protein–protein interfaces We compared these interfaces with respect to physicochemical properties at the amino acid level from amino acid composition Aside from the physicochemical character of the interfaces secondary structure content was also found to be an important property of protein–protein interfaces and has been used as one of the analysis parameters In the present study the outer membrane proteins of outer membrane vesicles of Neisseria meningitidis serogroup B were used for the prediction of linear B cell epitopes Amino acid composition physicochemical properties and secondary structure element preference were analyzed to identify putative patterns in the predicted epitopesA set of 15 OM protein complements was selected from the OMV 236 nonredundant proteins and represented only 64  of the total number of proteins detected Williams et al 2007 The complete genome and protein sequences of N meningitidis serogroup B MC58 were taken from Genbank NCBI and UniProtKB The selected protein sequences were retrieved in FASTA format and used for further analysesAmino acid compositions were computed by using Expasy’s ProtParam server Gasteiger et al 2005 The similarity of human protein to OM proteins of OMV were searched using BlastP Protein secondary structure prediction was done by APSSP2 Advanced Protein Secondary Structure Prediction Server Raghava 2002The Epitopia server Rubinstein et al 2009a b has been used to predict epitopes in the manually curated dataset The Epitopia is a Webbased server that aims to predict immunogenic regions in either a protein threedimensional structure or a linear sequence Epitopia implements a machinelearning algorithm that has been trained to discern antigenic features within a given protein The Epitopia algorithm Rubinstein et al 2009a b uses a naïve Bayes classifier to predict the immunogenic potential of protein regions The classifier was trained to recognize immunogenic properties using a benchmark dataset of 66 nonredundant validated epitopes derived from antibody–antigen cocrystal structures and 194 nonredundant validated epitopes derived from antigen sequences

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