ArticleBiology direct2013
Identification of B-cell epitopes in an antigen for inducing specific class of antibodies.
Article in Biology direct, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.
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61 citing papers in PubMed, 122 citations in OpenAlex.
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- In-silico design of a multi-epitope vaccine candidate against Strongyloides stercoralis.BMC infectious diseases · 2026Article
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- In Silico Design of a Multiepitope Vaccine Against Intestinal PathogenicDiseases (Basel, Switzerland) · 2025Article
- Design of a multi-epitope vaccine against drug-resistant mycobacterium tuberculosis and mycobacterium bovis using reverse vaccinology.Scientific reports · 2025Article
- Cyclic di AMP phosphodiesterase nanovaccine elicits protective immunity against Burkholderia cenocepacia infection in mice.NPJ vaccines · 2025Article
- Immunogenic mapping of potential epitopes from Tc-CTL-1 for the diagnosis of murine toxocariasis.Memorias do Instituto Oswaldo Cruz · 2025Article
- Development of a multi-neoepitope vaccine targeting non-small cell lung cancer through reverse vaccinology and bioinformatics approaches.Frontiers in immunology · 2025Article
- Advances of computational methods enhance the development of multi-epitope vaccines.Briefings in bioinformatics · 2024Review
- Characterization of antigenic proteins of the Taenia solium postoncospheral form.Molecular and biochemical parasitology · 2024Article
- Design of an epitope-based peptide vaccine against Cryptococcus neoformans.FEBS open bio · 2024Article
- Multi-epitope vaccine design of African swine fever virus considering T cell and B cell immunogenicity.AMB Express · 2024Article
- Novel prophylactic and therapeutic multi-epitope vaccine based on Ag85A, Ag85B, ESAT-6, and CFP-10 of Mycobacterium tuberculosis using an immunoinformatics approach.Osong public health and research perspectives · 2024Article
- Immunoinformatics approach for design novel multi-epitope prophylactic and therapeutic vaccine based on capsid proteins L1 and L2 and oncoproteins E6 and E7 of human papillomavirus 16 and human papillomavirus 18 against cervical cancer.Osong public health and research perspectives · 2024Article
- Exploring malaria parasite surface proteins to devise highly immunogenic multi-epitope subunit vaccine for Plasmodium falciparum.Journal, genetic engineering & biotechnology · 2024Article
- Immune Epitopes of SARS-CoV-2 Spike Protein and Considerations for Universal Vaccine Development.ImmunoHorizons · 2024Review
- Prediction of linear B-cell epitopes based on protein sequence features and BERT embeddings.Scientific reports · 2024Article
1 more citing papers are in PubMed but not listed here.
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5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the past, numerous methods have been developed for predicting antigenic regions or B-cell epitopes that can induce B-cell response. To the best of authors' knowledge, no method has been developed for predicting B-cell epitopes that can induce a specific class of antibody (e.g., IgA, IgG) except allergenic epitopes (IgE). In this study, an attempt has been made to understand the relation between primary sequence of epitopes and the class of antibodies generated.
resultsThe dataset used in this study has been derived from Immune Epitope Database and consists of 14725 B-cell epitopes that include 11981 IgG, 2341 IgE, 403 IgA specific epitopes and 22835 non-B-cell epitopes. In order to understand the preference of residues or motifs in these epitopes, we computed and compared amino acid and dipeptide composition of IgG, IgE, IgA inducing epitopes and non-B-cell epitopes. Differences in composition profiles of different classes of epitopes were observed, and few residues were found to be preferred. Based on these observations, we developed models for predicting antibody class-specific B-cell epitopes using various features like amino acid composition, dipeptide composition, and binary profiles. Among these, dipeptide composition-based support vector machine model achieved maximum Matthews correlation coefficient of 0.44, 0.70 and 0.45 for IgG, IgE and IgA specific epitopes respectively. All models were developed on experimentally validated non-redundant dataset and evaluated using five-fold cross validation. In addition, the performance of dipeptide-based model was also evaluated on independent dataset.
conclusionPresent study utilizes the amino acid sequence information for predicting the tendencies of antigens to induce different classes of antibodies. For the first time, in silico models have been developed for predicting B-cell epitopes, which can induce specific class of antibodies. A web service called IgPred has been developed to serve the scientific community. This server will be useful for researchers working in the field of subunit/epitope/peptide-based vaccines and immunotherapy (http://crdd.osdd.net/raghava/igpred/).
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