In Silico Identification of B-Cell Epitopes of Leishmania infantum Recombinant Histone Shared with Human Sera Stably Living in Area Where Leishmania Species Does Perpetuate

Identification of B-cell epitopes is a fundamental step for development of epitope-based vaccines, therapeutic antibodies, and diagnostic tools. Epitope-based antibodies are currently the most promising class of biopharmaceuticals. In the last decade, in-depth in silico analysis and categorization of the experimentally identified epitopes stimulated development of algorithms for epitope prediction. Recently, various in silico tools are employed in attempts to predict B-cell epitopes based on sequence and/or structural data. The main objective of epitope identification is to replace an antigen in the immunization, antibody production, and serodiagnosis. The accurate identification of B-cell epitopes still presents major challenges for immunologists. Advances in B-cell epitope mapping and computational prediction have yielded molecular insights into the process of biorecognition and formation of antigen-antibody complex, which may help to localize B-cell epitopes more precisely. In this paper, we have comprehensively reviewed state-of-the-art experimental methods for B-cell epitope identification, existing databases for epitopes, and novel in silico resources and prediction tools available online. We have also elaborated new trends in the antibody-based epitope prediction. The aim of this review is to assist researchers in identification of B-cell epitopes.

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Serodiagnosis of tuberculosis using nine in silico predicted B-cell epitopes peptides derived from Mycobacterium tuberculosis proteins

International Journal of Infectious Diseases ◽

10.1016/j.ijid.2010.02.407 ◽

2010 ◽

Vol 14 ◽

pp. e354

Author(s):

L. Baassii ◽

K. Sadki ◽

F. Seghrouchni ◽

S. Contini ◽

W. Cherki ◽

...

Keyword(s):

Mycobacterium Tuberculosis ◽

B Cell ◽

In Silico ◽

B Cell Epitopes

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Immuno-informatics Design of a Multimeric Epitope Peptide Based Vaccine Targeting SARS-CoV-2 Spike Glycoprotein

10.1101/2020.07.30.228221 ◽

2020 ◽

Author(s):

Onyeka S. Chukwudozie ◽

Clive M. Gray ◽

Tawakalt A. Fagbayi ◽

Rebecca C. Chukwuanukwu ◽

Victor O. Oyebanji ◽

...

Keyword(s):

T Cell ◽

B Cell ◽

In Silico ◽

Peptide Vaccine ◽

Spike Protein ◽

Cell Mediated Immunity ◽

Epitope Peptide ◽

Mhc I ◽

B Cell Epitopes ◽

Antibody Recognition

ABSTRACTDeveloping an efficacious vaccine to SARS-CoV-2 infection is critical to stem COVID-19 fatalities and providing the global community with immune protection. We have used a bioinformatic approach to aid in the design of an epitope peptide-based vaccine against the spike protein of the virus. Five antigenic B cell epitopes with viable antigenicity and a total of 27 discontinuous B cell epitopes were mapped out structurally in the spike protein for antibody recognition. We identified eight CD8+ T cell 9-mers along with 12 CD4+ T cell 14-15-mer as promising candidate epitopes putatively restricted by a large number of MHC-I and II alleles respectively. We used this information to construct an in silico chimeric peptide vaccine whose translational rate was highly expressed when cloned in pET28a (+) vector. The vaccine construct was predicted to elicit high antigenicity and cell-mediated immunity when given as a homologous prime-boost, with triggering of toll-like receptor 5 by the adjuvant linker. The vaccine was characterized by an increase in IgM and IgG and an array of Th1 and Th2 cytokines. Upon in silico challenge with SARS-CoV-2, there was a decrease in antigen levels using our immune simulations. We therefore propose that potential vaccine designs consider this approach.

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In silico prediction of B cell epitopes of the hemolysis-associated protein 1 for vaccine design against leptospirosis

Journal of Current Biomedical Reports ◽

10.52547/jcbior.1.1.32 ◽

2020 ◽

Vol 1 (1) ◽

pp. 32-37

Author(s):

Sakineh Poorhosein Fookolaee ◽

Somayyeh Talebishelimaki ◽

Mohammad Taha Saadati Rad ◽

Mostafa Akbarian Rokni

Keyword(s):

B Cell ◽

In Silico ◽

Vaccine Design ◽

In Silico Prediction ◽

B Cell Epitopes

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Molecular cloning, expression, purification and in silico epitope prediction of cobalamin-independent methionine synthase (Mor a 2), as a novel allergen from Morus alba pollen

Archives of Medical Science ◽

10.5114/aoms/136322 ◽

2021 ◽

Author(s):

Yunus AKSÜT

Keyword(s):

T Cell ◽

B Cell ◽

In Silico ◽

Allergic Diseases ◽

Structural Features ◽

Morus Alba ◽

Methionine Synthase ◽

Antigenic Peptides ◽

T Cell Epitopes ◽

B Cell Epitopes

IntroductionMorus alba (white mulberry) pollen is an aero-allergen source that can trigger allergic diseases. Cobalamin-independent methionine synthase (MetE) in M. alba pollen has been proved to be one of the major allergens for some patients living in Istanbul (Turkey). The aim of the present study was the recombinant production and identification of MetE (Mor a 2), a novel allergen from M. alba pollen. The IgE binding reactivity of rMor a 2 produced for the first time was evaluated and some structural features were investigated by in silico methods to better understand its immunogenicity.Material and methodsThe gene encoding Mor a 2 was cloned in fission yeast, Schizosaccharomyces pombe ura4-D18h- strain, using pSLF1073 vector. This is the first report of the production of recombinant pollen allergen in S. pombe. After the purification, immunoreactivity of rMor a 2 was confirmed by immunoblotting using sera of patient allergic to M. alba pollen. Besides, B-cell epitopes of rMor a 2 were predicted using various bioinformatic tools, namely Bioinformatics Predicted Antigenic Peptides, BepiPred 2.0 and Immune Epitope Database whereas T-cell epitopes were estimated using NetMHCIIpan-3.2 and NetMHCII 2.3 servers.ResultsThe immunoblotting analysis yielded 11 of 11 positive reactions to rMor a 2. In silico predictions exerted seven B-cell epitopes (22-33, 384-394, 407-423, 547-553, 571-577, 671-678, 736-741) and seven T-cell epitopes (54-62, 161-170, 197-205, 347-358, 622-630, 657-665, 756-764).ConclusionsThese findings may help the use of rMor a 2 in the diagnosis and treatment of allergic diseases associated with M. alba and/or MetE.

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