Literature DB >> 34918258

Bioinformatic Techniques for Vaccine Development: Epitope Prediction and Structural Vaccinology.

Peter McCaffrey1.   

Abstract

Structural vaccinology involves characterizing the interactions between an antigen and antibodies or host immune receptors. Central to this is the task of epitope prediction, which involves describing the binding affinity and interactions of a given peptide typically to the major histocompatibility complex in the case of T-cells or to the antibodies in the case of B-cells. Several computational models exist for this purpose which we will review here. Generally, epitope predictions for MHC-I and MHC-II are substantially different tasks as well as epitope prediction for continuous versus discontinuous B-cell epitopes. Overall, these models suffer from overprediction of epitopes although general themes support both the use of neural networks as well as the incorporation of more abundant and more varied experimental annotation into model training as valuable in improving predictive performance.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Epitope prediction; Neural network; Position-specific scoring matrix; Structural vaccinology

Mesh:

Substances:

Year:  2022        PMID: 34918258     DOI: 10.1007/978-1-0716-1892-9_21

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  16 in total

1.  Cutting edge: TCR contacts as anchors: effects on affinity and HLA-DM stability.

Authors:  Matthew W Anderson; Jack Gorski
Journal:  J Immunol       Date:  2003-12-01       Impact factor: 5.422

2.  Prediction of MHC class I binding peptides using profile motifs.

Authors:  Pedro A Reche; John-Paul Glutting; Ellis L Reinherz
Journal:  Hum Immunol       Date:  2002-09       Impact factor: 2.850

3.  Efficient peptide-MHC-I binding prediction for alleles with few known binders.

Authors:  Laurent Jacob; Jean-Philippe Vert
Journal:  Bioinformatics       Date:  2007-12-14       Impact factor: 6.937

Review 4.  An overview of bioinformatics tools for epitope prediction: implications on vaccine development.

Authors:  Ruth E Soria-Guerra; Ricardo Nieto-Gomez; Dania O Govea-Alonso; Sergio Rosales-Mendoza
Journal:  J Biomed Inform       Date:  2014-11-10       Impact factor: 6.317

5.  Improved peptide-MHC class II interaction prediction through integration of eluted ligand and peptide affinity data.

Authors:  Christian Garde; Sri H Ramarathinam; Emma C Jappe; Morten Nielsen; Jens V Kringelum; Thomas Trolle; Anthony W Purcell
Journal:  Immunogenetics       Date:  2019-06-10       Impact factor: 2.846

6.  An automated benchmarking platform for MHC class II binding prediction methods.

Authors:  Massimo Andreatta; Thomas Trolle; Zhen Yan; Jason A Greenbaum; Bjoern Peters; Morten Nielsen
Journal:  Bioinformatics       Date:  2018-05-01       Impact factor: 6.937

7.  HLA-DM constrains epitope selection in the human CD4 T cell response to vaccinia virus by favoring the presentation of peptides with longer HLA-DM-mediated half-lives.

Authors:  Liusong Yin; J Mauricio Calvo-Calle; Omar Dominguez-Amorocho; Lawrence J Stern
Journal:  J Immunol       Date:  2012-09-10       Impact factor: 5.422

8.  Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes.

Authors:  Weilong Zhao; Xinwei Sher
Journal:  PLoS Comput Biol       Date:  2018-11-08       Impact factor: 4.475

Review 9.  Structural Vaccinology for Viral Vaccine Design.

Authors:  Mohd Ishtiaq Anasir; Chit Laa Poh
Journal:  Front Microbiol       Date:  2019-04-16       Impact factor: 5.640

10.  EpiJen: a server for multistep T cell epitope prediction.

Authors:  Irini A Doytchinova; Pingping Guan; Darren R Flower
Journal:  BMC Bioinformatics       Date:  2006-03-13       Impact factor: 3.169

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