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Journal of Immunology Research
Volume 2014 (2014), Article ID 768515, 15 pages
Research Article

Model for Vaccine Design by Prediction of B-Epitopes of IEDB Given Perturbations in Peptide Sequence, In Vivo Process, Experimental Techniques, and Source or Host Organisms

1Department of Organic Chemistry II, University of the Basque Country UPV/EHU, 48940 Bilbao, Spain
2Ikerbasque, Basque Foundation for Science, 48011 Bilbao, Spain
3Department of Microbiology and Parasitology, University of Santiago de Compostela (USC), 15782 Santiago de Compostela, Spain

Received 21 August 2013; Accepted 17 November 2013; Published 12 January 2014

Academic Editor: Darren R. Flower

Copyright © 2014 Humberto González-Díaz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Perturbation methods add variation terms to a known experimental solution of one problem to approach a solution for a related problem without known exact solution. One problem of this type in immunology is the prediction of the possible action of epitope of one peptide after a perturbation or variation in the structure of a known peptide and/or other boundary conditions (host organism, biological process, and experimental assay). However, to the best of our knowledge, there are no reports of general-purpose perturbation models to solve this problem. In a recent work, we introduced a new quantitative structure-property relationship theory for the study of perturbations in complex biomolecular systems. In this work, we developed the first model able to classify more than 200,000 cases of perturbations with accuracy, sensitivity, and specificity >90% both in training and validation series. The perturbations include structural changes in >50000 peptides determined in experimental assays with boundary conditions involving >500 source organisms, >50 host organisms, >10 biological process, and >30 experimental techniques. The model may be useful for the prediction of new epitopes or the optimization of known peptides towards computational vaccine design.