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
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 variat...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Immunology Research |
| Online Access: | http://dx.doi.org/10.1155/2014/768515 |
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| author | Humberto González-Díaz Lázaro G. Pérez-Montoto Florencio M. Ubeira |
| author_facet | Humberto González-Díaz Lázaro G. Pérez-Montoto Florencio M. Ubeira |
| author_sort | Humberto González-Díaz |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-aa59e21544ed49968c8c63ae411b7c21 |
| institution | Kabale University |
| issn | 2314-8861 2314-7156 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Immunology Research |
| spelling | doaj-art-aa59e21544ed49968c8c63ae411b7c212025-02-03T07:26:08ZengWileyJournal of Immunology Research2314-88612314-71562014-01-01201410.1155/2014/768515768515Model for Vaccine Design by Prediction of B-Epitopes of IEDB Given Perturbations in Peptide Sequence, In Vivo Process, Experimental Techniques, and Source or Host OrganismsHumberto González-Díaz0Lázaro G. Pérez-Montoto1Florencio M. Ubeira2Department of Organic Chemistry II, University of the Basque Country UPV/EHU, 48940 Bilbao, SpainDepartment of Microbiology and Parasitology, University of Santiago de Compostela (USC), 15782 Santiago de Compostela, SpainDepartment of Microbiology and Parasitology, University of Santiago de Compostela (USC), 15782 Santiago de Compostela, SpainPerturbation 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.http://dx.doi.org/10.1155/2014/768515 |
| spellingShingle | Humberto González-Díaz Lázaro G. Pérez-Montoto Florencio M. Ubeira 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 Journal of Immunology Research |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| url | http://dx.doi.org/10.1155/2014/768515 |
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