CIVETAN   23983
CENTRO DE INVESTIGACION VETERINARIA DE TANDIL
Unidad Ejecutora - UE
artículos
Título:
QSPR-Perturbation Models for the Prediction of B-Epitopes from Immune Epitope Database: A Potentially Valuable Route for Predicting ?In Silico? New Optimal Peptide Sequences and/or Boundary Conditions for Vaccine Development
Autor/es:
FLORENCIO M. UBEIRA; ESPERANZA PANIAGUA; SEVERO VÁZQUEZ PRIETO; HUMBERTO GONZÁLEZ-DÍAZ
Revista:
INTERNATIONAL JOURNAL OF PEPTIDE RESEARCH AND THERAPEUTICS
Editorial:
SPRINGER
Referencias:
Año: 2016 vol. 22 p. 445 - 450
ISSN:
1573-3149
Resumen:
In the present study, three different physicochemical molecular properties for peptides were calculated using the program MARCH-INSIDE: atomic polarizability, partition coefficient, and polarity. These measures were used as input parameters of a linear discriminant analysis (LDA) in order to develop three different quantitative structure?property relationship (QSPR)-perturbation models for the prediction of B-epitopes reported in the immune epitope database (IEDB) given perturbations in peptide sequence, in vivo process, experimental techniques, and source or host organisms. The accuracy, sensitivity and specificity of the models were[90 % for both training andcross-validation series. The statistical parameters of the models were compared to the results achieved with the electronegativity QSPR-perturbation model previously reported by Gonza´lez-Dı´az et al. (J Immunol Res. doi:10.1155/2014/768515, 2014). The results indicate that this type of approach may constitute a potentially valuable route for predicting ??in silico?? new optimal peptide sequences and/or boundary conditions for vaccine development.