PEPOP: Computational design of immunogenic peptides
Open Access
- 30 January 2008
- journal article
- Published by Springer Science and Business Media LLC in BMC Bioinformatics
- Vol. 9 (1), 71
- https://doi.org/10.1186/1471-2105-9-71
Abstract
Background Most methods available to predict protein epitopes are sequence based. There is a need for methods using 3D information for prediction of discontinuous epitopes and derived immunogenic peptides. Results PEPOP uses the 3D coordinates of a protein both to predict clusters of surface accessible segments that might correspond to epitopes and to design peptides to be used to raise antibodies that target the cognate antigen at specific sites. To verify the ability of PEPOP to identify epitopes, 13 crystallographically defined epitopes were compared with PEPOP clusters: specificity ranged from 0.75 to 1.00, sensitivity from 0.33 to 1.00, and the positive predictive value from 0.19 to 0.89. Comparison of these results with those obtained with two other prediction algorithms showed comparable specificity and slightly better sensitivity and PPV. To prove the capacity of PEPOP to predict immunogenic peptides that induce protein cross-reactive antibodies, several peptides were designed from the 3D structure of model antigens (IA-2, TPO, and IL8) and chemically synthesized. The reactivity of the resulting anti-peptides antibodies with the cognate antigens was measured. In 80% of the cases (four out of five peptides), the flanking protein sequence process (sequence-based) of PEPOP successfully proposed peptides that elicited antibodies cross-reacting with the parent proteins. Polyclonal antibodies raised against peptides designed from amino acids which are spatially close in the protein, but separated in the sequence, could also be obtained, although they were much less reactive. The capacity of PEPOP to design immunogenic peptides that induce antibodies suitable for a sandwich capture assay was also demonstrated. Conclusion PEPOP has the potential to guide experimentalists that want to localize an epitope or design immunogenic peptides for raising antibodies which target proteins at specific sites. More successful predictions of immunogenic peptides were obtained when a peptide was continuous as compared with peptides corresponding to discontinuous epitopes. PEPOP is available for use at http://diagtools.sysdiag.cnrs.fr/PEPOP/.Keywords
This publication has 66 references indexed in Scilit:
- The MEPS server for identifying protein conformational epitopesBMC Bioinformatics, 2007
- Prediction of residues in discontinuous B‐cell epitopes using protein 3D structuresProtein Science, 2006
- Machine learning approaches for prediction of linear B‐cell epitopes on proteinsJournal of Molecular Recognition, 2006
- Benchmarking B cell epitope prediction: Underperformance of existing methodsProtein Science, 2005
- Antigenicity and Immunogenicity of Synthetic PeptidesBiologicals, 2001
- The 2.5 Å resolution structure of the Jel42 Fab fragment/HPr complex 1 1Edited by I. A. WilsonJournal of Molecular Biology, 1998
- USE OF HOMOLOGY MODELING IN CONJUNCTION WITH SITE-DIRECTED MUTAGENESIS FOR ANALYSIS OF STRUCTURE-FUNCTION RELATIONSHIPS OF MAMMALIAN CYTOCHROMES P450Life Sciences, 1997
- The Crystal Structure of the Antibody N10-Staphylococcal Nuclease Complex at 2.9 Å ResolutionJournal of Molecular Biology, 1995
- Crystal structures of two mutant neuraminidase-antibody complexes with amino acid substitutions in the interfaceJournal of Molecular Biology, 1992
- Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical featuresPeptide Science, 1983