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PEPOP 2.0: new approaches to mimic non-continuous epitopes
- Source :
- BMC Bioinformatics, BMC Bioinformatics, BioMed Central, 2019, 20 (1), ⟨10.1186/s12859-019-2867-5⟩, BMC Bioinformatics, Vol 20, Iss 1, Pp 1-14 (2019), BMC Bioinformatics, 2019, 20 (1), ⟨10.1186/s12859-019-2867-5⟩
- Publication Year :
- 2019
- Publisher :
- HAL CCSD, 2019.
-
Abstract
- Background Bioinformatics methods are helpful to identify new molecules for diagnostic or therapeutic applications. For example, the use of peptides capable of mimicking binding sites has several benefits in replacing a protein which is difficult to produce, or toxic. Using peptides is less expensive. Peptides are easier to manipulate, and can be used as drugs. Continuous epitopes predicted by bioinformatics tools are commonly used and these sequential epitopes are used as is in further experiments. Numerous discontinuous epitope predictors have been developed but only two bioinformatics tools have been proposed so far to predict peptide sequences: Superficial and PEPOP 2.0. PEPOP 2.0 can generate series of peptide sequences that can replace continuous or discontinuous epitopes in their interaction with their cognate antibody. Results We have developed an improved version of PEPOP (PEPOP 2.0) dedicated to answer to experimentalists’ need for a tool able to handle proteins and to turn them into peptides. The PEPOP 2.0 web site has been reorganized by peptide prediction category and is therefore better formulated to experimental designs. Since the first version of PEPOP, 32 new methods of peptide design were developed. In total, PEPOP 2.0 proposes 35 methods in which 34 deal specifically with discontinuous epitopes, the most represented epitope type in nature. Conclusion Through the presentation of its user-friendly, well-structured new web site conceived in close proximity to experimentalists, we report original methods that show how PEPOP 2.0 can assist biologists in dealing with discontinuous epitopes. Electronic supplementary material The online version of this article (10.1186/s12859-019-2867-5) contains supplementary material, which is available to authorized users.
- Subjects :
- Protein surface
Computer science
IPP
[SDV]Life Sciences [q-bio]
Peptide
medicine.disease_cause
Biochemistry
Epitope
Structural bioinformatics
Epitopes
Mice
0302 clinical medicine
Structural Biology
Peptide design
[SDV.BV] Life Sciences [q-bio]/Vegetal Biology
lcsh:QH301-705.5
chemistry.chemical_classification
0303 health sciences
[SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]
biology
Applied Mathematics
Immunogenicity
Methodology Article
A protein
Antibodies, Monoclonal
Antigenicity
[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]
3. Good health
Computer Science Applications
[SDV] Life Sciences [q-bio]
Molecular mimicry
030220 oncology & carcinogenesis
lcsh:R858-859.7
Discontinuous epitope
DNA microarray
Antibody
Surface protein
Discontinuous and continuous epitope
Computational biology
lcsh:Computer applications to medicine. Medical informatics
03 medical and health sciences
Protein Domains
medicine
Molecule
Animals
[SDV.BV]Life Sciences [q-bio]/Vegetal Biology
Amino Acid Sequence
Binding site
Molecular Biology
030304 developmental biology
Internet
Immune Sera
Computational Biology
Proteins
B-cell epitope
Ag-ab interaction
lcsh:Biology (General)
chemistry
biology.protein
Peptides
Software
Subjects
Details
- Language :
- English
- ISSN :
- 14712105
- Database :
- OpenAIRE
- Journal :
- BMC Bioinformatics, BMC Bioinformatics, BioMed Central, 2019, 20 (1), ⟨10.1186/s12859-019-2867-5⟩, BMC Bioinformatics, Vol 20, Iss 1, Pp 1-14 (2019), BMC Bioinformatics, 2019, 20 (1), ⟨10.1186/s12859-019-2867-5⟩
- Accession number :
- edsair.doi.dedup.....ba880873a479f0eb0607d04645692203