A cohesive and integrated platform for immunogenicity prediction
Methods in Molecular Biology, ISSN: 1064-3745, Vol: 1404, Page: 761-770
2016
- 5Citations
- 22Captures
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Metrics Details
- Citations5
- Citation Indexes5
- CrossRef2
- Captures22
- Readers22
- 22
Book Chapter Description
In silico methods for immunogenicity prediction mine the enormous quantity of data arising from deciphered genomes and proteomes to identify immunogenic proteins. While high and productive immunogenicity is essential for vaccines, therapeutic proteins and monoclonal antibodies should be minimally immunogenic. Here, we present a cohesive platform for immunogenicity and MHC class I and/or II binding affinity prediction. The platform integrates three quasi-independent modular servers: VaxiJen, EpiJen, and EpiTOP. VaxiJen (http://www.ddg-pharmfac.net/vaxijen) predicts immunogenicity of proteins of different origin; EpiJen (http://www.ddg-pharmfac.net/epijen) predicts peptide binding to MHC class I proteins; and EpiTOP (http://www.ddg-pharmfac.net/epitop) predicts peptide binding to MHC class II proteins. The platform is freely accessible and user-friendly. The protocol for immunogenicity prediction is demonstrated by selecting immunogenic proteins from Mycobacterium tuberculosis and predicting how the peptide epitopes within them bind to MHC class I and class II proteins.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84963830956&origin=inward; http://dx.doi.org/10.1007/978-1-4939-3389-1_50; http://www.ncbi.nlm.nih.gov/pubmed/27076336; http://link.springer.com/10.1007/978-1-4939-3389-1_50; https://dx.doi.org/10.1007/978-1-4939-3389-1_50; https://link.springer.com/protocol/10.1007/978-1-4939-3389-1_50
Springer Science and Business Media LLC
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