Computational characterization and epitope prediction for Bet-v1 like protein of Cannabis sativa
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Biology
- Keywords
- allergen, epitope prediction, Structure modeling, phosphorylation, Cannabis sativa
- Copyright
- © 2016 Basharat
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2016. Computational characterization and epitope prediction for Bet-v1 like protein of Cannabis sativa. PeerJ Preprints 4:e2305v1 https://doi.org/10.7287/peerj.preprints.2305v1
Abstract
Cannabis sativa encodes a Bet-v1 like protein is an allergen and a causuative agent of pollen allergy. Multiple sequence alignment of this protein revealed conserved residues in Betv1 domain. Identification of linear epitopes of this protein was done after preliminary bioinformatics characterization and structure prediction. Structure prediction was done using Modeller software and minimized using Swiss PDBViewer. Six linear epitopes were then, predicted using EMBOSS antigenic program. Phylogenetic analysis of Bet-v1 with other sequences demonstrated divergence patterns with allergens of other species but revealed conserved residues in allergenic epitopes. This study can serve as an informational aid in the development of hypoallergenic vaccine for Cannabis sativa allergy.
Author Comment
This is a preprint submission to PeerJ Preprints. This preprint version may contain grammatical and proofreading mistakes. Errors and omissions excepted.