Pepitope: epitope mapping from affinity-selected peptides
Identifying the epitope to which an antibody binds is central for many immunological applications such as drug design and vaccine development. The Pepitope server is a web-based tool that aims at predicting discontinuous epitopes based on a set of peptides that were affinity-selected against a monoc...
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Published in | Bioinformatics Vol. 23; no. 23; pp. 3244 - 3246 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article Web Resource |
Language | English |
Published |
Oxford
Oxford University Press
01.12.2007
Oxford Publishing Limited (England) |
Subjects | |
Online Access | Get full text |
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Summary: | Identifying the epitope to which an antibody binds is central for many immunological applications such as drug design and vaccine development. The Pepitope server is a web-based tool that aims at predicting discontinuous epitopes based on a set of peptides that were affinity-selected against a monoclonal antibody of interest. The server implements three different algorithms for epitope mapping: PepSurf, Mapitope, and a combination of the two. The rationale behind these algorithms is that the set of peptides mimics the genuine epitope in terms of physicochemical properties and spatial organization. When the three-dimensional (3D) structure of the antigen is known, the information in these peptides can be used to computationally infer the corresponding epitope. A user-friendly web interface and a graphical tool that allows viewing the predicted epitopes were developed. Pepitope can also be applied for inferring other types of protein–protein interactions beyond the immunological context, and as a general tool for aligning linear sequences to a 3D structure. Availability: http://pepitope.tau.ac.il/ Contact: talp@post.tau.ac.il |
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Bibliography: | istex:15C902BA76D1A6AB92574326139F3AECB485E127 To whom correspondence should be addressed. ark:/67375/HXZ-CF72SDWL-3 Associate Editor: Alfonso Valencia ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 1367-4803 1460-2059 1367-4811 |
DOI: | 10.1093/bioinformatics/btm493 |