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Author, Editor(s)

Author(s):

Antes, Iris
Siu, Shirley Weng-In
Lengauer, Thomas

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BibTeX cite key*:

Lengauer2007e

Title

Title*:

DynaPred: A structure and sequence based method for the prediction of MHC class I binding peptide sequence and conformations


AntesSiuLengauer.pdf (157.5 KB)

Journal

Journal Title*:

Bioinformatics

Journal's URL:


Download URL
for the article:

http://bioinformatics.oxfordjournals.org/cgi/reprint/22/14/e16

Language:

English

Publisher

Publisher's
Name:


Publisher's URL:


Publisher's
Address:


ISSN:


Vol, No, pp, Date

Volume*:

22

Number:

14

Publishing Date:

2006

Pages*:

16-24

Number of
VG Pages:

8

Page Start:

16

Page End:

24

Sequence Number:


DOI:

10.1093/bioinformatics/btl216

Note, Abstract, ©

Note:


(LaTeX) Abstract:

Motivation: The binding of endogenous antigenic peptides to MHC class I molecules is an important step during the immunologic response of a host against a pathogen. Thus, various sequence- and structure-based prediction methods have been proposed for this purpose. The sequence-based methods are computationally efficient, but are hampered by the need of sufficient experimental data and do not provide a structural interpretation of their results. The structural methods are data-independent, but are quite time-consuming and thus not suited for screening of whole genomes. Here, we present a new method, which performs sequence-based prediction by incorporating information obtained from molecular modeling. This allows us to perform large databases screening and to provide structural information of the results.
Results: We developed a SVM-trained, quantitative matrix-based method for the prediction of MHC class I binding peptides, in which the features of the scoring matrix are energy terms retrieved from molecular dynamics simulations. At the same time we used the equilibrated structures obtained from the same simulations in a simple and efficient docking procedure. Our method consists of two steps: First, we predict potential binders from sequence data alone and second, we construct protein-peptide complexes for the predicted binders. So far, we tested our approach on the HLA-A0201 allele. We constructed two prediction models, using local, position-dependent (DynaPredPOS) and global, position-independent (DynaPred) features. The former model outperformed the two sequence-based methods used in our evaluation; the latter shows a much higher generalizability towards other alleles than the position-dependent models. The constructed peptide structures can be refined within seconds to structures with an average backbone RMSD of 1.53 Å from the corresponding experimental structures.

URL for the Abstract:

http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/14/e16

Categories,
Keywords:


HyperLinks / References / URLs:


Copyright Message:

Copyright:The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

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BibTeX Entry:

@ARTICLE{Lengauer2007e,
AUTHOR = {Antes, Iris and Siu, Shirley Weng-In and Lengauer, Thomas},
TITLE = {{DynaPred}: A structure and sequence based method for the prediction of {MHC} class I binding peptide sequence and conformations},
JOURNAL = {Bioinformatics},
YEAR = {2006},
NUMBER = {14},
VOLUME = {22},
PAGES = {16--24},
DOI = {10.1093/bioinformatics/btl216},
}


Entry last modified by Anja Becker, 02/07/2008
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Editor(s)
Ruth Schneppen-Christmann
Created
01/10/2007 09:47:58 AM
Revisions
12.
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8.
Editor(s)
Anja Becker
Anja Becker
Iris Antes
Christine Kiesel
Christine Kiesel
Edit Dates
07.02.2008 10:44:10
07.02.2008 10:41:30
04/13/2007 02:41:54 PM
30.03.2007 16:00:00
30.03.2007 15:50:36
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