Skip Navigation

This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (131)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Brusic, V.
Right arrow Articles by Harrison, L.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Brusic, V.
Right arrow Articles by Harrison, L.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Bioinformatics, Vol 14, 121-130, Copyright © 1998 by Oxford University Press

ARTICLES

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

V Brusic, G Rudy, G Honeyman, J Hammer and L Harrison
The Walter and Eliza Hall Institute of Medical Research, PO Royal Melbourne Hospital, Victoria, Australia.

MOTIVATION: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. RESULTS: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification . This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA- DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binders were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotherapeutic peptides. AVAILABILITY: Software and data are available from the authors upon request. CONTACT: vladimir@wehi.edu. au
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BioinformaticsHome page
D. S. DeLuca, B. Eiz-Vesper, N. Ladas, B. A.-M. Khattab, and R. Blasczyk
High-throughput minor histocompatibility antigen prediction
Bioinformatics, September 15, 2009; 25(18): 2411 - 2417.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
C. Lundegaard, O. Lund, C. Kesmir, S. Brunak, and M. Nielsen
Modeling the adaptive immune system: predictions and simulations
Bioinformatics, December 15, 2007; 23(24): 3265 - 3275.
[Abstract] [Full Text] [PDF]

Home page
 Brief BioinformHome page
J. C. Tong, T. W. Tan, and S. Ranganathan
Methods and protocols for prediction of immunogenic epitopes
Brief Bioinform, March 1, 2007; 8(2): 96 - 108.
[Abstract] [Full Text] [PDF]

Home page
 J. Immunol.Home page
D. Ito, A. Albers, Y. X. Zhao, C. Visus, E. Appella, T. L. Whiteside, and A. B. DeLeo
The Wild-Type Sequence (wt) p5325-35 Peptide Induces HLA-DR7 and HLA-DR11-Restricted CD4+ Th Cells Capable of Enhancing the Ex Vivo Expansion and Function of Anti-wt p53264-272 Peptide CD8+ T Cells
J. Immunol., November 15, 2006; 177(10): 6795 - 6803.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
S. T. Chang, D. Ghosh, D. E. Kirschner, and J. J. Linderman
Peptide length-based prediction of peptide-MHC class II binding
Bioinformatics, November 15, 2006; 22(22): 2761 - 2767.
[Abstract] [Full Text] [PDF]

Home page
 Mol. Cell. ProteomicsHome page
L. Zhang, C. Shao, D. Zheng, and Y. Gao
An Integrated Machine Learning System to Computationally Screen Protein Databases for Protein Binding Peptide Ligands
Mol. Cell. Proteomics, July 1, 2006; 5(7): 1224 - 1232.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
P. Donnes and O. Kohlbacher
SVMHC: a server for prediction of MHC-binding peptides.
Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W194 - W197.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
S. Zhu, K. Udaka, J. Sidney, A. Sette, K. F. Aoki-Kinoshita, and H. Mamitsuka
Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules
Bioinformatics, July 1, 2006; 22(13): 1648 - 1655.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
J. C. Tong, G. L. Zhang, T. W. Tan, J. T. August, V. Brusic, and S. Ranganathan
Prediction of HLA-DQ3.2{beta} Ligands: evidence of multiple registers in class II binding peptides
Bioinformatics, May 15, 2006; 22(10): 1232 - 1238.
[Abstract] [Full Text] [PDF]

Home page
 Mol. Cell. ProteomicsHome page
A. W. Purcell and J. J. Gorman
Immunoproteomics: Mass Spectrometry-based Methods to Study the Targets of the Immune Response
Mol. Cell. Proteomics, March 1, 2004; 3(3): 193 - 208.
[Abstract] [Full Text] [PDF]

Home page
 Cancer Res.Home page
K. Chikamatsu, A. Albers, J. Stanson, W. W. Kwok, E. Appella, T. L. Whiteside, and A. B. DeLeo
p53110-124-specific Human CD4+ T-helper Cells Enhance in Vitro Generation and Antitumor Function of Tumor-reactive CD8+ T Cells
Cancer Res., July 1, 2003; 63(13): 3675 - 3681.
[Abstract] [Full Text] [PDF]

Home page
 Int ImmunolHome page
M. Tanaka, S. Ozaki, D. Kawabata, M. Kishimura, F. Osakada, M. Okubo, M. Murakami, K. Nakao, and T. Mimori
Potential preventive effects of follistatin-related protein/TSC-36 on joint destruction and antagonistic modulation of its autoantibodies in rheumatoid arthritis
Int. Immunol., January 1, 2003; 15(1): 71 - 77.
[Abstract] [Full Text] [PDF]

Home page
 J. Immunol.Home page
K. Udaka, H. Mamitsuka, Y. Nakaseko, and N. Abe
Empirical Evaluation of a Dynamic Experiment Design Method for Prediction of MHC Class I-Binding Peptides
J. Immunol., November 15, 2002; 169(10): 5744 - 5753.
[Abstract] [Full Text] [PDF]

Home page
 J. Immunol.Home page
T. G. Forsthuber, C. L. Shive, W. Wienhold, K. de Graaf, E. G. Spack, R. Sublett, A. Melms, J. Kort, M. K. Racke, and R. Weissert
T Cell Epitopes of Human Myelin Oligodendrocyte Glycoprotein Identified in HLA-DR4 (DRB1*0401) Transgenic Mice Are Encephalitogenic and Are Presented by Human B Cells
J. Immunol., December 15, 2001; 167(12): 7119 - 7125.
[Abstract] [Full Text] [PDF]

Home page
 J. Immunol.Home page
Y. Zhao, B. Gran23, C. Pinilla, S. Markovic-Plese, B. Hemmer, A. Tzou, L. W. Whitney, W. E. Biddison, R. Martin, and R. Simon
Combinatorial Peptide Libraries and Biometric Score Matrices Permit the Quantitative Analysis of Specific and Degenerate Interactions Between Clonotypic TCR and MHC Peptide Ligands
J. Immunol., August 15, 2001; 167(4): 2130 - 2141.
[Abstract] [Full Text] [PDF]

Home page
 Cancer Res.Home page
H. M. Zarour, W. J. Storkus, V. Brusic, E. Williams, and J. M. Kirkwood
NY-ESO-1 Encodes DRB1*0401-restricted Epitopes Recognized by Melanoma-reactive CD4+ T Cells
Cancer Res., September 1, 2000; 60(17): 4946 - 4952.
[Abstract] [Full Text]

Home page
 Proc. Natl. Acad. Sci. USAHome page
H. M. Zarour, J. M. Kirkwood, L. S. Kierstead, W. Herr, V. Brusic, C. L. Slingluff Jr., J. Sidney, A. Sette, and W. J. Storkus
Melan-A/MART-151-73 represents an immunogenic HLA-DR4-restricted epitope recognized by melanoma-reactive CD4+ T cells
PNAS, January 4, 2000; 97(1): 400 - 405.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.