MULTIPRED: a computational system for prediction of promiscuous HLA binding peptides

被引:117
作者
Zhang, GL
Khan, AM
Srinivasan, KN
August, JT
Brusic, V
机构
[1] Int Infocomm Res, Singapore 119613, Singapore
[2] Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore
[3] Natl Univ Singapore, Dept Biochem, Singapore 117597, Singapore
[4] Johns Hopkins Sch Med, Dept Pharmacol & Mol Sci, Baltimore, MD 21205 USA
[5] John Hopkins Singapore, Div Biomed Sci, Singapore 138669, Singapore
[6] Univ Queensland, Sch Land & Food Sci, Brisbane, Qld 4072, Australia
[7] Univ Queensland, Inst Mol Biosci, Brisbane, Qld 4072, Australia
关键词
D O I
10.1093/nar/gki452
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
MULTIPRED is a web-based computational system for the prediction of peptide binding to multiple molecules ( proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. It uses hidden Markov models and artificial neural network methods as predictive engines. A novel data representation method enables MULTIPRED to predict peptides that promiscuously bind multiple HLA alleles within one HLA supertype. Extensive testing was performed for validation of the prediction models. Testing results show that MULTIPRED is both sensitive and specific and it has good predictive ability ( area under the receiver operating characteristic curve A(ROC) > 0.80). MULTIPRED can be used for the mapping of promiscuous T-cell epitopes as well as the regions of high concentration of these targets termed T-cell epitope hotspots. MULTIPRED is available at http:// antigen.i2r.a-star.edu.sg/ multipred/.
引用
收藏
页码:W172 / W179
页数:8
相关论文
共 24 条
[1]   Discovery of promiscuous HLA-II-restricted T cell epitopes with TEPITOPE [J].
Bian, HJ ;
Hammer, J .
METHODS, 2004, 34 (04) :468-475
[2]   Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications [J].
Brusic, V ;
Bajic, VB ;
Petrovsky, N .
METHODS, 2004, 34 (04) :436-443
[3]   MHCPEP - A DATABASE OF MHC-BINDING PEPTIDES [J].
BRUSIC, V ;
RUDY, G ;
HARRISON, LC .
NUCLEIC ACIDS RESEARCH, 1994, 22 (17) :3663-3665
[4]   Prediction of promiscuous peptides that bind HLA class I molecules [J].
Brusic, V ;
Petrovsky, N ;
Zhang, GL ;
Bajic, VB .
IMMUNOLOGY AND CELL BIOLOGY, 2002, 80 (03) :280-285
[5]   Class II MHC peptide loading by the professionals [J].
Bryant, P ;
Ploegh, H .
CURRENT OPINION IN IMMUNOLOGY, 2004, 16 (01) :96-102
[6]   Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach [J].
Buus, S ;
Lauemoller, SL ;
Worning, P ;
Kesmir, C ;
Frimurer, T ;
Corbet, S ;
Fomsgaard, A ;
Hilden, J ;
Holm, A ;
Brunak, S .
TISSUE ANTIGENS, 2003, 62 (05) :378-384
[7]   Prediction of MHC class I binding peptides, using SVMHC -: art. no. 25 [J].
Dönnes, P ;
Elofsson, A .
BMC BIOINFORMATICS, 2002, 3 (1)
[8]   Quantitative online prediction of peptide binding to the major histocompatibility complex [J].
Hattotuwagama, CK ;
Guan, PP ;
Doytchinova, IA ;
Zygouri, C ;
Flower, DR .
JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2004, 22 (03) :195-207
[9]  
KAST WM, 1994, J IMMUNOL, V152, P3904
[10]   Definition of supertypes for HLA molecules using clustering of specificity matrices [J].
Lund, O ;
Nielsen, M ;
Kesmir, C ;
Petersen, AG ;
Lundegaard, C ;
Worning, P ;
Sylvester-Hvid, C ;
Lamberth, K ;
Roder, G ;
Justesen, S ;
Buus, S ;
Brunak, S .
IMMUNOGENETICS, 2004, 55 (12) :797-810