Abstract
Identification of T-cell epitopes (parts of antigenic proteins to which the T-cells receptor respond) is important in the development of vaccines and immunotherapeutics. We developed MULTIPRED1 (http://antigen.i2r.astar.edu.sg/ multipred1/), a web-based computational system for prediction of peptides (protein fragments) that bind multiple related human leukocyte antigen (HLA) molecules (the human major histocompatibility complex - MHC molecules). In this paper, the performance of MULTIPRED1 in predicting individual 9-mer binders to HLA-A2 and A3 molecules was compared with five other publicly available prediction tools, SFYPEITHI, BIMAS, SMM, RANKPEP and SVMHC. The results show that MULTIPRED1 is both sensitive and specific for prediction of binders to individual HLA alleles and demonstrates comparable accuracy as those of other prediction tools. Majority voting was applied to combine the strength of the three prediction models of MULTIPRED1 and results indicate that better prediction performance can be achieved. MULTIPRED1 is useful in the selection of key antigenic regions to minimize the number of experiments required for mapping of promiscuous T-cell epitopes.
| Original language | English |
|---|---|
| Title of host publication | ICBPE 2006 - Proceedings of the 2006 International Conference on Biomedical and Pharmaceutical Engineering |
| Pages | 307-313 |
| Number of pages | 7 |
| DOIs | |
| Publication status | Published - 2006 |
| Externally published | Yes |
| Event | ICBPE 2006 - 2006 International Conference on Biomedical and Pharmaceutical Engineering - Singapore, Singapore Duration: Dec 11 2006 → Dec 14 2006 |
Other
| Other | ICBPE 2006 - 2006 International Conference on Biomedical and Pharmaceutical Engineering |
|---|---|
| Country | Singapore |
| City | Singapore |
| Period | 12/11/06 → 12/14/06 |
Fingerprint
Keywords
- MHC binding peptide
- MULTIPRED1
- T-cell epitope
ASJC Scopus subject areas
- Biomedical Engineering
- Pharmacology (medical)
- Pharmacology, Toxicology and Pharmaceutics(all)
Cite this
Performance evaluation of MULTIEPD1 on prediction of MHC class i binders. / Zhang, Guang Lan; Kwoh, Chee Keong; August, J. Thomas; Brusic, Vladimir.
ICBPE 2006 - Proceedings of the 2006 International Conference on Biomedical and Pharmaceutical Engineering. 2006. p. 307-313 4155914.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Performance evaluation of MULTIEPD1 on prediction of MHC class i binders
AU - Zhang, Guang Lan
AU - Kwoh, Chee Keong
AU - August, J. Thomas
AU - Brusic, Vladimir
PY - 2006
Y1 - 2006
N2 - Identification of T-cell epitopes (parts of antigenic proteins to which the T-cells receptor respond) is important in the development of vaccines and immunotherapeutics. We developed MULTIPRED1 (http://antigen.i2r.astar.edu.sg/ multipred1/), a web-based computational system for prediction of peptides (protein fragments) that bind multiple related human leukocyte antigen (HLA) molecules (the human major histocompatibility complex - MHC molecules). In this paper, the performance of MULTIPRED1 in predicting individual 9-mer binders to HLA-A2 and A3 molecules was compared with five other publicly available prediction tools, SFYPEITHI, BIMAS, SMM, RANKPEP and SVMHC. The results show that MULTIPRED1 is both sensitive and specific for prediction of binders to individual HLA alleles and demonstrates comparable accuracy as those of other prediction tools. Majority voting was applied to combine the strength of the three prediction models of MULTIPRED1 and results indicate that better prediction performance can be achieved. MULTIPRED1 is useful in the selection of key antigenic regions to minimize the number of experiments required for mapping of promiscuous T-cell epitopes.
AB - Identification of T-cell epitopes (parts of antigenic proteins to which the T-cells receptor respond) is important in the development of vaccines and immunotherapeutics. We developed MULTIPRED1 (http://antigen.i2r.astar.edu.sg/ multipred1/), a web-based computational system for prediction of peptides (protein fragments) that bind multiple related human leukocyte antigen (HLA) molecules (the human major histocompatibility complex - MHC molecules). In this paper, the performance of MULTIPRED1 in predicting individual 9-mer binders to HLA-A2 and A3 molecules was compared with five other publicly available prediction tools, SFYPEITHI, BIMAS, SMM, RANKPEP and SVMHC. The results show that MULTIPRED1 is both sensitive and specific for prediction of binders to individual HLA alleles and demonstrates comparable accuracy as those of other prediction tools. Majority voting was applied to combine the strength of the three prediction models of MULTIPRED1 and results indicate that better prediction performance can be achieved. MULTIPRED1 is useful in the selection of key antigenic regions to minimize the number of experiments required for mapping of promiscuous T-cell epitopes.
KW - MHC binding peptide
KW - MULTIPRED1
KW - T-cell epitope
UR - http://www.scopus.com/inward/record.url?scp=46249103826&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=46249103826&partnerID=8YFLogxK
U2 - 10.1109/ICBPE.2006.348605
DO - 10.1109/ICBPE.2006.348605
M3 - Conference contribution
SN - 8190426249
SN - 9788190426244
SP - 307
EP - 313
BT - ICBPE 2006 - Proceedings of the 2006 International Conference on Biomedical and Pharmaceutical Engineering
ER -