An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions

Mette Voldby Larsen; Claus Lundegaard; Kasper Lamberth; Søren Buus; Søren Brunak; Ole Lund; Morten Nielsen

doi:10.1002/eji.200425811

An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions

Mette Voldby Larsen, Claus Lundegaard, Kasper Lamberth, Søren Buus, Søren Brunak, Ole Lund, Morten Nielsen

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

270 Citationer (Scopus)

Abstract

Udgivelsesdato: 2005-Aug

Originalsprog	Engelsk
Tidsskrift	European Journal of Immunology
Vol/bind	35
Udgave nummer	8
Sider (fra-til)	2295-303
Antal sider	8
ISSN	0014-2980
DOI	https://doi.org/10.1002/eji.200425811
Status	Udgivet - 2005

Bibliografisk note

Keywords: ATP-Binding Cassette Transporters; Algorithms; Data Interpretation, Statistical; Epitopes, T-Lymphocyte; Histocompatibility Antigens Class I; Humans; Hydrolysis; Predictive Value of Tests; Proteasome Endopeptidase Complex; Protein Binding; T-Lymphocytes, Cytotoxic

Adgang til dokumentet

10.1002/eji.200425811

Citationsformater

An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions. / Larsen, Mette Voldby; Lundegaard, Claus; Lamberth, Kasper et al.
I: European Journal of Immunology, Bind 35, Nr. 8, 2005, s. 2295-303.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

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title = "An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions",

abstract = "Reverse immunogenetic approaches attempt to optimize the selection of candidate epitopes, and thus minimize the experimental effort needed to identify new epitopes. When predicting cytotoxic T cell epitopes, the main focus has been on the highly specific MHC class I binding event. Methods have also been developed for predicting the antigen-processing steps preceding MHC class I binding, including proteasomal cleavage and transporter associated with antigen processing (TAP) transport efficiency. Here, we use a dataset obtained from the SYFPEITHI database to show that a method integrating predictions of MHC class I binding affinity, TAP transport efficiency, and C-terminal proteasomal cleavage outperforms any of the individual methods. Using an independent evaluation dataset of HIV epitopes from the Los Alamos database, the validity of the integrated method is confirmed. The performance of the integrated method is found to be significantly higher than that of the two publicly available prediction methods BIMAS and SYFPEITHI. To identify 85% of the epitopes in the HIV dataset, 9% and 10% of all possible nonamers in the HIV proteins must be tested when using the BIMAS and SYFPEITHI methods, respectively, for the selection of candidate epitopes. This number is reduced to 7% when using the integrated method. In practical terms, this means that the experimental effort needed to identify an epitope in a hypothetical protein with 85% probability is reduced by 20-30% when using the integrated method.The method is available at http://www.cbs.dtu.dk/services/NetCTL. Supplementary material is available at http://www.cbs.dtu.dk/suppl/immunology/CTL.php.",

author = "Larsen, {Mette Voldby} and Claus Lundegaard and Kasper Lamberth and S{\o}ren Buus and S{\o}ren Brunak and Ole Lund and Morten Nielsen",

note = "Keywords: ATP-Binding Cassette Transporters; Algorithms; Data Interpretation, Statistical; Epitopes, T-Lymphocyte; Histocompatibility Antigens Class I; Humans; Hydrolysis; Predictive Value of Tests; Proteasome Endopeptidase Complex; Protein Binding; T-Lymphocytes, Cytotoxic",

year = "2005",

doi = "10.1002/eji.200425811",

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TY - JOUR

T1 - An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions

AU - Larsen, Mette Voldby

AU - Lundegaard, Claus

AU - Lamberth, Kasper

AU - Buus, Søren

AU - Brunak, Søren

AU - Lund, Ole

AU - Nielsen, Morten

N1 - Keywords: ATP-Binding Cassette Transporters; Algorithms; Data Interpretation, Statistical; Epitopes, T-Lymphocyte; Histocompatibility Antigens Class I; Humans; Hydrolysis; Predictive Value of Tests; Proteasome Endopeptidase Complex; Protein Binding; T-Lymphocytes, Cytotoxic

PY - 2005

Y1 - 2005

N2 - Reverse immunogenetic approaches attempt to optimize the selection of candidate epitopes, and thus minimize the experimental effort needed to identify new epitopes. When predicting cytotoxic T cell epitopes, the main focus has been on the highly specific MHC class I binding event. Methods have also been developed for predicting the antigen-processing steps preceding MHC class I binding, including proteasomal cleavage and transporter associated with antigen processing (TAP) transport efficiency. Here, we use a dataset obtained from the SYFPEITHI database to show that a method integrating predictions of MHC class I binding affinity, TAP transport efficiency, and C-terminal proteasomal cleavage outperforms any of the individual methods. Using an independent evaluation dataset of HIV epitopes from the Los Alamos database, the validity of the integrated method is confirmed. The performance of the integrated method is found to be significantly higher than that of the two publicly available prediction methods BIMAS and SYFPEITHI. To identify 85% of the epitopes in the HIV dataset, 9% and 10% of all possible nonamers in the HIV proteins must be tested when using the BIMAS and SYFPEITHI methods, respectively, for the selection of candidate epitopes. This number is reduced to 7% when using the integrated method. In practical terms, this means that the experimental effort needed to identify an epitope in a hypothetical protein with 85% probability is reduced by 20-30% when using the integrated method.The method is available at http://www.cbs.dtu.dk/services/NetCTL. Supplementary material is available at http://www.cbs.dtu.dk/suppl/immunology/CTL.php.

AB - Reverse immunogenetic approaches attempt to optimize the selection of candidate epitopes, and thus minimize the experimental effort needed to identify new epitopes. When predicting cytotoxic T cell epitopes, the main focus has been on the highly specific MHC class I binding event. Methods have also been developed for predicting the antigen-processing steps preceding MHC class I binding, including proteasomal cleavage and transporter associated with antigen processing (TAP) transport efficiency. Here, we use a dataset obtained from the SYFPEITHI database to show that a method integrating predictions of MHC class I binding affinity, TAP transport efficiency, and C-terminal proteasomal cleavage outperforms any of the individual methods. Using an independent evaluation dataset of HIV epitopes from the Los Alamos database, the validity of the integrated method is confirmed. The performance of the integrated method is found to be significantly higher than that of the two publicly available prediction methods BIMAS and SYFPEITHI. To identify 85% of the epitopes in the HIV dataset, 9% and 10% of all possible nonamers in the HIV proteins must be tested when using the BIMAS and SYFPEITHI methods, respectively, for the selection of candidate epitopes. This number is reduced to 7% when using the integrated method. In practical terms, this means that the experimental effort needed to identify an epitope in a hypothetical protein with 85% probability is reduced by 20-30% when using the integrated method.The method is available at http://www.cbs.dtu.dk/services/NetCTL. Supplementary material is available at http://www.cbs.dtu.dk/suppl/immunology/CTL.php.

U2 - 10.1002/eji.200425811

DO - 10.1002/eji.200425811

M3 - Journal article

C2 - 15997466

SN - 0014-2980

VL - 35

SP - 2295

EP - 2303

JO - European Journal of Immunology

JF - European Journal of Immunology

IS - 8

ER -