A computational resource for the prediction of peptide binding to Indian rhesus macaque MHC class I molecules

B. Peters, H. H. Bui, J. Sidney, Z. Weng, J. T. Loffredo, David Watkins, B. R. Mothé, A. Sette

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Non-human primates, in general, and Indian rhesus macaques, specifically, play an important role in the development and testing of vaccines and diagnostics destined for human use. To date, several frequently expressed macaque MHC molecules have been identified and their binding specificities characterized in detail. Here, we report the development of computational algorithms to predict peptide binding and potential T cell epitopes for the common MHC class I alleles Mamu-A*01, -A*02, -A*11, -B*01 and -B*17, which cover approximately two thirds of the captive Indian rhesus macaque populations. We validated this method utilizing an SIV derived data set encompassing 59 antigenic peptides. Of all peptides contained in the SIV proteome, the 2.4% scoring highest in the prediction contained 80% of the antigenic peptides. The method was implemented in a freely accessible and user friendly website at www.mamu.liai.org. Thus, we anticipate that our approach can be utilized to rapidly and efficiently identify CD8+ T cell epitopes recognized by rhesus macaques and derived from any pathogen of interest.

Original languageEnglish
Pages (from-to)5212-5224
Number of pages13
JournalVaccine
Volume23
Issue number45
DOIs
StatePublished - Nov 1 2005
Externally publishedYes

Fingerprint

Macaca mulatta
peptides
Peptides
T-Lymphocyte Epitopes
prediction
epitopes
T-lymphocytes
Macaca
Proteome
proteome
Primates
Vaccines
Alleles
vaccines
alleles
pathogens
methodology
Population
testing

Keywords

  • Epitope
  • Indian rhesus macaque
  • MHC

ASJC Scopus subject areas

  • Immunology
  • Microbiology
  • Virology
  • Infectious Diseases
  • Public Health, Environmental and Occupational Health
  • veterinary(all)

Cite this

A computational resource for the prediction of peptide binding to Indian rhesus macaque MHC class I molecules. / Peters, B.; Bui, H. H.; Sidney, J.; Weng, Z.; Loffredo, J. T.; Watkins, David; Mothé, B. R.; Sette, A.

In: Vaccine, Vol. 23, No. 45, 01.11.2005, p. 5212-5224.

Research output: Contribution to journalArticle

Peters, B, Bui, HH, Sidney, J, Weng, Z, Loffredo, JT, Watkins, D, Mothé, BR & Sette, A 2005, 'A computational resource for the prediction of peptide binding to Indian rhesus macaque MHC class I molecules', Vaccine, vol. 23, no. 45, pp. 5212-5224. https://doi.org/10.1016/j.vaccine.2005.07.086
Peters, B. ; Bui, H. H. ; Sidney, J. ; Weng, Z. ; Loffredo, J. T. ; Watkins, David ; Mothé, B. R. ; Sette, A. / A computational resource for the prediction of peptide binding to Indian rhesus macaque MHC class I molecules. In: Vaccine. 2005 ; Vol. 23, No. 45. pp. 5212-5224.
@article{4d96ab59ebf94035a8472fe4bb45176b,
title = "A computational resource for the prediction of peptide binding to Indian rhesus macaque MHC class I molecules",
abstract = "Non-human primates, in general, and Indian rhesus macaques, specifically, play an important role in the development and testing of vaccines and diagnostics destined for human use. To date, several frequently expressed macaque MHC molecules have been identified and their binding specificities characterized in detail. Here, we report the development of computational algorithms to predict peptide binding and potential T cell epitopes for the common MHC class I alleles Mamu-A*01, -A*02, -A*11, -B*01 and -B*17, which cover approximately two thirds of the captive Indian rhesus macaque populations. We validated this method utilizing an SIV derived data set encompassing 59 antigenic peptides. Of all peptides contained in the SIV proteome, the 2.4{\%} scoring highest in the prediction contained 80{\%} of the antigenic peptides. The method was implemented in a freely accessible and user friendly website at www.mamu.liai.org. Thus, we anticipate that our approach can be utilized to rapidly and efficiently identify CD8+ T cell epitopes recognized by rhesus macaques and derived from any pathogen of interest.",
keywords = "Epitope, Indian rhesus macaque, MHC",
author = "B. Peters and Bui, {H. H.} and J. Sidney and Z. Weng and Loffredo, {J. T.} and David Watkins and Moth{\'e}, {B. R.} and A. Sette",
year = "2005",
month = "11",
day = "1",
doi = "10.1016/j.vaccine.2005.07.086",
language = "English",
volume = "23",
pages = "5212--5224",
journal = "Vaccine",
issn = "0264-410X",
publisher = "Elsevier BV",
number = "45",

}

TY - JOUR

T1 - A computational resource for the prediction of peptide binding to Indian rhesus macaque MHC class I molecules

AU - Peters, B.

AU - Bui, H. H.

AU - Sidney, J.

AU - Weng, Z.

AU - Loffredo, J. T.

AU - Watkins, David

AU - Mothé, B. R.

AU - Sette, A.

PY - 2005/11/1

Y1 - 2005/11/1

N2 - Non-human primates, in general, and Indian rhesus macaques, specifically, play an important role in the development and testing of vaccines and diagnostics destined for human use. To date, several frequently expressed macaque MHC molecules have been identified and their binding specificities characterized in detail. Here, we report the development of computational algorithms to predict peptide binding and potential T cell epitopes for the common MHC class I alleles Mamu-A*01, -A*02, -A*11, -B*01 and -B*17, which cover approximately two thirds of the captive Indian rhesus macaque populations. We validated this method utilizing an SIV derived data set encompassing 59 antigenic peptides. Of all peptides contained in the SIV proteome, the 2.4% scoring highest in the prediction contained 80% of the antigenic peptides. The method was implemented in a freely accessible and user friendly website at www.mamu.liai.org. Thus, we anticipate that our approach can be utilized to rapidly and efficiently identify CD8+ T cell epitopes recognized by rhesus macaques and derived from any pathogen of interest.

AB - Non-human primates, in general, and Indian rhesus macaques, specifically, play an important role in the development and testing of vaccines and diagnostics destined for human use. To date, several frequently expressed macaque MHC molecules have been identified and their binding specificities characterized in detail. Here, we report the development of computational algorithms to predict peptide binding and potential T cell epitopes for the common MHC class I alleles Mamu-A*01, -A*02, -A*11, -B*01 and -B*17, which cover approximately two thirds of the captive Indian rhesus macaque populations. We validated this method utilizing an SIV derived data set encompassing 59 antigenic peptides. Of all peptides contained in the SIV proteome, the 2.4% scoring highest in the prediction contained 80% of the antigenic peptides. The method was implemented in a freely accessible and user friendly website at www.mamu.liai.org. Thus, we anticipate that our approach can be utilized to rapidly and efficiently identify CD8+ T cell epitopes recognized by rhesus macaques and derived from any pathogen of interest.

KW - Epitope

KW - Indian rhesus macaque

KW - MHC

UR - http://www.scopus.com/inward/record.url?scp=26644444563&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=26644444563&partnerID=8YFLogxK

U2 - 10.1016/j.vaccine.2005.07.086

DO - 10.1016/j.vaccine.2005.07.086

M3 - Article

VL - 23

SP - 5212

EP - 5224

JO - Vaccine

JF - Vaccine

SN - 0264-410X

IS - 45

ER -