Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes

Valerie A. Walshe; Channa K. Hattotuwagama; Irini A. Doytchinova; MaiLee Wong; Isabel K. Macdonald; Arend Mulder; Frans H.J. Claas; Pierre Pellegrino; Jo Turner; Ian Williams; Emma L. Turnbull; Persephone Borrow; Darren R Flower

doi:10.1371/journal.pone.0008095

Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes

Valerie A. Walshe
, Channa K. Hattotuwagama
, Irini A. Doytchinova
, MaiLee Wong
, Isabel K. Macdonald
, Arend Mulder
, Frans H.J. Claas
, Pierre Pellegrino
, Jo Turner
, Ian Williams
, Emma L. Turnbull
, Persephone Borrow
, Darren R Flower

University of Oxford
Leiden University Medical Centre
University College London
Camden Primary Care Trust

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

126 Downloads (Pure)

Abstract

Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102.

Original language	English
Article number	e8095
Number of pages	11
Journal	PLoS ONE
Volume	4
Issue number	11
DOIs	https://doi.org/10.1371/journal.pone.0008095
Publication status	Published - 2009

Bibliographical note

© 2009 Walshe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

alleles
amino acid motifs
computational biology
edetic acid
epitopes
HIV-1
HLA-C antigens
histocompatibility antigens class I
humans
mononuclear leukocytes
major histocompatibility complex
statistical models
peptides
protein binding
tertiary protein structure

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10.1371/journal.pone.0008095

Integrating In Silico and In Vitro Analysis of Peptide Binding Affinity to HLA-Cw*0102
© 2009 Walshe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submitted manuscript, 309 KBLicence: CC BY 3.0

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0008095

Cite this

Walshe, V. A., Hattotuwagama, C. K., Doytchinova, I. A., Wong, M., Macdonald, I. K., Mulder, A., Claas, F. H. J., Pellegrino, P., Turner, J., Williams, I., Turnbull, E. L., Borrow, P., & Flower, D. R. (2009). Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes. PLoS ONE, 4(11), Article e8095. https://doi.org/10.1371/journal.pone.0008095

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title = "Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes",

abstract = "Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102.",

keywords = "alleles, amino acid motifs, computational biology, edetic acid, epitopes, HIV-1, HLA-C antigens, histocompatibility antigens class I, humans, mononuclear leukocytes, major histocompatibility complex, statistical models, peptides, protein binding, tertiary protein structure",

author = "Walshe, \{Valerie A.\} and Hattotuwagama, \{Channa K.\} and Doytchinova, \{Irini A.\} and MaiLee Wong and Macdonald, \{Isabel K.\} and Arend Mulder and Claas, \{Frans H.J.\} and Pierre Pellegrino and Jo Turner and Ian Williams and Turnbull, \{Emma L.\} and Persephone Borrow and Flower, \{Darren R\}",

note = "{\textcopyright} 2009 Walshe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",

year = "2009",

doi = "10.1371/journal.pone.0008095",

language = "English",

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Walshe, VA, Hattotuwagama, CK, Doytchinova, IA, Wong, M, Macdonald, IK, Mulder, A, Claas, FHJ, Pellegrino, P, Turner, J, Williams, I, Turnbull, EL, Borrow, P & Flower, DR 2009, 'Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes', PLoS ONE, vol. 4, no. 11, e8095. https://doi.org/10.1371/journal.pone.0008095

TY - JOUR

T1 - Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102

T2 - a bioinformatic approach to the prediction of new epitopes

AU - Walshe, Valerie A.

AU - Hattotuwagama, Channa K.

AU - Doytchinova, Irini A.

AU - Wong, MaiLee

AU - Macdonald, Isabel K.

AU - Mulder, Arend

AU - Claas, Frans H.J.

AU - Pellegrino, Pierre

AU - Turner, Jo

AU - Williams, Ian

AU - Turnbull, Emma L.

AU - Borrow, Persephone

AU - Flower, Darren R

N1 - © 2009 Walshe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2009

Y1 - 2009

N2 - Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102.

AB - Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102.

KW - alleles

KW - amino acid motifs

KW - computational biology

KW - edetic acid

KW - epitopes

KW - HIV-1

KW - HLA-C antigens

KW - histocompatibility antigens class I

KW - humans

KW - mononuclear leukocytes

KW - major histocompatibility complex

KW - statistical models

KW - peptides

KW - protein binding

KW - tertiary protein structure

UR - https://www.scopus.com/pages/publications/77951247977

U2 - 10.1371/journal.pone.0008095

DO - 10.1371/journal.pone.0008095

M3 - Article

C2 - 19956609

SN - 1932-6203

VL - 4

JO - PLoS ONE

JF - PLoS ONE

IS - 11

M1 - e8095

ER -

Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes

Abstract

Bibliographical note

UN SDGs

Keywords

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