PMID- 24461003
OWN - NLM
STAT- MEDLINE
DCOM- 20140915
LR  - 20140127
IS  - 1399-0039 (Electronic)
IS  - 0001-2815 (Linking)
VI  - 82
IP  - 4
DP  - 2013 Oct
TI  - Evaluation of peptide selection approaches for epitope-based vaccine design.
PG  - 243-51
LID - 10.1111/tan.12199 [doi]
AB  - A major challenge in epitope-based vaccine (EV) design stems from the vast 
      genomic variation of pathogens and the diversity of the host cellular immune 
      system. Several computational approaches have been published to assist the 
      selection of potential T cell epitopes for EV design. So far, no thorough 
      comparison between the current methods has been realized. Using human 
      immunodeficiency virus as test case, different EV selection algorithms were 
      evaluated with respect to their ability to select small peptides sets with broad 
      coverage of allelic and pathogenic diversity. The methods were compared in terms 
      of in silico measurements simulating important vaccine properties like the 
      ability of inducing protection against a multivariant pathogen in a population; 
      the predicted immunogenicity; pathogen, allele, and population coverage; as well 
      as the conservation of selected epitopes. Additionally, we evaluate the use of 
      human leukocyte antigen (HLA) supertypes with regards to their applicability for 
      population-spanning vaccine design. The results showed that in terms of induced 
      protection methods that simultaneously aim to optimize pathogen and HLA coverage 
      significantly outperform methods focusing on pathogen coverage alone. Moreover, 
      supertype-based approaches for coverage of HLA diversity were showed to yield 
      only satisfying results in populations in which the supertype representatives are 
      prevalent.
CI  - (c) 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
FAU - Schubert, B
AU  - Schubert B
AD  - Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, 
      and Department of Computer Science, University of Tubingen, 72076, Tubingen, 
      Germany.
FAU - Lund, O
AU  - Lund O
FAU - Nielsen, M
AU  - Nielsen M
LA  - eng
GR  - HHSN272201200010C/PHS HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PL  - England
TA  - Tissue Antigens
JT  - Tissue antigens
JID - 0331072
RN  - 0 (AIDS Vaccines)
RN  - 0 (Antigens, Viral)
RN  - 0 (Epitopes, T-Lymphocyte)
RN  - 0 (HLA Antigens)
RN  - 0 (Peptides)
RN  - 0 (Vaccines, Subunit)
SB  - IM
MH  - AIDS Vaccines/*immunology
MH  - Algorithms
MH  - Alleles
MH  - Antigens, Viral/genetics/*immunology
MH  - Computer Simulation
MH  - Epitopes, T-Lymphocyte/genetics/*immunology
MH  - Gene Frequency
MH  - HIV Infections/*prevention & control/virology
MH  - HIV-1/genetics/*immunology
MH  - HLA Antigens/genetics/immunology
MH  - Host-Pathogen Interactions
MH  - Humans
MH  - Models, Immunological
MH  - Peptides/genetics/*immunology
MH  - T-Lymphocytes/immunology/virology
MH  - Vaccines, Subunit
OTO - NOTNLM
OT  - HLA supertypes
OT  - epitope-based vaccine design
OT  - optimization
OT  - peptide selection
EDAT- 2014/01/28 06:00
MHDA- 2014/09/16 06:00
CRDT- 2014/01/28 06:00
PHST- 2013/03/22 00:00 [received]
PHST- 2013/07/11 00:00 [revised]
PHST- 2013/08/14 00:00 [accepted]
PHST- 2014/01/28 06:00 [entrez]
PHST- 2014/01/28 06:00 [pubmed]
PHST- 2014/09/16 06:00 [medline]
AID - 10.1111/tan.12199 [doi]
PST - ppublish
SO  - Tissue Antigens. 2013 Oct;82(4):243-51. doi: 10.1111/tan.12199.