PMID- 24447175
OWN - NLM
STAT- MEDLINE
DCOM- 20140908
LR  - 20211021
IS  - 1399-0039 (Electronic)
IS  - 0001-2815 (Print)
IS  - 0001-2815 (Linking)
VI  - 83
IP  - 2
DP  - 2014 Feb
TI  - Improved pan-specific MHC class I peptide-binding predictions using a novel 
      representation of the MHC-binding cleft environment.
PG  - 94-100
LID - 10.1111/tan.12292 [doi]
AB  - Major histocompatibility complex (MHC) molecules play a key role in cell-mediated 
      immune responses presenting bounded peptides for recognition by the immune system 
      cells. Several in silico methods have been developed to predict the binding 
      affinity of a given peptide to a specific MHC molecule. One of the current 
      state-of-the-art methods for MHC class I is NetMHCpan, which has a core 
      ingredient for the representation of the MHC class I molecule using a 
      pseudo-sequence representation of the binding cleft amino acid environment. New 
      and large MHC-peptide-binding data sets are constantly being made available, and 
      also new structures of MHC class I molecules with a bound peptide have been 
      published. In order to test if the NetMHCpan method can be improved by 
      integrating this novel information, we created new pseudo-sequence definitions 
      for the MHC-binding cleft environment from sequence and structural analyses of 
      different MHC data sets including human leukocyte antigen (HLA), non-human 
      primates (chimpanzee, macaque and gorilla) and other animal alleles (cattle, 
      mouse and swine). From these constructs, we showed that by focusing on MHC 
      sequence positions found to be polymorphic across the MHC molecules used to train 
      the method, the NetMHCpan method achieved a significant increase in the 
      predictive performance, in particular, of non-human MHCs. This study hence showed 
      that an improved performance of MHC-binding methods can be achieved not only by 
      the accumulation of more MHC-peptide-binding data but also by a refined 
      definition of the MHC-binding environment including information from non-human 
      species.
CI  - (c) 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
FAU - Carrasco Pro, S
AU  - Carrasco Pro S
AD  - Laboratorio de Bioinformatica y Biologia Molecular, Laboratorios de Investigacion 
      y Desarrollo, Facultad de Ciencias y Filosofia, Universidad Peruana Cayetano 
      Heredia, Lima, Peru.
FAU - Zimic, M
AU  - Zimic M
FAU - Nielsen, M
AU  - Nielsen M
LA  - eng
GR  - HHSN272200900045C/AI/NIAID NIH 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 (Histocompatibility Antigens Class I)
RN  - 0 (Peptides)
SB  - IM
MH  - Alleles
MH  - Animals
MH  - Binding Sites
MH  - Cattle
MH  - Databases, Protein
MH  - Gorilla gorilla
MH  - Histocompatibility Antigens Class I/*chemistry/immunology/metabolism
MH  - Humans
MH  - Macaca
MH  - Mice
MH  - *Molecular Docking Simulation
MH  - Pan troglodytes
MH  - Peptides/*chemistry/immunology/metabolism
MH  - Protein Binding
MH  - Protein Interaction Domains and Motifs
MH  - *Software
MH  - Swine
PMC - PMC3925504
MID - NIHMS551103
OTO - NOTNLM
OT  - Artificial Neural Networks
OT  - Binding specificity
OT  - CTL epitopes
OT  - Epitope prediction
OT  - MHC class I
OT  - Non-human primates
EDAT- 2014/01/23 06:00
MHDA- 2014/09/10 06:00
PMCR- 2015/02/01
CRDT- 2014/01/23 06:00
PHST- 2013/10/22 00:00 [received]
PHST- 2013/12/16 00:00 [accepted]
PHST- 2014/01/23 06:00 [entrez]
PHST- 2014/01/23 06:00 [pubmed]
PHST- 2014/09/10 06:00 [medline]
PHST- 2015/02/01 00:00 [pmc-release]
AID - 10.1111/tan.12292 [doi]
PST - ppublish
SO  - Tissue Antigens. 2014 Feb;83(2):94-100. doi: 10.1111/tan.12292.