The utility and limitations of current Web-available algorithms to predict peptides recognized by CD4 T cells in response to pathogen infection.
The utility and limitations of current Web-available algorithms to predict peptides recognized by CD4 T cells in response to pathogen infection.
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DOI：
10.4049/jimmunol.1103640
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发表时间：
2012-05-01
期刊：
影响因子：
--
通讯作者：
Sant AJ
中科院分区：
文献类型：
--
作者：
Chaves FA;Lee AH;Nayak JL;Richards KA;Sant AJ
The ability to track CD4 T cells elicited in response to pathogen infection or vaccination is critical because of the role these cells play in protective immunity. Coupled with advances in genome sequencing of pathogenic organisms, there is considerable appeal for implementation of computer-based algorithms to predict peptides that bind to the class II molecules, forming the complex recognized by CD4 T cells. Despite recent progress in this area, there is a paucity of data regarding their success in identifying actual pathogen-derived epitopes. In this study, we sought to rigorously evaluate the performance of multiple web-available algorithms by comparing their predictions and our results using purely empirical methods for epitope discovery in influenza that utilized overlapping peptides and cytokine Elispots, for three independent class II molecules. We analyzed the data in different ways, trying to anticipate how an investigator might use these computational tools for epitope discovery. We come to the conclusion that currently available algorithms can indeed facilitate epitope discovery, but all shared a high degree of false positive and false negative predictions. Therefore, efficiencies were low. We also found dramatic disparities among algorithms and between predicted IC50 values and true dissociation rates of peptide:MHC class II complexes. We suggest that improved success of predictive algorithms will depend less on changes in computational methods or increased data sets and more on changes in parameters used to “train” the algorithms that factor in elements of T cell repertoire and peptide acquisition by class II molecules.
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影响因子：
3.7
作者：
Chen C;Dow C;Wang P;Sidney J;Read A;Harmsen A;Samuel JE;Peters B
通讯作者：
Peters B
影响因子：
4.4
作者：
Arens, Ramon;Wang, Peng;Benedict, Chris A.
通讯作者：
Benedict, Chris A.
DOI：
10.1073/pnas.91.19.8842
发表时间：
1994-09-13
影响因子：
11.1
作者：
BEESON, C;MCCONNELL, HM
通讯作者：
MCCONNELL, HM
影响因子：
64.8
作者：
CHICZ, RM;URBAN, RG;STROMINGER, JL
通讯作者：
STROMINGER, JL
影响因子：
--
作者：
Chung, Jo L.;Sun, Jian;Peters, Bjoern
通讯作者：
Peters, Bjoern