Evaluation of MHC-II peptide binding prediction servers: applications for vaccine research
2008

Evaluation of MHC-II Peptide Binding Prediction Servers for Vaccine Research

Sample size: 721 publication Evidence: moderate

Author Information

Author(s): Lin Hong Huang, Zhang Guang Lan, Tongchusak Songsak, Reinherz Ellis L, Brusic Vladimir

Primary Institution: Dana-Farber Cancer Institute

Hypothesis

How accurately can different prediction servers identify MHC-II peptide binding?

Conclusion

Current HLA-II prediction servers have limited accuracy compared to HLA-I predictors, indicating a need for improved methods.

Supporting Evidence

  • The study assessed a total of 113 predictors across various HLA-DR alleles.
  • 17 predictors showed good performance, while 55 showed poor performance.
  • The best individual predictor was NETMHCIIPAN, followed by PROPRED and IEDB (Consensus).
  • Current predictive capabilities allow for the prediction of only 50% of actual T-cell epitopes.

Takeaway

This study looked at different computer programs that predict how well certain proteins can bind to immune system molecules. It found that many of these programs don't work very well.

Methodology

The study analyzed the performance of 21 HLA-II binding prediction servers using data from 721 peptide binding assays.

Potential Biases

The performance assessments may be biased due to the use of pre-defined peptide sets rather than standardized full-overlapping studies.

Limitations

The study was limited to seven common HLA-DR molecules and did not assess all possible predictors.

Digital Object Identifier (DOI)

10.1186/1471-2105-9-S12-S22

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