Main reference:

NetCTLpan. Pan-specific MHC class I pathway epitope predictions.
Stranzl T., Larsen M. V., Lundegaard C., Nielsen M.
Immunogenetics. 2010 Apr 9. [Epub ahead of print]

Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark

Reliable predictions of immunogenic peptides are essential in rational vaccine design and can minimize the experimental effort needed to identify epitopes. In this work, we describe a pan-specific MHC class I epitope predictor, NetCTLpan. The method integrates predictions of proteasomal cleavage, TAP transport efficiency, and MHC class I binding affinities into a MHC class I pathway likelihood score and is an improved and extended version of NetCTL. The NetCTLpan method performs predictions for all MHC class I molecules with known protein sequence and allows predictions for 8, 9, 10 and 11-mer epitopes. In order to meet the need for a low false positive rate, the method is optimized to achieve high specificity.

The method was trained and validated on large data sets of experimentally identified MHC class I ligands and CTL epitope. It has been reported, that MHC molecules are differentially dependent on TAP transport and proteasomal cleavage. Here, we did not find any consistent signs of such MHC differences and the NetCTLpan method is implemented with fixed weights for proteasomal cleavage and TAP transport for all MHC molecules.

The predictive performance of the NetCTLpan method was shown to outperform other state-of-the-art CTL epitope prediction methods. Our results further illustrate the importance of using full-type HLA restriction information when identifying MHC class-I epitopes. When compared to the NetMHCpan and NetCTL methods, the experimental effort to identify 90% of new epitopes can be reduced by 15% and 40% respectively.

The method and benchmark data set are available at

PMID: 20379710

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