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
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 http://www.cbs.dtu.dk/services/NetCTLpan-1.0.