NetCTLpan 1.1 Server
NetCTLpan 1.1 server predicts CTL epitopes in protein sequences. The current version 1.1 is an update to the original NetCTL server that allows for prediction of CTL epitope with restriction to any MHC molecules of known protein sequence.
NOTE. New in this version. The method has been updated to include the newest MHC allele releases from the IMGT/HLA and IPD-MHC databases (for non-human primates and pig). This includes adaptation of the new nomenclature for HLA and Rhesus macaque (Mamu) alleles. The MHC binding predictions has been updated to NetMHCpan version 2.3.
Predictions can be made for 8-11mer peptides. Note that all non 9mer predictions are made using approximations. Most HLA molecules have a strong preference for binding 9mers.
The method integrates prediction of peptide MHC class I binding, proteasomal C terminal cleavage and TAP transport efficiency. MHC class I binding and proteasomal cleavage is performed using artificial neural networks. TAP transport efficiency is predicted using weight matrix.
The prediction values are calculated as a weighted average of the MHC, TAP and C terminal cleavage scores. and as %-Rank to a set of 200.000 random natural peptides.
The MHC peptide binding is predicted using neural networks trained as described for the NetMHCpan server. The proteasome cleavage event is predicted using the version of the NetChop neural networks trained on C terminals of known CTL epitopes as describe for the NetChop-3.0 server. The TAP transport efficiency is predicted using the weight matrix based method describe by Peters et al., 2003
Species Warning. Note, that both the proteasome and TAP predictions were developed using experimental data for human versions of the molecule. At least for TAP molecules, there are known to be some species dependent differences in specificity. Therefore, using these predictions for eptitope processing in non-human cells should only be done with extra caution in interpreting results.
View the version history of this server. All the previous versions are available on line, for comparison and reference.
For publication of results, please cite:
Data resources used to develop this server was obtained from
Scientific problems: Technical problems: