NetChop 2.0 Prediction Server
The NetChop server produces neural network predictions for cleavage sites of the
NetChop has been trained on human data only, and will therefore presumably have
better performance for prediction of the cleavage sites of the human proteasome.
However, since the proteasome structure is quite conserved, we believe that the
server is able to produce reliable predictions for at least the other mammalian
At the moment there are four different networks that can be used for predictions:
C-term 1.0, C-term 2.0, N-term, and 20S. The different networks are trained on
different data sets. C-term 1.0 network is trained with 229 MHC class I ligands
extracted from public databases (using only C-terminal cleavages). N-term network
is trained with the same data set, but by using N-terminal cleavages. C-term 2.0
network is trained with a larger database consisting of 1110 publicly available
MHC class I ligands (using only C-terminal cleavage site of the ligands). 20S
network is trained with in vitro degradation data published in
Toes, et al.
and Emmerich et al.
We believe C-term 2.0 network performs best in predicting the boundaries of CTL
epitopes. It is possible to get the averaged prediction from different networks.
4-3-2004: There had been some discussion about whether or not
C-term 1.0 and C-term 2.0 networks can predict proteasome specificity,
because they are trained using MHC ligands. In a recent article
Saxova et al., we have shown that these
networks can predict proteasome cleavage sites identified by in vitro
experiments much better than other methods available at the moment.
Still, if you feel uncomfortable using C-term networks, you can use 20S
network. Our 20S network has a very good performance in predicting in
vitro proteasomal cleavage.
Another proteasome prediction server is available in Tubingen University:
Type/paste in your sequence OR enter the name of a file with one or more sequences in FASTA format:
NOTE: All sequences are automatically deleted immediately after
For publication of results, please cite:
Prediction of proteasome cleavage motifs by neural networks.
A. Nussbaum, Hansjorg Schild, Vincent Detours, and S. Brunak,
Prot. Eng., 2002, vol. 15(4), 287-296