Figure courtesy of A. J. Reits

NetCTL 1.0 Server

NetCTL 1.0 server predicts CTL epitopes in protein sequences. The method integrates prediction of peptide MHC binding, proteasomal C terminal cleavage and TAP transport efficiency. The server allows for predictions of CTL epitopes restricted to 10 MHC supertype. MHC binding and proteasomal cleavage is performed using artificial neural networks. TAP transport efficiency is predictied using weight matrix.

The MHC peptide binding is predicted using neural networks trained as described for the NetMHC 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.

The server includes predictions of MHC/peptide binding for 10 MHC class I supertypes. The output from the neural network predicting MHC/peptide binding is a log transformed value related to the IC50 values in nM units. For details on the transformation please see output format.

The scores from the three individual prediction methods are integrated as a weighted sum with a relative weight on peptide/MHC binding of 1. Different thresholds for the integrated score can be translated into sensitivity/specificity values. In a large benchmark calculate containing more than 200 known CTL epitopes the following relations were found

Score	Sensitivity	Specificity
> 1.00	0.53	0.99
> 0.75	0.65	0.97
> 0.50	0.75	0.93

The project is collaboration between CBS and IMMI.

Instructions

Output format

Article abstract

CITATIONS

For publication of results, please cite:

• Current version:

  An integrative approach to CTL epitope prediction. A combined algorithm integrating MHC-I binding, TAP transport efficiency, and proteasomal cleavage predictions.
  Larsen M.V., Lundegaard C., Kasper Lamberth, Buus S,. Brunak S., Lund O., and Nielsen M.
  European Journal of Immunology. 35(8): 2295-303. 2005

  View the abstract        

• Related publications:

  Reliable prediction of T-cell epitopes using neural networks with novel sequence representations.
  Nielsen M, Lundegaard C, Worning P, Lauemoller SL, Lamberth K, Buus S, Brunak S, Lund O.
  Protein Sci., 12:1007-17, 2003.

  View the abstract

  Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach.
  Buus S, Lauemoller SL, Worning P, Kesmir C, Frimurer T, Corbet S, Fomsgaard A, Hilden J, Holm A, Brunak S.
  Tissue Antigens., 62(5):378-84, 2003.

  View the abstract

  The role of the proteasome in generating cytotoxic T cell epitopes: Insights obtained from improved predictions of proteasomal cleavage.
  M. Nielsen, C. Lundegaard, S. Brunak, O. Lund, and C. Kesmir. Immunogenetics., 57(1-2):33-41, 2005.

  View the abstract

  Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors
  Peters, B., Bulik, S., Tampe, R., Endert, P. M. V. and Holzhutter, H. G.
  J. Immunol. 171: 1741-1749, 2003.

  View the abstract

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  PORTABLE VERSION

  Would you prefer to run NetCTL at your own site? The NetCTL 1.0 package is in preparation. It will soon be available for the most common UNIX platforms including MIPS (under IRIX, Silicon Graphics), SPARC (under Solaris, Sun), Alpha (under OSF1) and Pentium family (under Linux). Send inquiries by e-mail to software@cbs.dtu.dk.
  
  

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  GETTING HELP

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