Original Paper

Immunogenetics

, Volume 62, Issue 6, pp 357-368

Open Access This content is freely available online to anyone, anywhere at any time.

NetCTLpan: pan-specific MHC class I pathway epitope predictions

  • Thomas StranzlAffiliated withDepartment of Systems Biology DTU, Building 208, Center for Biological Sequence Analysis, Technical University of Denmark Email author 
  • , Mette Voldby LarsenAffiliated withDepartment of Systems Biology DTU, Building 208, Center for Biological Sequence Analysis, Technical University of Denmark
  • , Claus LundegaardAffiliated withDepartment of Systems Biology DTU, Building 208, Center for Biological Sequence Analysis, Technical University of Denmark
  • , Morten NielsenAffiliated withDepartment of Systems Biology DTU, Building 208, Center for Biological Sequence Analysis, Technical University of Denmark

Abstract

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 major histocompatibility complex (MHC) class I epitope predictor, NetCTLpan. The method integrates predictions of proteasomal cleavage, transporter associated with antigen processing (TAP) transport efficiency, and MHC class I binding affinity 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 peptides. 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 datasets of experimentally identified MHC class I ligands and cytotoxic T lymphocyte (CTL) epitopes. 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 dependencies, 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 confirm the importance of using full-type human leukocyte antigen restriction information when identifying MHC class I epitopes. Using the NetCTLpan method, the experimental effort to identify 90% of new epitopes can be reduced by 15% and 40%, respectively, when compared to the NetMHCpan and NetCTL methods. The method and benchmark datasets are available at http://​www.​cbs.​dtu.​dk/​services/​NetCTLpan/​.

Keywords

MHC class I pathway HLA Pan-specific prediction CTL epitope MHC polymorphism