※ Computational resources of MHC binding epitopes :

Last updated: November 26th, 2011

Introduction :

    Major histocompatibility complex (MHC) molecules play an important role in the immune system through capturing peptide antigens for display on cell surfaces, while different types of MHC molecules bind distinct peptides. These peptide-MHC complexes are recognized by T cells via their T-cell receptors, which resulted in that T-cell recognition is thus restricted to those peptides that the MHC molecules can present. Therefore, prediction of peptides which could bind to MHC molecules is important for identification of peptides capable of eliciting a T-cell response.

    We apologized that the computational studies without any web links of databases or tools will not be included in this compendium, since it's not easy for experimentalists to use studies directly. We are grateful for users feedback. Please inform Zexian Liu, Dr. Yu Xue or Dr. Jian Ren to add, remove or update one or multiple web links below.


<1> MHC binding epitopes Databases

<2> Prediction of MHC binding epitopes


<1> MHC binding epitopes Databases:

1. IEDB: T cell epitopes and antibody databases (Vita Prasad, et al., 2010 ).

2. MHCBN : Database containing MHC/TAP binding peptides, non-binding peptides and T-cell epitopes (Lata, et al., 2009 ).

3. SYFPEITHI : Database containing MHC ligands and peptide motifs (Rammensee, et al., 1999).

4. ANTIJEN: Database containing B Cell Epitopes, TAP and T Cell Epitopes (Toseland, et al., 2005).

5. EPIMHC: Database containing MHC-binding peptides and T cell epitopes (Reche, et al., 2005).

6. JenPep: Database containing MHC and TAP binding peptides and T-cell epitopes(Blytheet al., 2002).

7. IMGT: A integrated database on immunoglobulins (IG) or antibodies, T cell receptors (TR) , major histocompatibility complex (MHC) and antigens. (Lefrancet al., 2011).

8. MotifScan: HIV molecular immunology database.

9. HIV database: defined HIV epitopes.

10. dbMHC: A Database of DNA and clinical data related to MHC.

<2> Prediction of MHC binding epitopes:

1. PREDNOD: a prediction server for peptide binding to the H-2g7 haplotype of the non-obese diabetic mouse. The tool is not available (Rajapakseet al., 2006).

2. SYFFPEITHI: Prediction of the ligation strength to a defined MHC I or II type for a sequence of amino acids (Rammenseeet al., 1999).

3. RANKPEP: Prediction of MHCI- and MHCII-peptide binders (Recheet al., 2002).

4. NetMHC: The server predicts peptides binding to different MHC I molecules. (Lundegaardet al., 2008).

5. NetCTL: Prediction of CTL epitopes (Larsenet al., 2007).

6. MHC2PRED: Prediction of promiscuous MHC II binders.

7. IEDB: The tools provide the prediction and analysis of immune epitopes (Zhanget al., 2008).

8. netMHCII: The server can predict peptides binding to 14 MHC II supertypes (Nielsenet al., 2007).

9. netMHCpan: Prediction of peptides binding to more than 120 different MHC I molecules (Nielsenet al., 2007).

10. netMHCIIpan: The server can predict MHC II restricted peptides (Nielsenet al., 2008).

11. PROPREDI: Identifying the promiscuous binding regions for 47 MHC class-I alleles (Singhet al., 2003).

12. PROPRED: Prediction of MHC class-II binding peptides (Singhet al., 2001).

13. PREDEP: A MHC Class I epitope prediction.

14. BIMAS: Prediction of 8-mer, 9-mer, or 10-mer peptides binding to HLA class I molecules (Parkeret al., 1994).

15. MAPPP: Prediction of MHC-I antigenic peptides including cleavage prediction and MHC binding prediction (Hakenberget al., 2003).

16. BiodMHC: the binding affinity prediction of class II MHC-peptide. The tool is not available (Wanget al., 2009).

17. MOTIF_SCAN: three functions: (1) find HLA anchor residue motifs within protein sequences for specified HLA genotypes, serotypes, or supertypes, (2) search any single protein for all known HLA anchor residue motifs, and (3) view motif libraries.

18. MULTIPRED: the prediction of peptide binding to multiple molecules (proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. The tool is not available (Zhanget al., 2005).

19. SVMHC: prediction of both MHC class I and class II binding peptides (D?nneset al., 2006).

20. SVRMHC: predicting peptide-MHC binding affinities using SVRMHC models (Wanet al., 2006).

21. POPI: predicting immunogenicity of MHC class I and II binding peptides (Tung?et al., 2007).

22. MHCPRED: A quantitative T-cell epitope prediction server. The tool is not available. (Guanet al., 2006).

23. ARB: predictions of peptide binding to MHC class II molecules (Buiet al., 2005).

24. AntiBP: Prediction of the antibacterial peptides (Lataet al., 2007).

25. CTLpred: prediction of CTL epitopes (Bhasinet al., 2004).

26. EpiDirect: MHC II restricted T cell epitopes and ligands. The tool is not available..

27. EpiVaxb: MHC I and II conserved and promiscuous epitopes.

28. FRAGPREDICT: Prediction of proteasome cleavage sites (Holzhütteret al., 1999).

29. MHC bench: A server for evaluating MHC binding peptide prediction algorithms.

30. nHLAPred: A neural network prediction server for MHC class-I binding peptides (Bhasinet al., 2007).

31. REMUS: Identification of unique peptide segments (Changet al., 2006).

32. SMM: Prediction of HLA-A2 binding peptides (Peterset al., 2003).

33. HLA-DR4Pred: Prediction of HLA-DRB1*0401 binders based SVM and ANN (Bhasinet al., 2004).

34. MMBPred: Prediction of mutated high affinity MHC class I binders based upon quantitative matrices (Bhasinet al., 2003).