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. Author manuscript; available in PMC: 2013 Apr 3.
Published in final edited form as: Curr Pharm Des. 2009;15(28):3249–3261. doi: 10.2174/138161209789105171

Table I.

Some approaches to predicting HLA-DR peptide binding

Approach Name Notes References
Endogenous peptide sequences SYFPEITHI Preferred residues at particular positions [1]
IC50 assay of single amino acid variants of test peptides TEPITOPE ProPred Includes “virtual” matrices for some alleles by pocket combination [2, 3]
IC50 assay of large sets of varied peptide sequences ARB, SMM - align Position-specific scoring matrices [4, 5]
Analysis of known T cell epitopes RANKPEP Position-specific scoring matrices [6]
Analysis of known T cell epitopes MULTIPRED Neural network and Hidden Markov model algorithms, identification of promiscuous epitopes [7]
Direct binding of peptide displayed on a phage libraries “anchor combination” Position-specific scoring matrices [8]
Binding inhibition by a positional scanning libraries “undecapeptide library screen” 10-residue motif developed [9]
Known T cell epitopes, MHC structures and sequences NetMHCIIPan Neural network approach to associate binding preferences and MHC sequences [10]
[1]

Rammensee H, Bachmann J, Emmerich NP, Bachor OA, Stevanovic S. SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics. 1999; 50:213-9.

[2]

Sturniolo T, Bono E, Ding J, Raddrizzani L, Tuereci O, Sahin U, et al. Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices. Nat Biotechnol. 1999; 17:555-61.

[3]

Singh H, Raghava GP. ProPred: prediction of HLA?DR binding sites. Bioinformatics. 2001; 17:1236-7.

[4]

Bui HH, Sidney J, Peters B, Sathiamurthy M, Sinichi A, Purton KA, et al. Automated generation and evaluation of specific MHC binding predictive tools: ARB matrix applications. Immunogenetics. 2005; 57:304-14.

[5]

Nielsen M, Lundegaard C, Lund O. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinformatics. 2007; 8:238.

[6]

Reche PA, Glutting JP, Reinherz EL. Prediction of MHC class I binding peptides using profile motifs. Hum Immunol. 2002; 63:701-9.

[7]

Zhang GL, Khan AM, Srinivasan KN, August JT, Brusic V. MULTIPRED: a computational system for prediction of promiscuous HLA binding peptides. Nucleic Acids Res. 2005; 33:W172-9.

[8]

Hammer J, Belunis C, Bolin D, Papadopoulos J, Walsky R, Higelin J, et al. High-affinity binding of short peptides to major histocompatibility complex class II molecules by anchor combinations. Proc Natl Acad Sci U S A. 1994; 91:4456-60.

[9]

Fleckenstein B, Kalbacher H, Muller CP, Stoll D, Halder T, Jung G, et al. New ligands binding to the human leukocyte antigen class II molecule DRB1*0101 based on the activity pattern of an undecapeptide library. Eur J Biochem. 1996; 240:71-7.

[10]

Nielsen M, Lundegaard C, Blicher T, Peters B, Sette A, Justesen S, et al. Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan. PLoS Comput Biol. 2008; 4:e1000107.