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Epitope prediction is a key problem in computational immunology. An epitope is a part of an antigen that is recognized by the immune system. One distinguishes between B-cell and T-cell epitopes. Epitope prediction helps to gain a deeper understanding of immune responses and is of great interest to vaccine design. [1]
T-Cell Epitope Prediction
editT-cell epitopes are peptides derived from antigenic proteins that are presented on the cell surface by MHC molecules and recognized by T cells. Due to the highly complex and so far not sufficiently understood processes governing T-cell response, prediction of T-cell epitopes is a very challenging problem. Available prediction methods are not sufficiently accurate to be beneficial for vaccine design.
MHC-peptide binding on the other hand can be accurately predicted. Since it is essential, albeit not sufficient, for a T-cell epitope to bind to an MHC molecule, MHC-binding prediction is commonly used as an alternative to epitope prediction. Often, the term Epitope prediction actually refers to MHC-binding prediction.
A wide variety of methods have been proposed to predict MHC-binding peptides. [2][3][4][5][6]
MHC class I binding prediction can be improved by additionally predicting the antigen processing pathway, namely the degradation of the protein by the proteasome, and the transport of peptides from the cytosol into the endoplasmatic reticulum by TAP. Peptides that bind to MHC but are not produced by the antigen processing machinery are filtered out.
There exist methods for proteasomal cleavage and TAP transport alone. Some integrated methods for the prediction of antigen processing and MHC binding have also been published. [7][8]
The prediction of T-cell reactivity of peptide:MHC complexes has also been addressed computationally. These attempts are only moderately successful. [9]
B-Cell Epitope Prediction
editWhile T-cell epitopes are linear epitopes, B-cell epitopes (structures that are recognized by B-cell receptors or antibodies) are mostly conformational epitopes, i.e. they exist within the tertiary structure of the antigen. The prediction of B-cell epitopes has therefore been less successful than the prediction of T-cell epitopes. [10][11][12]
See also
edit- Vaccine Design
- Computational immunology
External links
editT-Cell Epitope Prediction
editInterfaces to Multiple Prediction Methods
editT-cell Reactivity Prediction
editB-Cell Epitope Prediction
editReferences
edit- ^ Toussaint NC, Kohlbacher O (2009). "Towards in silico design of epitope-based vaccines". Expert Opinion on Drug Discovery. 4 (10): 1047–1060. doi:10.1517/17460440903242283.
- ^ Buus S, Lauemöller SL, Worning P, Kesmir C, Frimurer T, Corbet S, Fomsgaard A, Hilden J, Holm A, Brunak S (2003). "Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach". Tissue Antigens. 62 (5): 378–384. doi:10.1034/j.1399-0039.2003.00112.x. PMID 14617044.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ^ Rammensee H, Bachmann J, Emmerich NP, Bachor OA, Stevanovic S (1999). "SYFPEITHI: atabase for MHC ligands and peptide motifs". Immunogenetics. 50 (3–4): 213––219. doi:10.1007/s002510050595. PMID 10602881.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ^ Parker KC, Bednarek MA, Coligan JE (1994). "Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains". J Immunol. 152 (1): 163–175. PMID 8254189.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ^ Dönnes P, Kohlbacher O (2006). "SVMHC: a server for prediction of MHC-binding peptides". Nucleic Acids Res. 34 (Web Server issue): W194––W197. doi:10.1093/nar/gkl284. PMC 1538857. PMID doi = 10.1093/nar/gkl284 16844990 doi = 10.1093/nar/gkl284.
{{cite journal}}: Check|pmid=value (help); Missing pipe in:|pmid=(help) - ^ Nielsen M, Lundegaard C, Blicher T, Lamberth K, Harndahl M, Justesen S, Roder G, Peters B, Sette , Lund O, Buus S (2007). Kallas, Esper (ed.). "NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence". PLoS ONE. 2 (8): e796. doi:10.1371/journal.pone.0000796. PMC 1949492. PMID 17726526.
{{cite journal}}: CS1 maint: multiple names: authors list (link) CS1 maint: unflagged free DOI (link) - ^ önnes P, Kohlbacher O (2005). "Integrated modeling of the major events in the MHC class I antigen processing pathway". Protein Sci. 14(8) (8): 2132–214. doi:10.1110/ps.051352405. PMC 2279325. PMID 15987883.
- ^ Larsen MV, Lundegaard C, Lamberth K, Buus S, Brunak S, Lund O, Nielsen M (2005). "An integrative approach to CTL pitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions". Eur J Immunol. 35 (8): 2295–2303. doi:10.1002/eji.200425811. PMID 5997466.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ^ Tung CW, Shinn-Ying H (007). "POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties". Bioinformatics. 23 (8): 942–949. doi:10.1093/bioinformatics/btm061. PMID doi = 10.1093/bioinformatics/btm061 17384427 doi = 10.1093/bioinformatics/btm061.
{{cite journal}}: Check|pmid=value (help); Check date values in:|year=(help); Missing pipe in:|pmid=(help) - ^ ndersen PH , Nielsen M, Lund O (2006). "Prediction of residues in discontinuous B-cell epitopes using protein 3D structures". Protein Sci. 15 (11): 2558–2567. doi:10.1110/ps.062405906. PMC 2242418. PMID 7001032.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ^ Larsen JEP, Lund O, Nielsen M (2006). "Improved method for predicting linear B-cell epitopes". Immunome Res. 2: 2. doi:10.1186/1745-7580-2-2. PMC 1479323. PMID 16635264.
{{cite journal}}: CS1 maint: multiple names: authors list (link) CS1 maint: unflagged free DOI (link) - ^ Rubinstein ND, Mayrose I, Martz E, Pupko T (2009). "Epitopia: a web-server for predicting B-cell epitopes". BMC Bioinformatics. 10: 287 pmid = 19751513. doi:10.1186/1471-2105-10-287. PMC 2751785. PMID 19751513.
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