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Flanking p10 contribution and sequence bias in matrix based epitope prediction: revisiting the assumption of independent binding pockets.

Parry CS - BMC Struct. Biol. (2008)

Bottom Line: One new matrix shows significant improvement over the base matrix; the other does not.One of the extended quantitative matrices showed significant improvement in prediction over the original nine residue matrix and over the other extended matrix.Proline in the sequence of the peptide library of the better performing matrix presumably stabilizes the peptide conformation through neighbour interactions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computational Biophysics Section, Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892-9314, USA. csparry@helix.nih.gov

ABSTRACT

Background: Eluted natural peptides from major histocompatibility molecules show patterns of conserved residues. Crystallographic structures show that the bound peptide in class II major histocompatibility complex adopts a near uniform polyproline II-like conformation. This way allele-specific favoured residues are able to anchor into pockets in the binding groove leaving other peptide side chains exposed for recognition by T cells. The anchor residues form a motif. This sequence pattern can be used to screen large sequences for potential epitopes. Quantitative matrices extend the motif idea to include the contribution of non-anchor peptide residues. This report examines two new matrices that extend the binding register to incorporate the polymorphic p10 pocket of human leukocyte antigen DR1. Their performance is quantified against experimental binding measurements and against the canonical nine-residue register matrix.

Results: One new matrix shows significant improvement over the base matrix; the other does not. The new matrices differ in the sequence of the peptide library.

Conclusion: One of the extended quantitative matrices showed significant improvement in prediction over the original nine residue matrix and over the other extended matrix. Proline in the sequence of the peptide library of the better performing matrix presumably stabilizes the peptide conformation through neighbour interactions. Such interactions may influence epitope prediction in this test of quantitative matrices. This calls into question the assumption of the independent contribution of individual binding pockets.

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Related in: MedlinePlus

Distribution of residuals for GAD65. Values of half maximal inhibitory concentration are plotted for glutamic acid decarboxylase (GAD65) together with calculated residuals. The top panel is the plot of IC50 against prediction for GAD65; the bottom panel shows the distribution of the residuals.
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Figure 3: Distribution of residuals for GAD65. Values of half maximal inhibitory concentration are plotted for glutamic acid decarboxylase (GAD65) together with calculated residuals. The top panel is the plot of IC50 against prediction for GAD65; the bottom panel shows the distribution of the residuals.

Mentions: The predictive potential is more accurately captured in terms of variance ("bandwidth") and residuals ("noise"). Residuals for the three data sets were calculated. A typical plot is shown in Figure 3 for GAD65 data set. The sum of the square of the residual values is calculated for each prediction matrix P9, P10 or PP10. Finally, the quality of the fit is assessed through the r-square value:


Flanking p10 contribution and sequence bias in matrix based epitope prediction: revisiting the assumption of independent binding pockets.

Parry CS - BMC Struct. Biol. (2008)

Distribution of residuals for GAD65. Values of half maximal inhibitory concentration are plotted for glutamic acid decarboxylase (GAD65) together with calculated residuals. The top panel is the plot of IC50 against prediction for GAD65; the bottom panel shows the distribution of the residuals.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2600787&req=5

Figure 3: Distribution of residuals for GAD65. Values of half maximal inhibitory concentration are plotted for glutamic acid decarboxylase (GAD65) together with calculated residuals. The top panel is the plot of IC50 against prediction for GAD65; the bottom panel shows the distribution of the residuals.
Mentions: The predictive potential is more accurately captured in terms of variance ("bandwidth") and residuals ("noise"). Residuals for the three data sets were calculated. A typical plot is shown in Figure 3 for GAD65 data set. The sum of the square of the residual values is calculated for each prediction matrix P9, P10 or PP10. Finally, the quality of the fit is assessed through the r-square value:

Bottom Line: One new matrix shows significant improvement over the base matrix; the other does not.One of the extended quantitative matrices showed significant improvement in prediction over the original nine residue matrix and over the other extended matrix.Proline in the sequence of the peptide library of the better performing matrix presumably stabilizes the peptide conformation through neighbour interactions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computational Biophysics Section, Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892-9314, USA. csparry@helix.nih.gov

ABSTRACT

Background: Eluted natural peptides from major histocompatibility molecules show patterns of conserved residues. Crystallographic structures show that the bound peptide in class II major histocompatibility complex adopts a near uniform polyproline II-like conformation. This way allele-specific favoured residues are able to anchor into pockets in the binding groove leaving other peptide side chains exposed for recognition by T cells. The anchor residues form a motif. This sequence pattern can be used to screen large sequences for potential epitopes. Quantitative matrices extend the motif idea to include the contribution of non-anchor peptide residues. This report examines two new matrices that extend the binding register to incorporate the polymorphic p10 pocket of human leukocyte antigen DR1. Their performance is quantified against experimental binding measurements and against the canonical nine-residue register matrix.

Results: One new matrix shows significant improvement over the base matrix; the other does not. The new matrices differ in the sequence of the peptide library.

Conclusion: One of the extended quantitative matrices showed significant improvement in prediction over the original nine residue matrix and over the other extended matrix. Proline in the sequence of the peptide library of the better performing matrix presumably stabilizes the peptide conformation through neighbour interactions. Such interactions may influence epitope prediction in this test of quantitative matrices. This calls into question the assumption of the independent contribution of individual binding pockets.

Show MeSH
Related in: MedlinePlus