Phosphoprotein Binding - Peptide Microar

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Proteomic Peptide Microarray Technology for Phosphoprotein Binding Studies

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Or, dye-conjugated secondary Ab Phosphoprotein binding (PPBP) protein contains PPB domains (PPBD) which binds to phosphorylation sites in PPBP or phosphopeptide (PPEP). SH2 is an example of PPBD which recognizes phosphorylated tyrosine (pY); over 100 SH2 PPBDs are found in human proteome (1-3). Peptide on chip GST-SH2 Dye-labeled antibody Pros-and-cons of indirect vs direct labeling Protein stability in labeling reaction Simplicity of the experiment Specificity of the detection Economics Protein Detection through Domain Protein Binding PPBD and PPEP Binding assay X-ray structure of SH2 P P GST-SH2 P GST-SH2

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Domain-Binding Optimization – the Combined Use of Experimental and Computational Methods An 8-step EXPT-COMP working model

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PepCyber web page - http://pepcyber.umn.edu/PPEP Web Accessible PepCyber Database Interaction Search: PPEP-PPBP interaction table PPEP-PPBP Interaction Database Coverage Comparison Gong, W., Zhou, D., Ren, Y., Wang, Y., Zuo, Z., Shen, Y., Xiao, F., Zhu, Q., Hong, A., Zhou, X., Gao, X and Li, T. (2008) PepCyber:P~PEP: a database of human protein interactions mediated by phosphoprotein-binding domains. Nucleic Acids Res , 36 , D679-683. Wan, J., Kang, S., Tang, C., Yan, J., Ren, Y., Liu, J., Gao, X., Banerjee, A., Ellis, L.B. and Li, T. (2008) Meta-prediction of phosphorylation sites with weighted voting and restricted grid search parameter selection. Nucleic Acids Res doi:10.1093.

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High-density pY-phosphopeptide and pico-liter titer plate arrays have been Established Two major types of PPEP chips are developed: Pico-liter titer plate array – containing less number of sequences than the profiling array (see below). Peptides are, which are organized in a format of 96 well plate. The repeating sequences of the same peptide are synthesized on surface of different molecular densities and thus are presented at different “concentrations”. A 40 plate array means one chip (120 x 31 reaction sites) designed to contain the molecular content equivalent to 40 conventional 96-well plates. Profiling array – containing a large set of phosphopeptides for purposes of binding assays.

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Clustering analysis of peptide array binding data: Shown in plots #1 to #7 are clusters generated using K-means calculation (TIGR Multiple Experiment Viewer). The data sets were results of two peptide array binding using SHP2-2SH2 (left column) or SRC-SH2 (right column). The color scheme is -3.0 (green color) = weakest binding and 3.0 = strongest (red color) binding. 1 2 3 4 5 6 7 Legend Binding Pattern Analysis Target-specific signature peptides identification

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Illustration of the presence of cell growth receports and the activities of signaling proteins (SHP-2, Grb2, Csk, Src, etc.) in cell growth related pathways. The roles of CagA are only postulations at this time.

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CSH2 NSH2 2CH2 -3.0 0.0 3.0 CagA-B Gab1-659 IRS-1 AFAP110-3 Gab-3 FRS2-392 PDGFRB_Y1009 STAT301642 CagA-A Met2 SRC-1589 IL-6R-1 Figure 2. Illustration of diagnostic patterns from a SH2 binding phosphopeptide microarray. Specific binding patterns from “signature” peptides allow the differentiation of different SH2 proteins.

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2/14/2008 070086Qi Figure 3. Representative binding curves derived from a peptide array containing 40 pico-liter titer plates (96-well each) . Signal fluorescence intensity data processing further corrected for different synthesis efficiencies of different peptides. Table insert lists the peptides and their binding constant (EC50) determined from the plots. Fluorescence Signal (A.U) Relative Density of Phosphopeptide on Surface Figure 3. Binding curves derived from a peptide array containing 40 pico-liter titer plates (96-well each) . Signal fluorescence intensity data processing corrected for different synthesis efficiencies of different peptides. Binding assay used N-terminal SH2 of SHP2 (GST-NSH2, 100 mM), detected by anti-GST and cy5-IgG staining. Data processing of fluorescence signal involved baseline correction, replicate signal averaging, subtraction of control peptide signal (pY-A substitution peptides), synthesis efficiency correction (using the dimer synthesis efficiency table), and sigmoidal curve fitting using SigmaPlot.

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Profiling Array - SH2 binding to PPEP CagA from H. pylori exhibits cellular activities against SHP-2 (a phosphatase enzyme) which contains two SH2 (NSH2 and CSH2) domains. PPEP array contains CagA peptides and other families SH2-binding PPEPs.

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SHP1 SHP2 CagA STAT SRC Other Predicted non SHP-2 binding Binding specificity of SHP2-N-terminal SH2 versus p85a C-terminal SH2 Profiling Array – SHP2-NSH2 and P85a CSH2 binding to PPEP

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Comparison of the experimental data and prediction results SHP2 NSH2-PPEP: Weblogos display compositional preference of the preferred binding site. There is a general agreement between the experimental and the SVR modeling results. We are in process of adjust the experimental design and the computation cycles, aiming to identify and validate signature peptides for specific SH2 domain protein binding. The whole set used in chip:

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The program package (uPepChip Pro) for peptide array applications now has the functions for array design (peptide sequence selection, design, and writing), and for quantitative data analysis and advanced profile modeling based on Support Vector machine Regression (SVR). mPepChip Pro web page shown below demonstrates the [Array Design] function (indicated by a red arrow and a five step process for peptide sequence search and array layout design. Peptide Array Design Software (mPepChip Pro)

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Peptide Array Design Software (mPepChip Pro) has been Established The need – huge amount of bioinformatic work – standardization of array applications

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Peptide Array Design Software (mPepChip Pro) has been Established PepCyber web page - http://pepcyber.umn.edu/PepCyber.

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Representative plots obtained from pico-liter titer plate chips for quantitative binding measurements The binding constant (Kd) will be calibrated using SH2 and PPEPs of known binding properties. It is expected that the solid surface binding is not identical to that in solution, but this offset can be calibrated to corrected for the deviation from the solid surface reaction effect.

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First study: SVR modeling of peptide binding with Major Histocompatibility Complex (MHC) Predictive Computational Modeling Of Peptide Binding data – test case A problem in immunoinformatics, similar needs Is an “old” problem: >15 years in development, easy to compare with established methods Can compare with the best methods in the field: (1) 3D-QSAR based method; (2) LG-based “additive method” Tested on three mouse class I MHC alleles: H2-Db, H2-Kb and H2-Kk; compared the constructed SVR models with established additive models (LG-based) constructed using the same datasets

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First study: SVR modeling of peptide binding with Major Histocompatibility Complex (MHC) Predictive Computational Modeling Of Peptide Binding data – test case Results: SVR modeling consistently achieved best predicted binding affinity data