Quantifying Protein Kinase Activity via Peptide Grouping
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Solution Overview
Problem
Current methods for inferring protein kinase activity from phosphoproteomics data are unreliable due to noisy data from dynamic protein phosphorylation and variables like circadian clock and cell handling effects, making it challenging to accurately quantify kinase activity.
Innovation Solution
A method involving grouping modified peptides from samples based on shared protein modifying enzymes or modification motifs, calculating enrichment, and determining statistical significance to infer protein kinase activity, using MS-based techniques for data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If phosphoproteomics data is used to infer kinase activity, then kinase activity can be estimated, but the data becomes noisy and unreliable due to dynamic phosphorylation and experimental variables
Solution Approach 1:
The method segments the phosphoproteomics data by grouping phosphorylation sites according to their known kinase substrates or modification motifs. This segmentation allows analysis of phosphorylation patterns specific to individual kinases rather than treating all phosphorylation events uniformly, thereby improving the reliability of kinase activity inference from noisy global phosphoproteomics data
Solution Approach 2:
The invention uses known kinase substrates and modification motifs as intermediaries to connect phosphoproteomics measurements to kinase activity. By measuring phosphorylation at these specific intermediary sites with known kinase specificity, the method indirectly infers kinase activity while filtering out noise from non-specific phosphorylation events
2Adaptability or versatility
If multiple kinases are considered to phosphorylate the same substrates, then comprehensive kinase-substrate relationships are captured, but the ability to accurately attribute phosphorylation to specific kinases decreases
Solution Approach 1:
The method segments phosphorylation sites into groups based on their association with specific kinases or modification motifs. By creating distinct groups for different kinases and their preferred motifs, the approach maintains comprehensive coverage of kinase-substrate relationships while enabling precise attribution of phosphorylation events to specific kinases through motif-specific analysis
Solution Approach 2:
The invention applies local quality by analyzing phosphorylation patterns with respect to specific modification motifs that are characteristic of individual kinases. Instead of treating all phosphorylation sites uniformly, the method examines local sequence contexts and motif preferences to accurately attribute phosphorylation to the responsible kinase, even when multiple kinases can modify the same substrate
Data Source
AI summary
The present invention provides a method of quantifying the activity of a protein modifying enzyme in a sample, comprising: (i) grouping modified peptides from a first sample and modified peptides from a second sample into a single group according to one of the following parameters: (a) modified peptides having a modification site that is modified by the same protein modifying enzyme; or (b) modified peptides having a modification site that is part of the same modification motif; (ii) calculating enrichment of the modified peptides from the first sample compared to the modified peptides from the second sample in the group; and (iii) calculating the statistical significance of said enrichment; wherein a statistically significant enrichment is indicative of a protein modifying enzyme being activated in the first sample compared to the second sample. In some embodiments, the method further comprises identifying modified peptides in a first sample and a second sample using mass spectrometry (MS) prior to step (i).