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New analysis pipeline for high-throughput domain-peptide affinity experiments improves SH2 interaction data
Tom Ronan1, Roman Garnett2, Kristen M Naegle3
1Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.
The Journal of Biological Chemistry
|June 17, 2020
Summary
This study revises analysis methods for high-throughput (HTP) experiments measuring protein domain interactions, like Src homology 2 (SH2) domains with phosphotyrosine (pTyr) peptides. Improved analysis yields more accurate affinity measurements and reliable binding data for cellular processes.
Area of Science:
- Biochemistry
- Proteomics
- Molecular Biology
Background:
- Protein domain interactions, such as SH2 domains with pTyr peptides, are crucial for cellular functions.
- High-throughput (HTP) techniques have advanced the study of these interactions, but data variability and inconsistencies persist.
Purpose of the Study:
- To reevaluate analysis methods and raw data from published SH2-pTyr HTP experiments.
- To improve the accuracy of affinity measurements and the identification of positive/negative interactions.
- To develop a robust analysis pipeline for future domain-peptide interaction studies.
Main Methods:
- Implemented statistically appropriate model-fitting techniques for nonlinear SH2-pTyr interaction data.
- Developed a method to correct for protein concentration errors (impurities, degradation, aggregation).
- Applied machine-learning techniques to assess binding classification improvement.
Main Results:
- Revised analysis enhanced affinity accuracy and reduced false-negative rates.
- Increased the amount of useful data by including reliable true-negative results.
- Demonstrated improved binding classification accuracy, indicating enhanced data coherence.
Conclusions:
- The revised analysis pipeline provides more accurate and reliable data for SH2-pTyr interactions.
- This approach offers a standardized method for future HTP measurements of domain-peptide interactions.
- Improved data quality facilitates a deeper understanding of cellular biochemical processes.
