A robust CETSA data analysis automation workflow for routine screening.

Area of Science:

• Biochemistry
• Pharmacology
• Drug Discovery

Background:

• Cellular Thermal Shift Assay (CETSA) is crucial for studying protein-ligand interactions in cells.
• CETSA provides insights into binding affinity and specificity of small and large molecules.
• Current data analysis and quality control for CETSA are laborious, limiting high-throughput screening.

Purpose of the Study:

• To develop a scalable and robust data analysis workflow for integrating CETSA into routine high-throughput screening (HT-CETSA).
• To automate data analysis and quality control processes for CETSA experiments.

Main Methods:

• Introduction of a novel, automated data analysis workflow for CETSA.
• Incorporation of automated quality control (QC) measures, including outlier detection, sample and plate QC, and result triage.
• Validation of the workflow's robustness against experimental artifacts and assessment of scaling effects.

Main Results:

• The automated workflow enables scalable and robust data analysis for HT-CETSA.
• The workflow effectively automates data processing, reducing manual effort and potential errors.
• Demonstrated robustness against common experimental artifacts and analyzed scaling effects.

Conclusions:

• The developed workflow significantly enhances the throughput and reliability of CETSA for drug discovery.
• Automation of data analysis and QC is key to integrating CETSA into routine high-throughput screening.
• This approach facilitates more efficient and accurate assessment of protein-ligand interactions.