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A Novel High-Throughput FLIPR Tetra-Based Method for Capturing Highly Confluent Kinetic Data for Structure-Kinetic
Puneet Khurana1, Lisa McWilliams1, Jonathan Wingfield1
1Mechanistic Biology and Profiling, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK.
SLAS Discovery : Advancing Life Sciences R & D
|March 30, 2021
Summary
This study introduces a high-throughput method using fluorescent imaging plate reader (FLIPR) technology to rapidly collect kinetic data for drug discovery. This approach enables early-stage structure-kinetic relationship (SKR) analysis, optimizing candidate selection for clinical trials.
Area of Science:
- Biochemistry
- Pharmacology
- Drug Discovery
Background:
- Small molecule target engagement is crucial for physiological outcomes.
- Traditionally, thermodynamics guided structure-activity relationships (SAR), but kinetics are now recognized as critical.
- High-throughput kinetic data acquisition is limited by traditional methods, delaying key decisions in drug discovery.
Purpose of the Study:
- To develop a high-throughput method for biochemical kinetic data acquisition.
- To enable early-stage structure-kinetic relationship (SKR) analysis for drug candidate optimization.
- To overcome limitations in traditional kinetic data collection for time-course analysis.
Main Methods:
- Utilized fluorescent imaging plate reader (FLIPR) with charge-coupled device (CCD) camera technology.
- Designed and optimized assays for kinetic data collection with small time intervals.
- Collected confluent time-course data for kinase targets and analyzed kinetic parameters.
Main Results:
- Demonstrated FLIPR's potential for high-throughput kinetic data generation.
- Successfully collected time-course data for kinase targets, enabling SKR-guided medicinal chemistry.
- Showcased rapid kinetic data analysis for parameter estimation, including a covalent inhibition case study.
Conclusions:
- The FLIPR-based approach enables rapid kinetic studies on hundreds of compounds weekly.
- This method facilitates early-stage project decisions driven by kinetic data.
- Accelerates the drug discovery process by integrating kinetic insights earlier.

