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Updated: Feb 14, 2026

Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays
Published on: October 23, 2019
A printable hydrogel microarray for drug screening avoids false positives associated with promiscuous aggregating
Rabia Mateen1, M Monsur Ali2, Todd Hoare3,4
1School of Biomedical Engineering, McMaster University, Hamilton, ON, L8S 4K1, Canada.
This study introduces a novel hydrogel platform for drug screening. It accurately distinguishes true enzyme inhibitors from false positives caused by aggregating compounds, accelerating drug discovery.
Area of Science:
- Biochemistry
- Materials Science
- Drug Discovery
Background:
- High-throughput drug screening often yields false positives from promiscuous inhibitors that form colloidal aggregates.
- These aggregating compounds nonspecifically inhibit enzymes, hindering the identification of viable drug candidates.
Purpose of the Study:
- To develop a printable hydrogel-based platform for accurate differentiation of true enzyme inhibitors from promiscuous aggregating inhibitors.
- To accelerate the drug discovery process by improving the reliability of high-throughput screening.
Main Methods:
- A printable hydrogel platform was developed to immobilize and stabilize enzymes.
- The hydrogel platform was integrated into a microarray format for high-throughput screening.
- Enzyme activity and inhibitor dose-response relationships were quantified using the hydrogel assay.
Main Results:
- The hydrogel platform successfully differentiated true inhibitors from aggregating compounds.
- Enzymes immobilized in hydrogels retained activity despite drying, protease, or chemical denaturant treatment.
- The assay rapidly (<25 min) and inexpensively identified promising lead compounds using 95% less sample than solution assays.
Conclusions:
- The printable hydrogel platform offers a robust solution for identifying true enzyme inhibitors in drug discovery.
- This technology significantly reduces false positives and sample consumption in high-throughput screening.
- The platform accelerates the identification of clinically relevant drug leads with accurate dose-response quantification.
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