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Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays

Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays

Published on: October 23, 2019

DeepKinomeWeb: a quantitative, panel-level platform for kinase inhibitor screening and selectivity profiling.

Jisu Eun¹, Yeeun Lee², Seunghoon Yang^1,3

¹Bio-design Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Korea.

Nucleic Acids Research

|April 29, 2026

Summary

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This summary is machine-generated.

DeepKinomeWeb is a new platform that helps researchers discover kinase inhibitors. It uses deep learning to analyze screening data, making inhibitor selection faster and more efficient for drug discovery.

Area of Science:

Biochemistry
Computational Biology
Drug Discovery

Background:

Protein kinases are crucial drug targets, but developing selective inhibitors is difficult and expensive.
High-throughput screening data is complex and hard to interpret for early-stage drug development.

Purpose of the Study:

To present DeepKinomeWeb, a web platform for analyzing kinase inhibitor screening data.
To enable quantitative prediction of kinase-inhibitor binding and assess inhibitor selectivity.

Main Methods:

Developed DeepKinomeWeb based on the validated DeepKinome deep learning regression model.
Integrated competition-based screening data analysis with visualization of selectivity landscapes.
Incorporated structural and physicochemical analyses for comprehensive assessment.

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Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays

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Published on: October 23, 2019

Identification of Kinase-substrate Pairs Using High Throughput Screening

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Main Results:

DeepKinomeWeb transforms screening data into actionable insights for inhibitor prioritization.
The platform provides quantitative binding affinity predictions and selectivity metrics.
Offers panel-level visualization of selectivity landscapes.

Conclusions:

DeepKinomeWeb facilitates rational, data-driven decision-making in kinase inhibitor discovery.
Lowers the barrier for systematic selectivity assessment, aiding biologists and medicinal chemists.
Provides a user-friendly interface for efficient drug discovery processes.