Kinase selectivity potential for inhibitors targeting the ATP binding site: a network analysis

Area of Science:

• Biochemistry
• Structural Biology
• Drug Discovery

Background:

• Small-molecule inhibitors targeting the adenosine triphosphate (ATP) binding pocket of protein kinases offer potential for reduced side effects if selective.
• Developing selective inhibitors is a key challenge in kinase-targeted drug discovery.

Purpose of the Study:

• To develop a computational method for predicting the potential of kinases to yield selective inhibitors.
• To identify specific kinases with high potential for selective inhibitor development.

Main Methods:

• Mapping sequences of 518 human kinases onto a structural alignment of 116 known kinase structures.
• Encoding known selective inhibitor strategies into a fingerprint based on structural alignment.
• Utilizing network analysis to cluster kinases by fingerprint similarity and predict inhibitor selectivity.

Main Results:

• Network analysis successfully predicts the likelihood of finding selective inhibitors for individual kinases.
• Systematic guidelines for developing selective kinase inhibitors are proposed.
• The tyrosine kinase EphB4 is identified as a high-potential target for selective inhibitors, supported by experimental data.

Conclusions:

• The developed network analysis approach effectively predicts kinase selectivity potential.
• This method provides a framework for rational drug design targeting kinases.
• EphB4 represents a promising target for developing novel, selective kinase inhibitors.