High‐Throughput Kinetic Analysis for Target‐Directed Covalent Ligand Discovery
Cysteine‐reactive small molecules are used as chemical probes of biological systems and as medicines. Identifying high‐quality covalent ligands requires comprehensive kinetic analysis to distinguish selective binders from pan‐reactive compounds. Quantitative irreversible tethering (qIT), a general m...
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Published in | Angewandte Chemie International Edition Vol. 57; no. 19; pp. 5257 - 5261 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
WEINHEIM
Wiley
04.05.2018
Wiley Subscription Services, Inc John Wiley and Sons Inc |
Edition | International ed. in English |
Subjects | |
Online Access | Get full text |
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Summary: | Cysteine‐reactive small molecules are used as chemical probes of biological systems and as medicines. Identifying high‐quality covalent ligands requires comprehensive kinetic analysis to distinguish selective binders from pan‐reactive compounds. Quantitative irreversible tethering (qIT), a general method for screening cysteine‐reactive small molecules based upon the maximization of kinetic selectivity, is described. This method was applied prospectively to discover covalent fragments that target the clinically important cell cycle regulator Cdk2. Crystal structures of the inhibitor complexes validate the approach and guide further optimization. The power of this technique is highlighted by the identification of a Cdk2‐selective allosteric (type IV) kinase inhibitor whose novel mode‐of‐action could be exploited therapeutically.
A simple high‐throughput fluorescence assay was developed which rapidly identifies high‐affinity covalent fragments by maximizing kinetic selectivity of protein modification. This platform allows electrophiles with different warheads and reactivities to be simultaneously screened. Using this technology, a new class of allosteric Cdk2 inhibitors was discovered which show a unique selectivity profile and have potential therapeutic use. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1433-7851 1521-3773 |
DOI: | 10.1002/anie.201711825 |