期刊
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
卷 54, 期 50, 页码 15079-15083出版社
WILEY-V C H VERLAG GMBH
DOI: 10.1002/anie.201508055
关键词
chemical biology; computational chemistry; kinases; molecular design; target prediction
资金
- ETH Zurich
- OPO Foundation, Zurich, Switzerland
Automated molecular de novo design led to the discovery of an innovative inhibitor of death-associated protein kinase 3 (DAPK3). An unprecedented crystal structure of the inactive DAPK3 homodimer shows the fragment-like hit bound to the ATP pocket. Target prediction software based on machine learning models correctly identified additional macromolecular targets of the computationally designed compound and the structurally related marketed drug azosemide. The study validates computational de novo design as a prime method for generating chemical probes and starting points for drug discovery.
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