药物发现
片段(逻辑)
计算生物学
化学生物学
药品
计算机科学
结构生物学
化学
生物
生物化学
算法
药理学
作者
Tiago Rodrigues,Daniel Reker,M. Welin,Michael Caldera,Cyrill Brunner,Gisela Gabernet,Petra Schneider,Björn Walse,Gisbert Schneider
标识
DOI:10.1002/anie.201508055
摘要
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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