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Hit Expansion through Computational Selectivity Searching
Author(s) -
Stumpfe Dagmar,
Frizler Maxim,
Sisay Mihiret T.,
Batista José,
Vogt Ingo,
Gütschow Michael,
Bajorath Jürgen
Publication year - 2009
Publication title -
chemmedchem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.817
H-Index - 100
eISSN - 1860-7187
pISSN - 1860-7179
DOI - 10.1002/cmdc.200800304
Subject(s) - in silico , identification (biology) , virtual screening , computer science , cathepsin , computational biology , selectivity , task (project management) , information retrieval , chemistry , drug discovery , biology , bioinformatics , gene , biochemistry , enzyme , engineering , catalysis , botany , systems engineering
Finding small molecules that are selective for individual target proteins within target families is an important task. Thus far, computational screening methods have contributed very little to the identification of such molecules. We introduce in silico selectivity searching for the identification of cathepsin K inhibitors. By computational analysis, 16 candidates out of 3.7 million database compounds were selected and tested, and two inhibitors were identified that showed on average fivefold selectivity for cathepsin K over cathepsins S and L. One of these inhibitors represents a previously unobserved chemotype.