Premium
Confirmation of predicted activity for factor XIa inhibitors from a virtual screening approach
Author(s) -
Li Hang,
Visco Donald P.,
Leipzig Nic D.
Publication year - 2014
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.14508
Subject(s) - virtual screening , signature (topology) , fraction (chemistry) , factor (programming language) , computer science , throughput , data mining , information retrieval , chemistry , machine learning , mathematics , chromatography , stereochemistry , operating system , programming language , geometry , wireless , pharmacophore
Significance High‐throughput screening approaches, where hundreds of thousands of compounds are evaluated in microamounts for their activity against certain targets, can regularly result in hit rates that are only a fraction of a percent. Here, we take a previously developed machine‐learning classification model (with the Signature molecular descriptor) used to identify active compounds against Factor XIa and experimentally verify the virtual screening model predictions. Of 21 predicted compounds tested, seven show activity against Factor XIa, a 33% hit rate. © 2014 American Institute of Chemical Engineers AIChE J , 60: 2741–2746, 2014