Open AccessDiscovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning
Author(s) -
Merk Daniel,
Grisoni Francesca,
Schaller Kay,
Friedrich Lukas,
Schneider Gisbert
Publication year - 2019
Publication title -
chemistryopen
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.644
H-Index - 29
ISSN - 2191-1363
DOI - 10.1002/open.201800270
Subject(s) - farnesoid x receptor , pharmacophore , cover (algebra) , chemical space , computer science , artificial intelligence , artificial neural network , k nearest neighbors algorithm , machine learning , chemistry , nuclear receptor , engineering , drug discovery , stereochemistry , biochemistry , transcription factor , gene , mechanical engineering
Invited for this month's cover picture is the group of Prof. Dr. Gisbert Schneider from the Swiss Federal Institute of Technology (ETH) Zurich (Switzerland). The cover picture illustrates the application of machine‐learning methods to expand the chemical space of farnesoid X receptor (FXR)‐targeting small molecules, by employing an ensemble of three complementary machine‐learning approaches (counter‐propagation artificial neural network, k‐nearest neighbor learner, and three‐dimensional pharmacophore model). Read the full text of their Full Paper at 10.1002/open.201800156 .