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Predicting Compound Selectivity by Self‐Organizing Maps: Cross‐Activities of Metabotropic Glutamate Receptor Antagonists
Author(s) -
Noeske Tobias,
Sasse Britta C.,
Stark Holger,
Parsons Christopher G.,
Weil Tanja,
Schneider Gisbert
Publication year - 2006
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.200600147
Subject(s) - pharmacophore , metabotropic glutamate receptor , virtual screening , metabotropic glutamate receptor 5 , metabotropic receptor , metabotropic glutamate receptor 4 , metabotropic glutamate receptor 2 , metabotropic glutamate receptor 1 , chemistry , artificial intelligence , computer science , computational biology , neuroscience , receptor , glutamate receptor , biology , stereochemistry , biochemistry
A topological pharmacophore descriptor (CATS) and a self‐organizing map (SOM) were used for prediction of multiple receptor interaction of known mGluR antagonists. For a predicted target panel, the tested mGluR ligands exhibited the calculated binding pattern. This virtual screening concept might provide a basis for early recognition of potential side‐effects in lead discovery.