H. Bauknecht et al., LOCATING BIOLOGICALLY-ACTIVE COMPOUNDS IN MEDIUM-SIZED HETEROGENEOUS DATASETS BY TOPOLOGICAL AUTOCORRELATION VECTORS - DOPAMINE AND BENZODIAZEPINE AGONISTS, Journal of chemical information and computer sciences, 36(6), 1996, pp. 1205-1213
Citations number
23
Categorie Soggetti
Information Science & Library Science","Computer Application, Chemistry & Engineering","Computer Science Interdisciplinary Applications",Chemistry,"Computer Science Information Systems
Electronic properties located on the atoms of a molecule such as parti
al atomic charges as well as electronegativity and polarizability valu
es are encoded by an autocorrelation vector accounting for the constit
ution of a molecule. This encoding procedure is able to distinguish be
tween compounds being dopamine agonists and those being benzodiazepine
receptor agonists even after projection into a two-dimensional self-o
rganizing network. The two types of compounds can still be distinguish
ed if they are buried in a dataset of 8323 compounds of a chemical sup
plier catalog comprising a wide structural variety. The maps obtained
by this sequence of events, calculation of empirical physicochemical e
ffects, encoding in a topological autocorrelation vector, and projecti
on by a self-organizing neural network, can thus be used for searching
for structural similarity, and, in particular, for finding new lead s
tructures with biological activity.