title: Prediction of CNS activity of compound libraries using substructure analysis.
abstract: An in silico ADME/Tox prediction tool based on substructural analysis has been developed. The tool called SUBSTRUCT has been used to predict CNS activity. Data sets with CNS active and nonactive drugs were extracted from the World Drug Index (WDI). The SUBSTRUCT program predicts CNS activity as good as a much more complicated artificial neural network model. SUBSTRUCT separates the data sets with approximately 80% accuracy. Substructural analysis also shows surprisingly large differences in substructure profiles between CNS active and nonactive drugs.
authors.affiliation: CallistoGen AG, Neuendorfstrasse 24b, D-16761 Hennigsdorf, Germany. engkvist@axxima.com
authors.forename: Ola
authors.initials: O
authors.lastname: Engkvist
authors.forename: Paul
authors.initials: P
authors.lastname: Wrede
authors.forename: Ulrich
authors.initials: U
authors.lastname: Rester
mesh_terms: D001812:Blood-Brain Barrier / Q000187:drug effects; D002491:Central Nervous System Agents / Q000737:chemistry* / Q000494:pharmacology*; D015195:Drug Design; D008956:Models, Chemical; D015394:Molecular Structure; D016571:Neural Networks, Computer; D021281:Quantitative Structure-Activity Relationship; D012984:Software
chemical_list: D002491:Central Nervous System Agents