Generic placeholder image

Combinatorial Chemistry & High Throughput Screening


ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

A Neural Network Based Virtual High Throughput Screening Test for the Prediction of CNS Activity

Author(s): Gyorgy M. Keseru, Laszlo Molnar and Istvan Greiner

Volume 3, Issue 6, 2000

Page: [535 - 540] Pages: 6

DOI: 10.2174/1386207003331346

Price: $65


A virtual high throughput screening test to identify potentially CNS-active drugs has been developed. Discrimination was based on the knowledge available in databases containing CNS-active (Cipsline from Prous Science) and inactive compounds (Chemical Directory from Sigma-Aldrich). Molecular structures were represented using 2D Unity fingerprints and a feedforward neural network was trained to classify molecules regarding their CNS activity. The parameterized network was validated by reclassification of the training set elements, by the classification of a test set preselected from the Prous database, and also by the prediction of activity for known CNS drugs not used in the training set but available in the Medchem database (Daylight).These tests revealed that our neural net recognized at least 89% of CNS-active compounds and would be suitable for use in our virtual screening protocol.

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy