Top 200 medicines: Can new actions be discovered through computer-aided prediction?

Citation
V. Poroikov et al., Top 200 medicines: Can new actions be discovered through computer-aided prediction?, SAR QSAR EN, 12(4), 2001, pp. 327-344
Citations number
12
Categorie Soggetti
Chemistry
Journal title
SAR AND QSAR IN ENVIRONMENTAL RESEARCH
ISSN journal
1062936X → ACNP
Volume
12
Issue
4
Year of publication
2001
Pages
327 - 344
Database
ISI
SICI code
1062-936X(2001)12:4<327:T2MCNA>2.0.ZU;2-H
Abstract
Computer-aided prediction of the biological activity spectra by the program PASS was applied to a set of 130 pharmaceuticals from the list of the Top 200 medicines. The known pharmacological effects were found in the predicte d activity spectra in 93.2% of cases. Additionally, the probability of some supplementary effects was also predicted to be significant, including angi ogenesis inhibition, bone formation stimulation, possible use in cognition disorders treatment, multiple sclerosis treatment, etc. These predictions. if confirmed experimentally, may become a cause for a new application of ph armaceuticals from the Top 200 list. Most of known side and toxic effects w ere also predicted by PASS. PASS predictions at earlier R & D stages may th us provide a basis for finding new "leads" among already launched drugs and may help direct more attention to those particular effects of pharmaceutic als in clinical use which become apparent only in a small part of the popul ation and require additional precautions.