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

被引:36
作者
Poroikov, V
Akimov, D
Shabelnikova, E
Filimonov, D
机构
[1] Russian Acad Med Sci, Inst Biomed Chem, Moscow 119832, Russia
[2] Russian State Med Univ, Med & Biol Fac, Moscow 117869, Russia
关键词
biological activity spectra; Top; 200; medicines; side effect; toxicity; computer-aided prediction; PASS;
D O I
10.1080/10629360108033242
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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 predicted activity spectra in 93.2% of cases. Additionally, the probability of some supplementary effects was also predicted to be significant, including angiogenesis 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 pharmaceuticals from the Top 200 list. Most of known side and toxic effects were also predicted by PASS. PASS predictions at earlier R & D stages may thus provide a basis for finding new "leads" among already launched drugs and may help direct more attention to those particular effects of pharmaceuticals in clinical use which become apparent only in a small part of the population and require additional precautions.
引用
收藏
页码:327 / 344
页数:18
相关论文
共 12 条
[1]   Chemical similarity assessment through multilevel neighborhoods of atoms: definition and comparison with the other descriptors [J].
Filimonov, D ;
Poroikov, V ;
Borodina, Y ;
Gloriozova, T .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1999, 39 (04) :666-670
[2]  
Filimonov D. A., 1996, Bioactie Compound Design: Possibilities for Industrial Use, P47, DOI DOI 10.1128/MCB.00552-09
[3]   A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases [J].
Ghose, AK ;
Viswanadhan, VN ;
Wendoloski, JJ .
JOURNAL OF COMBINATORIAL CHEMISTRY, 1999, 1 (01) :55-68
[4]  
KUBINYI H, 1997, 3D QSAR DRUG DESIGN, V3
[5]  
KUBINYI H, 1997, 3D QSAR DRUG DESIGN, V2
[6]  
MAGGON KK, 1992, DRUG NEWS PERSPECT, V5, P261
[7]   Robustness of biological activity spectra predicting by computer program PASS for noncongeneric sets of chemical compounds [J].
Poroikov, VV ;
Filimonov, DA ;
Borodina, YV ;
Lagunin, AA ;
Kos, A .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2000, 40 (06) :1349-1355
[8]  
POROIKOV VV, 1996, CHIM PHARM J, V30, P20
[9]  
*US PHARM, 2000, DRUG INF HEALTHC PRO
[10]  
van de Waterbeemd H., 1996, Structure Property Correlations in Drug Research