MolPharm xPharm- The Comprehensive Pharmacology Reference

Home Help [Feedback] [For Subscribers] [Archive] [Search] [Contents]
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Full Text (PDF)
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Schmidt, A. W.
Right arrow Articles by Peroutka, S. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Schmidt, A. W.
Right arrow Articles by Peroutka, S. J.

Quantitative molecular analysis predicts 5-hydroxytryptamine3 receptor binding affinity

AW Schmidt and SJ Peroutka

Department of Neurology, Stanford University Medical Center, California 94305.

A quantitative molecular model was derived to predict drug affinities for 5-hydroxytryptamine3 (5-HT3) receptors. The model was based on the molecular characteristics of a "learning set" of 40 pharmacological agents that had been analyzed previously in radioligand binding studies. Molecules were analyzed for various structural features, i.e., the presence of a benzenoid ring and nitrogen atom, substitutions on the benzenoid ring, the location of the substitutions on the nitrogen, and the molecular characteristics of the most direct pathway from the benzenoid ring to the nitrogen. Weighting factors, based on published 5- HT3 receptor affinity data, were then assigned to each of 10 molecular characteristics. The derived computational model predicts accurately the affinities of the learning set for the 5-HT3 receptor (r = 0.98; p less than 0.001). The computational model was then used to predict the receptor affinities of a "test set" of 40 pharmacological agents. The predicted values for these agents also correlate significantly (r = 0.83; p less than 0.001) with drug affinities for the 5-HT3 receptor, as determined by radioligand binding assays. This first line screening approach allows for the accurate prediction of drug affinities based on molecular characteristics with minimal dependence upon animal tissues or radioactivity.

Volume 38, Issue 4, pp. 511-516, 10/01/1990
Copyright © 1990 by American Society for Pharmacology and Experimental Therapeutics




This article has been cited by other articles:


Home page
 J. Pharmacol. Exp. Ther.Home page
W. A. Hewlett, B. L. Trivedi, Z.-J. Zhang, T. de Paulis, D. E. Schmidt, D. M. Lovinger, M. S. Ansari, and M. H. Ebert
Characterization of (S)-Des-4-amino-3-[125I]iodozacopride ([125I]DAIZAC), a Selective High-Affinity Radioligand for 5-Hydroxytryptamine3 Receptors
J. Pharmacol. Exp. Ther., January 1, 1999; 288(1): 221 - 231.
[Abstract] [Full Text]


Home Help [Feedback] [For Subscribers] [Archive] [Search] [Contents]
All ASPET Journals Molecular Pharmacology Pharmacological Reviews
Molecular Interventions Drug Metabolism and Disposition

Copyright © 1990 by the American Society for Pharmacology and Experimental Therapeutics