You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Discovery of Antiandrogen Activity of Nonsteroidal Scaffolds of Marketed Drugs
W. H. Bisson, A. V. Cheltsov, N. Bruey-Sedano, B. Lin, J. Chen, N. Goldberger, L. T. May, A. Christopoulos, J. T. Dalton, P. M. Sexton, X.-K. Zhang and R. Abagyan
Proceedings of the National Academy of Sciences of the United States of America
Vol. 104, No. 29 (Jul. 17, 2007), pp. 11927-11932
Published by: National Academy of Sciences
Stable URL: http://www.jstor.org/stable/25436226
Page Count: 6
You can always find the topics here!Topics: Ligands, Receptors, Androgen antagonists, Databases, Nuclear receptors, Antipsychotic agents, Scaffolds, Lead, Drug interactions, Agonists
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
Finding good drug leads de novo from large chemical libraries, real or virtual, is not an easy task. High-throughput screening is often plagued by low hit rates and many leads that are toxic or exhibit poor bioavailability. Exploiting the secondary activity of marketed drugs, on the other hand, may help in generating drug leads that can be optimized for the observed side-effect target, while maintaining acceptable bioavailability and toxicity profiles. Here, we describe an efficient computational methodology to discover leads to a protein target from safe marketed drugs. We applied an in silico "drug repurposing" procedure for identification of nonsteroidal antagonists against the human androgen receptor (AR), using multiple predicted models of an antagonist-bound receptor. The library of marketed oral drugs was then docked into the best-performing models, and the 11 selected compounds with the highest docking score were tested in vitro for AR binding and antagonism of dihydrotestosterone-induced AR transactivation. The phenothiazine derivatives acetophenazine, fluphenazine, and periciazine, used clinically as antipsychotic drugs, were identified as weak AR antagonists. This in vitro biological activity correlated well with endocrine side effects observed in individuals taking these medications. Further computational optimization of phenothiazines, combined with in vitro screening, led to the identification of a nonsteroidal antiandrogen with improved AR antagonism and marked reduction in affinity for dopaminergic and serotonergic receptors that are the primary target of phenothiazine antipsychotics.
Proceedings of the National Academy of Sciences of the United States of America © 2007 National Academy of Sciences