Loading…

Novel Aromatase Inhibitors by Structure-Guided Design

Human cytochrome P450 aromatase catalyzes with high specificity the synthesis of estrogens from androgens. Aromatase inhibitors (AIs) such as exemestane, 6-methylideneandrosta-1,4-diene-3,17-dione, are preeminent drugs for the treatment of estrogen-dependent breast cancer. The crystal structure of h...

Full description

Saved in:
Bibliographic Details
Published in:Journal of medicinal chemistry 2012-10, Vol.55 (19), p.8464-8476
Main Authors: Ghosh, Debashis, Lo, Jessica, Morton, Daniel, Valette, Damien, Xi, Jingle, Griswold, Jennifer, Hubbell, Susan, Egbuta, Chinaza, Jiang, Wenhua, An, Jing, Davies, Huw M. L
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Human cytochrome P450 aromatase catalyzes with high specificity the synthesis of estrogens from androgens. Aromatase inhibitors (AIs) such as exemestane, 6-methylideneandrosta-1,4-diene-3,17-dione, are preeminent drugs for the treatment of estrogen-dependent breast cancer. The crystal structure of human placental aromatase has shown an androgen-specific active site. By utilization of the structural data, novel C6-substituted androsta-1,4-diene-3,17-dione inhibitors have been designed. Several of the C6-substituted 2-alkynyloxy compounds inhibit purified placental aromatase with IC50 values in the nanomolar range. Antiproliferation studies in a MCF-7 breast cancer cell line demonstrate that some of these compounds have EC50 values better than 1 nM, exceeding that for exemestane. X-ray structures of aromatase complexes of two potent compounds reveal that, per their design, the novel side groups protrude into the opening to the access channel unoccupied in the enzyme–substrate/exemestane complexes. The observed structure–activity relationship is borne out by the X-ray data. Structure-guided design permits utilization of the aromatase-specific interactions for the development of next generation AIs.
ISSN:0022-2623
1520-4804
DOI:10.1021/jm300930n