Document Detail


Computational methods for the design of potent aromatase inhibitors.
MedLine Citation:
PMID:  23373669     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
INTRODUCTION: It has long been considered that the most significant risks for breast cancer are gender and age but, as many other tumors, this cancer has also been undeniably linked to gene mutations. The vast majority of breast cancers in postmenopausal women are estrogen-responsive, a hormone which is biosynthesized from blood-circulating androgens through an aromatization reaction, catalyzed by aromatase (AR). One strategy, therefore, to combat breast cancer, has been to find compounds that can inhibit the activity of aromatase to reduce estrogen levels.
AREAS COVERED: The authors provide a broad and updated overview of the general structure-activity relationships and on the latest ligand- and structure-based approaches applied to the discovery of potent, selective and safer breast cancer drugs. Specifically the authors review the most consolidated techniques, based on structure-activity relationships, pharmacophore mapping, rigid and flexible molecular docking, as well as sophisticated and reliable protocols simulating critical biological events.
EXPERT OPINION: The recently solved X-ray structures of aromatase represent solid milestones to breathe new life into the search of newer chemotypes with reduced risks of cross-reactivity toward other CYPs and safer pharmacological profiles. We anticipate that great benefits will arrive from the wealth of information obtained by integrating genomics, site-directed mutagenesis experiments with protein modeling. Furthermore, we welcome the advent of GPU technology that, in conjunction with dedicated algorithms, grants scientists an unprecedented point of view on physiologically relevant phenomena, occurring on the µs time scale, such as ligand binding/unbinding.
Authors:
Angelo Danilo Favia; Orazio Nicolotti; Angela Stefanachi; Francesco Leonetti; Angelo Carotti
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Review     Date:  2013-02-04
Journal Detail:
Title:  Expert opinion on drug discovery     Volume:  8     ISSN:  1746-045X     ISO Abbreviation:  Expert Opin Drug Discov     Publication Date:  2013 Apr 
Date Detail:
Created Date:  2013-03-20     Completed Date:  2013-08-13     Revised Date:  2013-11-06    
Medline Journal Info:
Nlm Unique ID:  101295755     Medline TA:  Expert Opin Drug Discov     Country:  England    
Other Details:
Languages:  eng     Pagination:  395-409     Citation Subset:  IM    
Affiliation:
Dipartimento di Farmacia, Università degli Studi di Bari Aldo Moro, via Orabona 4, I-70125 Bari, Italy. angelo.carotti@uniba.it
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MeSH Terms
Descriptor/Qualifier:
Antineoplastic Agents, Hormonal / chemistry*,  pharmacology
Aromatase Inhibitors / chemistry*,  pharmacology
Breast Neoplasms / drug therapy*
Computer Simulation*
Drug Design*
Drug Screening Assays, Antitumor / methods
Estrogens / pharmacology
Female
Humans
Structure-Activity Relationship
Chemical
Reg. No./Substance:
0/Antineoplastic Agents, Hormonal; 0/Aromatase Inhibitors; 0/Estrogens

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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