Authors: Mukherjee, Subhendu; Saha, Achintya

Source: Current Computer - Aided Drug Design, Volume 2, Number 3, September 2006 , pp. 229-253(25)

Publisher: Bentham Science Publishers

Abstract:

The dimensional expansion in the research domain of Selective Estrogen Receptor (ER) Modulators (SERM) has been driven by discovering molecules with improved endocrine profiles that might be safer and valuable drug candidates for treating variety of estrogen-linked pathologies. Desirable tissue selectivity may result from the unique structural characteristics of a ligand that take advantage of differences in diversities of cell specific factors. The recent discovery of a second ER has provoked the search for ligands which are selective for either the classical ER or newer subtypes. Libraries of compounds, both synthetic and natural are being screened globally for finding ideal SERMs and investigating pharmacophore patterns for apprehending tissue selective parameters. Diverse series of selective synthetic analogs have been developed with high relative binding affinities to the ER as comparable to 17β-estradiol and extensive data sets of phytoestrogens have also been screened for selective binding at the ER surfaces. The successful synthesis, exploration of natural resources and biological testing of SERMs are emerging as vital tools for apprehending the differences in structure and biological functions of ER subtypes as well as for deducing pharmacophore maps of estrogenic analogs through application of virtual molecular modeling applications. Several approaches in calculating ligand-binding affinities have been used over the past decade, ranging from molecular field analysis studies to protein-based methods using empirical scoring functions. One of the most promising areas in present day computational chemistry that has further aided the understanding of mechanistic aspects of estrogenic activity, is the characterization of molecular properties and bio-activities by means of structurebased descriptors generated from theoretical improvement and computational applications that eventually lead to construction of quantitative SAR related to molecular features by statistical procedures. Consequently, this paper overviews the properties investigated towards explaining tissue selectivity of estrogens and structural homology patterns of active analogs on precision based In silico approaches. This review also takes into account some our ongoing research efforts in this area that have contributed significant findings.

Keywords: Selective estrogen receptor modulator; molecular modeling; pharmacophore; descriptor; QSAR; docking; molecular field and similarity analysis

Document Type: Research article

DOI: http://dx.doi.org/10.2174/157340906778226391

Affiliations: 1: Department of Chemical Technology, University of Calcutta, 92, A.P.C. Road, Kolkata - 700 009, India.

Publication date: 2006-09-01

More about this publication?

• Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.

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