Literature DB >> 17328537

Pharmacophore mapping of selective binding affinity of estrogen modulators through classical and space modeling approaches: exploration of bridged-cyclic compounds with diarylethylene linkage.

Subhendu Mukherjee1, Shuchi Nagar, Sanchita Mullick, Arup Mukherjee, Achintya Saha.   

Abstract

Research on Selective Estrogen Receptor Modulators (SERMs) has been driven by interest in discovering target selective molecules. In view of such significance, the present work explored the pharmacophores of estrogen receptor (ER) subtypes specific binding affinities of diverse compounds belonging to the category of bridged bicyclic-1,1-diarylethylene derivatives. Implementing classical QSAR and CATALYST based space-modeling approaches, it has been explored that attachment of aryl ring systems to unsaturated linkages, availability of phenolic hydroxyl group, global hydrophobicity, and stereochemistry of certain functional groups might be important for governing the subtype specific estrogenic behavior of this group of compounds. Supplementing this deduction, critical interfeature distances between hydrogen bond acceptor, hydrophobic, and ring aromatic features along with steric influence are found to primarily influence the ER-subtypes specific binding of this series of compounds.

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Year:  2007        PMID: 17328537     DOI: 10.1021/ci600419s

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  3 in total

1.  Human Estrogen Receptor Alpha Antagonists, Part 3: 3-D Pharmacophore and 3-D QSAR Guided Brefeldin A Hit-to-Lead Optimization toward New Breast Cancer Suppressants.

Authors:  Nezrina Kurtanović; Nevena Tomašević; Sanja Matić; Elenora Proia; Manuela Sabatino; Lorenzo Antonini; Milan Mladenović; Rino Ragno
Journal:  Molecules       Date:  2022-04-28       Impact factor: 4.927

2.  In silico identification of novel lead compounds with AT1 receptor antagonist activity: successful application of chemical database screening protocol.

Authors:  Mahima Pal; Sarvesh Paliwal
Journal:  Org Med Chem Lett       Date:  2012-03-01

3.  In silico prediction of estrogen receptor subtype binding affinity and selectivity using statistical methods and molecular docking with 2-arylnaphthalenes and 2-arylquinolines.

Authors:  Zhizhong Wang; Yan Li; Chunzhi Ai; Yonghua Wang
Journal:  Int J Mol Sci       Date:  2010-09-20       Impact factor: 5.923

  3 in total

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