Molecular mapping of heterocyclic diazene derivatives for estrogen receptor modulation

Selective estrogen receptor modulators (SERMs) are effectively used in hormone replacement therapy (HRT) by reducing post-menopausal symptoms, including hormone-responsive breast cancer and osteoporosis. The present study explored the pharmacophore features of diazene derivatives for selective estro...

Full description

Saved in:
Bibliographic Details
Published in:Indian journal of biochemistry & biophysics 2012-08, Vol.49 (4), p.236-245
Main Authors: Islam, M Ataul, Mukherjee, Arup, Saha, Achintya
Format: Article
Language:English
Subjects:
Heterocyclic Compounds - chemistry
Heterocyclic Compounds - metabolism
Heterocyclic Compounds - pharmacology
Imides - chemistry
Imides - metabolism
Imides - pharmacology
Models, Molecular
Protein Conformation
Quantitative Structure-Activity Relationship
Receptors, Estrogen - chemistry
Receptors, Estrogen - metabolism
Selective Estrogen Receptor Modulators - chemistry
Selective Estrogen Receptor Modulators - metabolism
Selective Estrogen Receptor Modulators - pharmacology
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Selective estrogen receptor modulators (SERMs) are effectively used in hormone replacement therapy (HRT) by reducing post-menopausal symptoms, including hormone-responsive breast cancer and osteoporosis. The present study explored the pharmacophore features of diazene derivatives for selective estrogen receptor (ER) modulation using quantitative structure activity relationship (QSAR) and space modeling approaches. The 2D-QSAR models (R2alpha = 0.907, Q2alpha = 0.700, R2(pred-alpha) = 0.735; R2beta = 0.913, Q2beta= 0.756, R2(pred-beta). = 0.745) showed the importance of orbital energies, hydrophobicity, refractivity and atomic charges for selective binding affinity to ER. In 3D-QSAR, molecular field (CoMFA, R2alpha = 0.948, Q2 = 0.720, R2(pred-alpha) = 0.708; R2beta = 0.994, Q2beta = 0.541, R2(pred-beta) = 0.721) and similarity models (CoMSIA, R2alpha = 0.984, Q2alpha = 0.793, R(pred-alpha) 0.738; R2beta = 0.996, Q2beta = 0.681, R2(pred-beta) = 0.725) indicated that steric and hydrophobic properties were important for binding selectivity. Space modeling study (R2alpha = 0.885, Q2alpha = 0.855, R2(pred-alpha) = 0.666; R2beta = 0.872, Q2beta = 0.883, R2(pred-beta) = 0.814) revealed that hydrophobic and aromatic ring features were important for both subtypes, whereas hydrogen bond (HB) acceptor and donor were crucial for beta- and alpha-subtypes, respectively. Interactions observed between ligand and catalytic residues at the active site in docking study substantiated the developed model which may be successfully used in high throughput screening (HTS) to obtain promising lead molecules for selective estrogen therapy.
ISSN:0301-1208