Islam M Ataul, Mukherjee Arup, Saha Achintya
Department of Chemical Technology, University of Calcutta, 92, A.P.C.Road, Kolkata 700 009, India.
Indian J Biochem Biophys. 2012 Aug;49(4):236-45.
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.
选择性雌激素受体调节剂（SERMs）通过减轻绝经后症状，包括激素反应性乳腺癌和骨质疏松症，有效地用于激素替代疗法（HRT）。本研究采用定量构效关系（QSAR）和空间建模方法，探索了二氮烯衍生物对选择性雌激素受体（ER）调节的药效团特征。二维QSAR模型（R2alpha = 0.907，Q2alpha = 0.700，R2(pred-alpha) = 0.735；R2beta = 0.913，Q2beta = 0.756，R2(pred-beta). = 0.745）表明轨道能量、疏水性、折射性和原子电荷对于与ER的选择性结合亲和力很重要。在三维QSAR中，分子场（CoMFA，R2alpha = 0.948，Q2 = 0.720，R2(pred-alpha) = 0.708；R2beta = 0.994，Q2beta = 0.541，R2(pred-beta) = 0.721）和相似性模型（CoMSIA，R2alpha = 0.984，Q2alpha = 0.793，R(pred-alpha) 0.738；R2beta = 0.996，Q2beta = 0.681，R2(pred-beta) = 0.725）表明空间和疏水性质对于结合选择性很重要。空间建模研究（R2alpha = 0.885，Q2alpha = 0.855，R2(pred-alpha) = 0.666；R2beta = 0.872，Q2beta = 0.883，R2(pred-beta) = 0.814）表明疏水和芳香环特征对于两种亚型都很重要，而氢键（HB）受体和供体分别对于β-和α-亚型至关重要。对接研究中观察到的配体与活性位点催化残基之间的相互作用证实了所开发的模型，该模型可成功用于高通量筛选（HTS），以获得用于选择性雌激素治疗的有前景的先导分子。
