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采用三种不同骨架,通过对接和 MM-GBSA 评分方法预测雌激素受体β配体的效力和选择性。

Prediction of estrogen receptor β ligands potency and selectivity by docking and MM-GBSA scoring methods using three different scaffolds.

机构信息

Department of Pharmacology, PSG College of Pharmacy, Coimbatore, India.

出版信息

J Enzyme Inhib Med Chem. 2012 Dec;27(6):832-44. doi: 10.3109/14756366.2011.618990. Epub 2011 Oct 14.

DOI:10.3109/14756366.2011.618990
PMID:21999568
Abstract

This study aimed to identify the docking and molecular mechanics-generalized born surface area (MM-GBSA) re-scoring parameters which can correlate the binding affinity and selectivity of the ligands towards oestrogen receptor β (ERβ). Three different series of ERβ ligands were used as dataset and the compounds were docked against ERβ (protein data bank (PDB) ID: 1QKM) using Glide and ArgusLab. Glide docking showed superior results when compared with ArgusLab. Docked poses were then rescored using Prime-MM-GBSA to calculate free energy binding. Correlations were made between observed activities of ERβ ligands with computationally predicted values from docking, binding energy parameters. ERβ ligands experimental binding affinity/selectivity did not correlate well with Glide and ArgusLab score. Whereas calculated Glide energy (coulomb-van der Waal interaction energy) correlated significantly with binding affinity of ERβ ligands (r(2) = 0.66). MM-GBSA re-scoring showed correlation of r(2) = 0.74 with selectivity of ERβ ligands. These results will aid the discovery of novel ERβ ligands with isoform selectivity.

摘要

本研究旨在确定对接和分子力学-广义 Born 表面积(MM-GBSA)再评分参数,这些参数可以将配体与雌激素受体β(ERβ)的结合亲和力和选择性相关联。使用三种不同系列的 ERβ配体作为数据集,并用 Glide 和 ArgusLab 将化合物对接至 ERβ(蛋白质数据库(PDB)ID:1QKM)。与 ArgusLab 相比,Glide 对接显示出更好的结果。然后使用 Prime-MM-GBSA 重新评分对接构象,以计算自由能结合。将 ERβ配体的观察活性与从对接、结合能参数计算出的预测值进行相关性分析。ERβ配体的实验结合亲和力/选择性与 Glide 和 ArgusLab 评分没有很好的相关性。然而,计算出的 Glide 能量(库仑-范德华相互作用能)与 ERβ配体的结合亲和力显著相关(r²=0.66)。MM-GBSA 再评分显示与 ERβ配体选择性的 r²=0.74 相关。这些结果将有助于发现具有同工型选择性的新型 ERβ配体。

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