基于雌激素β受体结构雌激素类化合物的三维定量结构-活性关系与分子对接研究

雌激素类化合物由于其对人和野生动物健康的负面影响而受到广泛关注.雌激素受体存在α和β两种亚型,由于雌激素β受体（ERβ）与α受体（ERα）两者结合腔中的氨基酸序列存在明显差异,因此配体化合物在与雌激素β受体和α受体的结合活性和模式上也可能存在较大差别.本文以50个与雌激素β受体结合的化合物为研究对象,应用比较分子相似性指数分析（COMSIA）的三维定量结构-活性关系（3D-QSAR）分析方法研究化合物结构与活性之间的关系,比较了原子契合和基于受体结构两种分子叠合方式对模型质量的影响,建立了相关性显著、预测能力强的定量活性预测模型（R^2=0.961,qLOO^2=0.671,R^2Pred=0.722）,并结合分子对接方法揭示了影响化合物活性的分子结构特征和分子机理.

3D-QSAR and docking studies of estrogen compounds based on estrogen receptor

Close attention has been paid to estrogen compounds because these chemicals may pose a serious threat to the health of humans and wildlife. Estrogen receptor（ER） exits as two subtypes, ERα and ERβ The difference in amino acids sequence of the binding sites of ERα and ERβ might get a result that some synthetic estrogens and naturally occurring steroidal ligands have different relative affinities and binding modes for ERα and ERβ In this investigation, comparative molecular similarity indices analysis （COMSIA） was performed on 50 estrogen compounds binding to ERβ to find out the structural relationship with the activities. We also compared two alignment schemes employed in COMSIA analysis, namely, atom-fit and receptor-based alignment, with respect to the predictive capabilities of their respective models for structurally diverse data sets. The model with the significant correlation and the best predictive power （R^2=0.961,q LOO^2 =0.671, RPred^2 =0.722） was achieved. The COMSIA and docking results revealed the structural features related to an activity and provided an insight into molecular mechanisms of estrogenic activity for estrogen compounds.