A new structure-based QSAR method affords both descriptive and predictive models for phosphodiesterase-4 inhibitors.
A new structure-based QSAR method affords both descriptive and predictive models for phosphodiesterase-4 inhibitors.
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DOI：
10.2174/1875397300802010029
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发表时间：
2008-11-06
期刊：
影响因子：
--
通讯作者：
Zheng, Weifan
中科院分区：
文献类型：
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作者：
Dong, Xialan;Zheng, Weifan
我们描述了一种新的QSAR(定量结构-活性关系)方法在PDE-4抑制剂的分析和建模中的应用。这种新方法利用PDE-4酶的X射线结构信息来表征小分子抑制剂。它基于其药效团特征对与靶结合口袋的那些(参考)特征对的匹配来计算分子描述符。由于参考来自所研究目标的X射线晶体结构，这些描述符因目标而异，易于解释。我们分析了35个基于吲哚类化合物的PDE-4抑制剂，其中使用偏最小二乘(PLS)分析得到预测模型。与CoMFA和CoMSIA等传统的QSAR方法相比，我们的模型对分子的训练集和测试集都具有更强的稳健性和预测性。我们的方法还可以确定关键的药效团特征，这些特征对小分子的抑制效力负责。因此，这种基于结构的QSAR方法为磷酸二酯酶-4抑制剂提供了描述性和预测性模型。这项研究的成功也为PDE酶家族的系统QSAR建模奠定了坚实的基础，最终将有助于针对PDE酶的化学基因组学研究和药物发现。
We describe the application of a new QSAR (quantitative structure-activity relationship) formalism to the analysis and modeling of PDE-4 inhibitors. This new method takes advantage of the X-ray structural information of the PDE-4 enzyme to characterize the small molecule inhibitors. It calculates molecular descriptors based on the matching of their pharmacophore feature pairs with those (the reference) of the target binding pocket. Since the reference is derived from the X-ray crystal structures of the target under study, these descriptors are target-specific and easy to interpret. We have analyzed 35 indole derivative-based PDE-4 inhibitors where Partial Least Square (PLS) analysis has been employed to obtain the predictive models. Compared to traditional QSAR methods such as CoMFA and CoMSIA, our models are more robust and predictive measured by statistics for both the training and test sets of molecules. Our method can also identify critical pharmacophore features that are responsible for the inhibitory potency of the small molecules. Thus, this structure-based QSAR method affords both descriptive and predictive models for phosphodiesterase-4 inhibitors. The success of this study has also laid a solid foundation for systematic QSAR modeling of the PDE family of enzymes, which will ultimately contribute to chemical genomics research and drug discovery targeting the PDE enzymes.