Challenges predicting ligand-receptor interactions of promiscuous proteins: the nuclear receptor PXR.
Challenges predicting ligand-receptor interactions of promiscuous proteins: the nuclear receptor PXR.
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DOI：
10.1371/journal.pcbi.1000594
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发表时间：
2009-12
影响因子：
4.3
通讯作者：
Krasowski MD
中科院分区：
文献类型：
--
作者：
Ekins S;Kortagere S;Iyer M;Reschly EJ;Lill MA;Redinbo MR;Krasowski MD
一些参与异物解毒和细胞凋亡的基因的转录调控是通过人类孕烷X受体(PXR)实现的，而PXR又被包括类固醇激素在内的结构不同的激动剂激活。PXR的激活有可能引发不良反应，改变药物的药代动力学或扰乱生理过程。PXR激动剂的可靠计算预测对药物和毒理学研究具有重要价值。基于结构的建模方法预测人类PXR激活物的成功有限。基于配基的建模方法，包括定量构效关系(QSAR)分析、药效团建模和机器学习，取得了略好的成功。在这项研究中，我们提出了一项全面的分析，重点是预测115个类固醇与人PXR的配体结合活性。六种晶体结构被用作对接和基于配体的建模方法(二维、三维、四维和五维分析)的模板。5D-QSAR的外部预测效果最好。带有FCFP_6描述符的贝叶斯模型在剔除很大比例的数据集并使用外部测试集后得到验证。将配体对接到与金丝桃素共结晶的PXR结构上具有最好的统计量。硫化类固醇(激活剂)一直被预测为非激活剂，而预测不佳的类固醇与5-α-雄-3-β-ol相反。人类PXR的建模是一个复杂的挑战，因为它有一个巨大的、灵活的配体结合腔。这项研究强调了这一点，使用迄今为止最大的量化数据集和多种建模方法说明了不大的成功。杂乱蛋白通常结合大量不同的配基结构。这可以通过非常大的结合部位、多个结合部位或可以调节配基大小的灵活结合部位来促进。这些方面也增加了预测一个分子是否会与这些蛋白质结合的复杂性，这些蛋白质经常作为外源化合物传感器对有毒压力做出反应。例如，转运蛋白可能会阻止某些分子的吸收，而酶可能会将它们转化为更容易排泄的化合物(或者在被其他解毒酶进一步清除之前激活它们)。核激素受体可能会对配体产生反应，然后影响下游基因的表达，从而上调酶和转运蛋白，从而增加对相同或不同分子的清除。我们评估了许多不同的基于配体和基于结构的计算方法对类固醇化合物激活人类PXR的模拟和预测能力。我们找到了最有效的计算方法来识别潜在的类固醇PXR激动剂，由于它们在临床医学中的广泛使用和环境中模拟物的存在，这些激动剂具有临床意义。
Transcriptional regulation of some genes involved in xenobiotic detoxification and apoptosis is performed via the human pregnane X receptor (PXR) which in turn is activated by structurally diverse agonists including steroid hormones. Activation of PXR has the potential to initiate adverse effects, altering drug pharmacokinetics or perturbing physiological processes. Reliable computational prediction of PXR agonists would be valuable for pharmaceutical and toxicological research. There has been limited success with structure-based modeling approaches to predict human PXR activators. Slightly better success has been achieved with ligand-based modeling methods including quantitative structure-activity relationship (QSAR) analysis, pharmacophore modeling and machine learning. In this study, we present a comprehensive analysis focused on prediction of 115 steroids for ligand binding activity towards human PXR. Six crystal structures were used as templates for docking and ligand-based modeling approaches (two-, three-, four- and five-dimensional analyses). The best success at external prediction was achieved with 5D-QSAR. Bayesian models with FCFP_6 descriptors were validated after leaving a large percentage of the dataset out and using an external test set. Docking of ligands to the PXR structure co-crystallized with hyperforin had the best statistics for this method. Sulfated steroids (which are activators) were consistently predicted as non-activators while, poorly predicted steroids were docked in a reverse mode compared to 5α-androstan-3β-ol. Modeling of human PXR represents a complex challenge by virtue of the large, flexible ligand-binding cavity. This study emphasizes this aspect, illustrating modest success using the largest quantitative data set to date and multiple modeling approaches. Promiscuous proteins generally bind a large array of diverse ligand structures. This may be facilitated by a very large binding site, multiple binding sites, or a flexible binding site that can adjust to the size of the ligand. These aspects also increase the complexity of predicting whether a molecule will bind or not to such proteins which frequently function as exogenous compound sensors to respond to toxic stress. For example, transporters may prevent absorption of some molecules, and enzymes may convert them to more readily excretable compounds (or alternatively activate them prior to further clearance by other detoxification enzymes). Nuclear hormone receptors may respond to ligands and then affect downstream gene expression to upregulate both enzymes and transporters to increase the clearance for the same or different molecules. We have assessed the ability of many different ligand-based and structure-based computational approaches to model and predict the activation of human PXR by steroidal compounds. We find the most effective computational approach to identify potential steroidal PXR agonists which are clinically relevant due to their widespread use in clinical medicine and the presence of mimics in the environment.
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影响因子：
3.7
作者：
Biswas, Arunima;Mani, Sridhar;Redinbo, Matthew R.;Krasowski, Matthew D.;Li, Hao;Ekins, Sean
通讯作者：
Ekins, Sean
DOI：
10.1073/pnas.95.21.12208
发表时间：
1998-10-13
影响因子：
11.1
作者：
Bertilsson, G;Heidrich, J;Berkenstam, A
通讯作者：
Berkenstam, A
影响因子：
5.6
作者：
Klon, Anthony E.;Lowrie, Jeffrey F.;Diller, David J.
通讯作者：
Diller, David J.
影响因子：
3.4
作者：
Azzaoui, Kamal;Hamon, Jacques;Urban, Laszlo
通讯作者：
Urban, Laszlo
影响因子：
11.5
作者：
Gupta, Divya;Venkatesh, Madhukumar;Mani, Sridhar
通讯作者：
Mani, Sridhar