Faculty of Mathematics and Computer Science, Jagiellonian University, S. Łojasiewicza Street 6, 30-048, Kraków, Poland.
Department of Medicinal Chemistry, Institute of Pharmacology, Polish Academy of Sciences, Smętna Street 12, 31-343, Kraków, Poland.
Mol Divers. 2019 Aug;23(3):603-613. doi: 10.1007/s11030-018-9894-4. Epub 2018 Nov 27.
Three-dimensional descriptors are often used to search for new biologically active compounds, in both ligand- and structure-based approaches, capturing the spatial orientation of molecules. They frequently constitute an input for machine learning-based predictions of compound activity or quantitative structure-activity relationship modeling; however, the distribution of their values and the accuracy of depicting compound orientations might have an impact on the power of the obtained predictive models. In this study, we analyzed the distribution of three-dimensional descriptors calculated for docking poses of active and inactive compounds for all aminergic G protein-coupled receptors with available crystal structures, focusing on the variation in conformations for different receptors and crystals. We demonstrated that the consistency in compound orientation in the binding site is rather not correlated with the affinity itself, but is more influenced by other factors, such as the number of rotatable bonds and crystal structure used for docking studies. The visualizations of the descriptors distributions were prepared and made available online at http://chem.gmum.net/vischem_stability , which enables the investigation of chemical structures referring to particular data points depicted in the figures. Moreover, the performed analysis can assist in choosing crystal structure for docking studies, helping in selection of conditions providing the best discrimination between active and inactive compounds in machine learning-based experiments.
三维描述符常用于基于配体和基于结构的方法中搜索新的具有生物活性的化合物,捕捉分子的空间取向。它们经常作为化合物活性的基于机器学习的预测或定量构效关系建模的输入;然而,它们的值的分布和描绘化合物取向的准确性可能会影响获得的预测模型的能力。在这项研究中,我们分析了为具有可用晶体结构的所有神经递质 G 蛋白偶联受体的对接构象计算的三维描述符的分布,重点研究了不同受体和晶体之间构象的变化。我们证明,化合物在结合位点中的取向一致性与其亲和力本身并没有相关性,而是更多地受到其他因素的影响,例如可旋转键的数量和用于对接研究的晶体结构。描述符分布的可视化已准备好并可在 http://chem.gmum.net/vischem_stability 上在线获取,这使得可以研究与图中描绘的特定数据点有关的化学结构。此外,所进行的分析可以帮助选择用于对接研究的晶体结构,有助于在基于机器学习的实验中选择提供活性和非活性化合物之间最佳区分的条件。