Three-dimensional descriptors for aminergic GPCRs: dependence on docking conformation and crystal structure

Abstract

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. Graphical abstract Electronic supplementary material The online version of this article (10.1007/s11030-018-9894-4) contains supplementary material, which is available to authorized users.

Exploring the Potential of Spherical Harmonics and PCVM for Compounds Activity Prediction

“…In [36] the authors strive to provide a novel local conjoint triad feature representation. Additionally, recent studies address the challenges faced in developing molecular descriptors and tools to drug design targeting GPCRs [37,38].…”