10.6084/m9.figshare.1050556.v3 A. Balupuri A. Balupuri P.K. Balasubramanian P.K. Balasubramanian C.G. Gadhe C.G. Gadhe S.J. Cho S.J. Cho Docking-based 3D-QSAR study of pyridyl aminothiazole derivatives as checkpoint kinase 1 inhibitors Taylor & Francis Group 2014 r 2 docking simulations drug candidates novel anticancer agents Chk 1. CoMSIA model binding conformations CoMFA model checkpoint kinase 1 inhibitors Checkpoint kinase 1 similarity indices analysis hydrogen bond acceptor fields CoMSIA models pyridyl aminothiazole derivatives 14 compounds r 2pred docking conformations q 2 field analysis Chk 1 inhibitors 2014-09-19 09:49:32 Journal contribution https://tandf.figshare.com/articles/journal_contribution/Docking_based_3D_QSAR_study_of_pyridyl_aminothiazole_derivatives_as_checkpoint_kinase_1_inhibitors/1050556 <div><p>Checkpoint kinase 1 (Chk1) is a promising target for the design of novel anticancer agents. In the present work, molecular docking simulations and three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on pyridyl aminothiazole derivatives as Chk1 inhibitors. AutoDock was used to determine the probable binding conformations of all the compounds inside the active site of Chk1. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed based on the docking conformations and alignments. The CoMFA model produced statistically significant results with a cross-validated correlation coefficient (<i>q</i><sup>2</sup>) of 0.608 and a coefficient of determination (<i>r</i><sup>2</sup>) of 0.972. The reliable CoMSIA model with <i>q</i><sup>2</sup> of 0.662 and <i>r</i><sup>2</sup> of 0.970 was obtained from the combination of steric, electrostatic and hydrogen bond acceptor fields. The predictive power of the models were assessed using an external test set of 14 compounds and showed reasonable external predictabilities (<i>r</i><sup>2</sup><sub>pred</sub>) of 0.668 and 0.641 for CoMFA and CoMSIA models, respectively. The models were further evaluated by leave-ten-out cross-validation, bootstrapping and progressive scrambling analyses. The study provides valuable information about the key structural elements that are required in the rational design of potential drug candidates of this class of Chk1 inhibitors.</p></div>