Molecular modelling on small molecular CDK2 inhibitors: an integrated approach using a combination of molecular docking, 3D-QSAR and pharmacophore modelling

Abstract

Cyclin-dependent kinase 2 (CDK2) has been identified as an important target for developing novel anticancer agents. Molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) and pharmacophore modelling were combined with the ultimate goal of studying the structure-activity relationship of CDK2 inhibitors. The comparative molecular similarity indices analysis (CoMSIA) model constructed based on a set of 3-aminopyrazole derivatives as CDK2 inhibitors gave statistically significant results (q (2) = 0.700; r (2) = 0.982). A HypoGen pharmacophore model, constructed using diverse CDK2 inhibitors, also showed significant statistics ([Formula: see text]Cost = 61.483; RMSD = 0.53; Correlation coefficient = 0.98). The small residues and error values between the estimated and experimental activities of the training and test set compounds proved their strong capability of activity prediction. The structural insights obtained from these two models were consistent with each other. The pharmacophore model summarized the important pharmacophoric features required for protein-ligand binding. The 3D contour maps in combination with the comprehensive pharmacophoric features helped to better interpret the structure-activity relationship. The results will be beneficial for the discovery and design of novel CDK2 inhibitors. The simplicity of this approach provides expansion to its applicability in optimizing other classes of small molecular CDK2 inhibitors.

Molecular Modeling and Design Studies of Purine Derivatives as Novel CDK2 Inhibitors

“…Progressive scrambling slopes ( dq 2 ′/dr 2 yy ’ ) for the optimal CoMFA model and the optimal CoMSIA model are 1.159 and 1.129, respectively. The progressive scrambling Q 2 of the two models are all greater than 0.350 and the progressive scrambling slopes of the two models are all less than 1.200 and near unity, which signifies that the models are robust and stable [ 20 , 21 ]. The test set not used to construct the 3D-QSAR models was used to evaluate the reliability and predictive ability of the obtained models.…”

Gaussian field-based 3D-QSAR and molecular simulation studies to design potent pyrimidine–sulfonamide hybrids as selective BRAFV600Einhibitors

“…Typically, 3D-QSAR investigations are employed for statistical analysis of SAR for a group of compounds with similar structures and to look into the characteristics of an interaction between a ligand and its target protein. 56 Molecular docking is used to understanding the structural relationship between a ligand and its target and predicting the best binding conformation. 57 The exibility, changes in the structural conformation of the target binding site, and stability of a ligand-receptor complex suggested by molecular docking was studied in details by the use of molecular dynamics (MD) simulations.…”

Design, Synthesis, Biological Evaluation, and Molecular Modeling of 2-Difluoromethylbenzimidazole Derivatives as Potential PI3Kα Inhibitors

“…In this study, 3D-QSAR models were developed using CoMFA [20] and CoMSIA [21] technology based on 85 2-difluoromethylbenzimidazole derivatives [22][23][24]. The relationships between the key structural and pharmacodynamic information were obtained from the 3D-QSAR model, which were helpful for further drug research [25][26][27][28][29][30]. The binding mode of the compound 29 with 4YKN was explored through molecular docking and molecular dynamics simulation.…”