In Silico Exploration of 1,7-Diazacarbazole Analogs as Checkpoint Kinase 1 Inhibitors by Using 3D QSAR, Molecular Docking Study, and Molecular Dynamics Simulations

Selected arylsulphonyl pyrazole derivatives as potential Chk1 kinase ligands-computational investigations

Protein kinases control diversity of biochemical processes in human organism. Checkpoint 1 kinase (Chk1) is an important element of the checkpoint signalling pathways and is responsible for DNA damage repair. Hence, this kinase plays an essential role in cancer cells survival and has become an important target for anticancer agents. Our previous investigations showed that some arylsulphonyl indazole derivatives displayed anticancer effect in vitro. In the present study, in order to verify possibility of interactions of pyrazole and indazole derivatives with Chk1, we focused on the docking of selected tosyl derivatives of indazole and condensed pyrazole 1-7 to the Chk1 pocket, analysis of interactions involving optimized ligand-protein system using DFT formalism, and estimation of the interaction enthalpy of the ligand-protein complex by applying the PM7 method. The estimation of binding affinity seems to indicate that the indazole 5-substituted with 3,5-dimethylpyrazole 4 and condensed pyrazoloquinoline derivative 7 fit the best to the Chk1-binding pocket. The values of the energy of interaction, i.e. the enthalpy change (ΔHint), were between - 85.06 and - 124.04 kcal mol-1 for the optimized ligand-Chk1 complexes. The relaxation of the ligands within the complexes azole-protein as well as the distribution of hydrogen contacts between the ligands and kinase pocket amino acids was also analysed using molecular dynamics as a supporting method. Graphical Abstract Presentation of methods used to describe the interactions between arylsulphonyl pyrazole derivatives and Chk1 kinase.

In silico exploration of aryl sulfonamide analogs as voltage-gated sodium channel 1.7 inhibitors by using 3D-QSAR, molecular docking study, and molecular dynamics simulations

It has been demonstrated by human genetics that the voltage-gated sodium channel Nav1.7 is currently a promising target for the treatment of pain. In this research, we performed molecular simulation works on a series of classic aryl sulfonamide Nav1.7 inhibitors using three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking and molecular dynamics (MD) simulations for the first time to explore the correlation between their structures and activities. The results of the relevant statistical parameters of comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analyses (CoMSIA) had been verified to be reasonable, and the deep relationship between the structures and activities of these inhibitors was obtained by analyzing the contour maps. The generated 3D-QSAR model showed a good predictive ability and provided valuable clues for the rational modification of molecules. The interactions between compounds and proteins were modeled by molecular docking studies. Finally, accuracy of the docking results and stability of the complexes were verified by 100 ns MD simulations. Detailed information on the key residues at the binding site and the types of interactions they participate in involved was obtained. The van der Waals energy contributed the most in the molecular binding process according to the calculation of binding free energy. All research results provided a good basis for further research on novel and effective Nav1.7 inhibitors.

Mechanism Exploration of Arylpiperazine Derivatives Targeting the 5-HT2A Receptor by In Silico Methods

As a G-protein coupled receptor, the 5-hydroxytryptamine 2A (5-HT_2A) receptor is known for its critical role in the cognitive, behavioural and physiological functions, and thus is a primary molecular target to treat psychiatric diseases, including especially depression. With purpose to explore the structural traits affecting the inhibitory activity, currently a dataset of 109 arylpiperazine derivatives as promising 5-HT_2A antagonists was built, based on which the ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR) study by using both comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches was carried out. The resultant optimal CoMSIA model displays proper validity and predictability with cross-validated correlation coefficient Q² = 0.587, non-cross-validated correlation coefficient R²_ncv = 0.900 and predicted correlation coefficient for the test set of compounds R²_pre = 0.897, respectively. Besides, molecular docking was also conducted to investigate the binding mode between these ligands and the active site of the 5-HT_2A receptor. Meanwhile, as a docking supplementary tool to study the antagonists' conformation in the binding cavity, molecular dynamics (MD) simulation was also performed, providing further elucidation about the changes in the ligand-receptor complex. Lastly, some new molecules were also newly-designed based on the above results that are potential arylpiperazine antagonists of 5-HT_2A receptor. We hope that the present models and derived information may be of help for facilitating the optimization and design of novel potent antagonists as antidepressant drugs as well as exploring the interaction mechanism of 5-HT_2A antagonists.