QSAR study, molecular docking and molecular dynamic simulation of Aurora kinase inhibitors derived from imidazo[4,5-b]pyridine derivatives

Abstract

Cancer is a serious threat to human life and social development and the use of scientific methods for cancer prevention and control is necessary. In this study, HQSAR, CoMFA, CoMSIA and TopomerCoMFA methods were used to establish models of 65 imidazo[4,5-b]pyridine derivatives to explore the quantitative structure activity relationship between their anticancer activities and molecular conformations. The results showed that the cross-validation coefficients q2 of HQSAR, CoMFA, CoMSIA and TopomerCoMFA were 0.892, 0.866, 0.877 and 0.905, respectively. The non-cross-validation coefficients r2 were 0.948, 0.983, 0.995 and 0.971, respectively. The externally validated complex correlation coefficients r2pred of external validation were 0.814, 0.829, 0.758 and 0.855, respectively. The PLS analysis verified the QSAR models we established with high prediction ability and stability. Based on these statisticians, virtual screening based on R group was done in ZINC database by using the Topomer search technology. Finally, 10 new compounds with higher activity were designed with the screened new fragments. In order to explore the binding modes and targets between ligands and protein receptors, these newly designed compounds were conjugated with macromolecular protein (PDB ID: 1MQ4) by molecular docking technology. Furthermore, to study the nature of newly designed compound in dynamic states and the stability of protein-ligand complex, molecular dynamics simulation for 50ns was carried out for N3, N4, N5 and N7 docked with 1MQ4 protease structure. Free energy landscape was computed to search the most stable conformation. These results proved the efficient and stability of the newly designed compounds. Finally, ADMET was used to predict the pharmacology and toxicity of the designed 10 drug molecules to test their pharmacological effects and safety.

Molecular modeling studies of Indoline Scaffold derivatives as PD‐1/PD‐L1 pathway inhibitors by QSAR, molecular docking and molecular dynamics simulation techniques

“…Finally, after obtaining the molecular holograms, the quantitative structure-activity relationship between the molecular holograms and the molecular bioactivity was modeled by a partial least squares regression algorithm. [27] In order to obtain the ideal HQSAR model, the molecular fragment descriptors, including atom (A), bond (B), connection (C), hydrogen (H), chirality (CH), and hydrogen bond donor/acceptor (DA), need to be adjusted. Appropriate parameters such as fragment length and holographic length can improve the predictive ability of the model with default values of 4-7 and 53-410, respectively.…”