In silico design of heteroaryldihydropyrimidine-based selective HBV capsid assembly inhibitors.

HIV-1 protease is a key enzyme in the maturation process of HIV protein. HIV-1 PIs are an important class of drug used to inhibit HIV infection and have an important effect on virus replication. In this article, 3D-QSAR was used to investigate the molecular simulations related to 50 DRV selective inhibitors. A 3D-QSAR model was established based on CoMFA and CoMSIA, and the best CoMSIA field was selected based on the model prediction results. The results showed that the CoMFA model (q² = 0.809, r² = 0.989) and CoMSIA (S + E + D + H (q² = 0.834, r² = 0.988)) have an excellent prediction capability. In addition, the method of docking between template molecules and the receptor was studied by molecular docking, and the results of the 3D-QSAR model were further verified. Through the analysis of counter maps, we designed 9 new small molecules and predicted their activity. Afterward, the newly designed small molecules were docked, and MD simulations and binding free energies were used to verify the accuracy of the docking results. Via a series of predictions, it was concluded that the newly designed compound D08 may have a better inhibitory activity. Furthermore, for the novel molecules, their ADMET properties and drug likeness were also analysed. The results show that these novel molecules also have reasonable pharmacokinetics. These results may provide an important reference for the design and development of novel effective HIV-1 PR inhibitors.

In this paper, a three-dimensional quantitative structure-activity relationship (3D-QSAR) namely CoMFA and CoMSIA has been carried out on a series (43 compounds) of capsid assembly inhibitors on N-phenyl-3-sulfamoyl-benzamide-based. The statistical parameters from the models (CoMFA: r² = 0.998, q² = 0.625, r²_pred = 0.837; CoMSIA: r² = 0.987, q² = 0.645, r²_pred = 0.698) indicate that the data are well fitted and have high predictive ability. Molecular docking was employed to explore the binding mode between these compounds and the receptor protein, as well as help understand the structure-activity relationship revealed by CoMFA and CoMSIA. Contour maps of the QSAR models were generated and validated by molecular docking study. The final models of CoMFA/CoMSIA and molecular docking could be useful for the design and development of novel potent HBV capsid assembly inhibitors.

Human immunodeficiency virus (HIV) reverse transcriptase (RT) works in the life cycle of HIV and is one of the key targets for anti-HIV-1 drug development. Recently, a novel series of diarylpyrimidine derivatives (DAPYs) have been reported as potent HIV-1 non-nucleoside RT inhibitors (NNRTIs), and they exhibit potent antiviral activity. Here we explored the binding interaction patterns of a set of 2,4,5-trisubstituted pyrimidine derivatives using molecular docking, three-dimensional quantitative structure–activity relationships (3D-QSAR), and molecular dynamics (MD) simulations. Molecular docking for exploring the mechanism of action of small molecule ligands with receptor proteins. Comparative molecular field (CoMFA q² = 0.828, r² = 0.988, r²_pred = 0.981) and comparative molecular similarity index (CoMSIA q² = 0.859, r² = 0.968, r²_pred = 0.980) were performed to build stable and reliable 3D-QSAR models. The contour plots revealed the relationship between structural features and inhibitory activities. Based on the molecular docking analysis and contour maps, some novel compounds with higher predicted activities were designed and further MD simulations and bind free energy calculations were performed. Our models results may provide an essential reference for the design and development of effective novel HIV-1 NNRTIs.