In Silico Screening of Novel α1-GABAA Receptor PAMs towards Schizophrenia Based on Combined Modeling Studies of Imidazo [1,2-a]-Pyridines

The ionotropic GABAA receptor (GABAAR) has been proven to be an important target of atypical antipsychotics. A novel series of imidazo [1,2-a]-pyridine derivatives, as selective positive allosteric modulators (PAMs) of α1-containing GABAARs with potent antipsychotic activities, have been reported recently. To better clarify the pharmacological essentiality of these PAMs and explore novel antipsychotics hits, three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, pharmacophore modeling, and molecular dynamics (MD) were performed on 33 imidazo [1,2-a]-pyridines. The constructed 3D-QSAR models exhibited good predictive abilities. The dockings results and MD simulations demonstrated that hydrogen bonds, π–π stackings, and hydrophobic interactions play essential roles in the binding of these novel PAMs in the GABAAR binding pocket. Four hit compounds (DS01–04) were then screened out by the combination of the constructed models and computations, including the pharmacophore model, Topomer Search, molecular dockings, ADME/T predictions, and MD simulations. The compounds DS03 and DS04, with higher docking scores and better predicted activities, were also found to be relatively stable in the binding pocket by MD simulations. These results might provide a significant theoretical direction or information for the rational design and development of novel α1-GABAAR PAMs with antipsychotic activities.

A QSAR study of peptidyl vinyl sulfone cysteine protease inhibitors using Topomer CoMFA and Molecular Docking

Background: Malaria is one of the most important infectious diseases in the world. The most severe form of malaria in humans is caused by Plasmodium falciparum. Malaria is a worldwide health problem, with 214 million new cases in 2015 and 438,000 deaths, most of which in Africa. Therefore, there is an urgent need for novel, low-toxic, more specific inhibitors to find new antimalarial agents. A promising target for antimalarial drug design is falcipain-2, a cysteine protease from P. falciparum, that has received considerable attention due to its key role in the life cycle of the parasite. Methods: Three-dimensional quantitative structure-activity relationship (3D-QSAR) models of 39 peptidyl vinyl sulfone cysteine protease inhibitors was constructed using Topomer CoMFA. Topomer Search was employed to virtually screen lead-like compounds in the ZINC database. Molecular docking was employed to further explore the binding requirements between the ligands and the receptor protein which included several hydrogen bonds between peptidyl vinyl sulfone cysteine protease inhibitors and active site residues. Results: The non-cross correlation coefficient (r 2 ), the interaction validation coefficient (q2 ) and the external validation (r 2 pred) were 0.902, 0.685 and 0.763, respectively. The results showed that the model not only had good estimation stability but also good prediction capability. 22 new molecules were obtained, whose predicted activity are higher than template molecules. The results showed that the Topomer Search technology can be effectively applied to screen and design new peptidyl vinyl sulfone cysteine protease inhibitors. Molecular docking showed extensive interactions between peptidyl vinyl sulfone cysteine protease inhibitors and residues of LYS24, ASP21, LYS59 and ASP17 in the active site. Conclusion: 39 peptidyl vinyl sulfone cysteine protease inhibitors were used in the 3D-QSAR study. Topomer CoMFA 3DQSAR method was used to build the model, and the model was well predicted and statistically validated. The design of potent new inhibitors of cysteine protease can get useful insights from these results.

Application of an R-group search technique in the molecular design of dipeptidyl boronic acid proteasome inhibitors

In this work, a 3D-QSAR model involving for 40 dipeptidyl boronic acid proteasome inhibitors was built based on Topomer CoMFA. The multiple correlation coefficient of fitting, cross-validation and external validation were 0.908, 0.647 and 0.703, respectively. The results indicated that the obtained Topomer CoMFA model has not only the favourable estimation stability but also the good prediction capability. Topomer Search was employed as a tool for virtual screening in lead-like compounds of ZINC database. Finally, 1 R1 group, 7 R2 groups and 6 R3 groups with higher contribution values were employed to alternately substitute the R1, R2 and R3 of the templete compound 23 with highest bioactivity. As a consequence, 33 new molecules with higher activity than that of the model molecule were designed successfully. The results showed that the Topomer Search technology could be effectively apply to screen and design new dipeptidyl boronic acid proteasome inhibitors and has good predictive capability to design new dipeptidyl boronic acid proteasome inhibitors drugs as guidance.

Application of an R-group search technique into molecular design of HIV-1 integrase inhibitors

In this paper, a three-dimensional quantitative structure-activity relationship (3D-QSAR) study for 62 HIV-1 integrase(IN) inhibitors was established using Topomer CoMFA. The multiple correlation coefficient of fitting, cross validation and external validation were 0.942, 0.670 and 0.748, respectively. The results indicated that the Topomer CoMFA model obtained has both favorable estimation stability and good prediction capability. Topomer Search was used to search R group from ZINC database. As the result, a series of R groups with relatively high activity contribution was obtained. By filtering with the most potent molecule in the set, 1 Ra group and 21 Rb groups were selected. We employed the 1 Ra groups and 21 Rb groups to alternately substitute the Ra and Rb of sample 42. Finally, we designed 21 new compounds and further predicted their activities using the Topomer CoMFA model and there were 10 new compounds with higher activity than that of the template molecule. The results suggested the Topomer Search technology could be effectively used to screen and design new HIV-1 IN inhibitors and has good predictive capability to guide the design of new HIV/AIDS drugs.