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

Abstract

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.