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 obtained Topomer CoMFA model had both favorable estimation stability and good prediction capability. Topomer Search was used to search the R group from the ZINC database. As a result, a series of R groups with a 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. The 1 Ra groups and 21 Rb groups were employed to substitute alternately the Ra and Rb of sample 42. Finally, 21 new compounds were designed and further their activities were predicted 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.