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

Jian-bo Tong, Yuan-Yuan Li, Guo-Yan Jang, Kang-Nan Li


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 not only has favorable estimation stability but also good prediction capability. Topomer Searchwas 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 for the R1, R2 and R3 of template compound 23 with highest bioactivity. As a consequence, 33 new molecules with higher activity than that of template molecular 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 a guidance.


quantitative structure–activity relationship (QSAR); proteasome inhibitors; Topomer CoMFA; Topomer search; design of new inhibitors


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