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

Abstract

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.

Keywords

• quantitative structure-activity relationship (QSAR)
• proteasome inhibitors
• Topomer CoMFA
• Topomer search
• design of new inhibitors