Background:
In recent years, the number of people infected with hepatitis C virus (HCV) has continued to grow, this becoming a major threat to global health, and new anti-HCV drugs are urgently needed. HCV NS5B polymerase is an RNA-dependent RNA polymerase (RdRp), which plays an important role in virus replication, and can effectively prevent the replication of HCV sub-genomic RNA in daughter cells. It is considered a very promising HCV therapeutic target for the design of anti-HCV drugs.
Methods:
In order to explore the relationship between the structure of benzimidazole derivatives and its inhibitory activity on NS5B polymerase, holographic quantitative structure-activity relationship (HQSAR) and Topomer comparative molecular field analysis (CoMFA) were used to establish benzimidazole QSAR model of derivative inhibitors.
Results:
The results show that for the Topomer CoMFA model, the cross-validation coefficient q2 value is 0.883, and the non-cross-validation coefficient r2 value is 0.975. The model is reasonable, reliable, and has good predictive ability. For the HQSAR model, the cross-validated q2 value is 0.922, and the uncross-validated r2 value is 0.971, indicating that the model data fits well and has high predictive ability. Through the analysis of contour map and color code diagram, 40 new benzimidazole inhibitor molecules were designed, and all of them have higher activity than template molecules, and the new molecules have significant interaction sites with protein 3SKE.
Conclusion:
The 3D-QSAR model established by Topomer CoMFA and HQSAR has good prediction results and the statistical verification is valid. The newly designed molecules and docking results provide theoretical guidance for the synthesis of new NS5B polymerase inhibitors, and for the identification of key residues that the inhibitor binds to NS5B, which helps to better understand its inhibitory mechanism. These findings are helpful for the development of new anti-HCV drugs.