Validation of quercetin in the treatment of colon cancer with diabetes via network pharmacology, molecular dynamics simulations, and in vitro experiments.

Abstract

This study built a prognostic model for CRC-diabetes and analyzed whether quercetin could be used for CRC-diabetes treatment through a network of pharmacology, molecular dynamics simulation, bioinformatics, and in vitro experiments. First, multivariate Cox proportional hazards regression was used to construct the prognosis modelof CRC-diabetes. Then, the intersection of quercetin target genes with CRC-diabetes genes was used to find the potential target for quercetin in the treatment of CRC-diabetes. Molecular docking and molecular dynamics simulations were used to screen the potential targets for quercetin in the treatment of CRC-diabetes. Finally, we verified the target and pathway of quercetin in the treatment of CRC-diabetes through in vitro experiments. Through molecular docking, seven proteins (HMOX1, ACE, MYC, MMP9, PLAU, MMP3, and MMP1) were selected as potential targets of quercetin. We conducted molecular dynamics simulations of quercetin and the above proteins, respectively, and found that the binding structure of quercetin with MMP9 and PLAU was relatively stable. Finally, according to the results of Western blot results, it was confirmed that quercetin could interact with MMP9. The experimental results show that quercetin may affect the JNK pathway, glycolysis, and epithelial-mesenchymal transition (EMT) to treat CRC-diabetes. Based on the TCGA, TTD, DrugBank, and other databases, a prediction model that can effectively predict the prognosis of colon cancer patients with diabetes was constructed. According to experiment results, quercetin can regulate the expression of MMP9. By acting on the JNK pathway, glycolysis, and EMT, it can treat colon cancer patients with diabetes.