Molecular Mechanism of Salvia miltiorrhiza in the Treatment of Colorectal Cancer Based on Network Pharmacology and Molecular Docking Technology

Abstract

Purpose

This study aimed to investigate the effect of Salvia miltiorrhiza on colorectal cancer, as well as the mechanisms involved.

Methods

The active compounds of Salvia miltiorrhiza and the associated genes in colorectal cancer were sourced from publicly available databases. Targets associated with colorectal cancer were identified by searching the GeneCards and OMIM databases. Subsequently, the Cytoscape 3.6.0 software was employed to create a regulatory network that illustrates the relationships among active ingredients, colorectal cancer, and their corresponding targets. The String database was utilized to generate a PPI network. Molecular docking studies, conducted with AutoDock Vina, verified the binding capabilities of these active components to core targets. The findings from network pharmacology analysis were corroborated through in vitro experiments.

Results

In this study, we identified 39 active components derived from Salvia miltiorrhiza that are predicted to target 544 genes associated with colorectal cancer through network pharmacology. Through a combined analysis of network pharmacology, we isolated three key targets: SRC, IL6, and INS. Molecular docking results convincingly demonstrated Salvia miltiorrhiza’s strong binding affinity to these targets. Additionally, in vitro experiments confirmed that Salvia miltiorrhiza effectively inhibited the progression of colorectal cancer via regulating the INS/SRC/IL6 pathway.

Conclusion

Salvia miltiorrhiza emerges as a compelling herbal intervention for colorectal cancer. This study lays the foundation for potential future clinical trials assessing the efficacy of Salvia miltiorrhiza in the management of colorectal cancer.

Keywords:

• Salvia miltiorrhiza
• network pharmacology
• traditional Chinese medicine
• docking technology
• colorectal cancer

Data Sharing Statement

The datasets used or/and analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

The authors gratefully acknowledge the Hengyang Science and Technology Board Program (Grant/Award Number.S2018F9031021264.).

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this article.