# Mechanisms Underlying the Therapeutic Effects of Brucea javanica in Cervical Cancer Treatment Based on Network Pharmacology and Molecular Docking

## TL;DR

This study explores how Brucea javanica treats cervical cancer by identifying its active compounds and their biological targets and pathways.

## Contribution

The study provides new insights into the mechanisms of Brucea javanica in cervical cancer treatment using network pharmacology and molecular docking.

## Key findings

- Fifteen active compounds and 86 targets were identified, with 51 linked to cervical cancer.
- Key genes like AKT1 were found to influence cancer cell proliferation and apoptosis.
- Molecular docking confirmed strong interactions between active compounds and their targets.

## Abstract

Aims: The aim of this study was to systematically analyze the role of Brucea javanica in the treatment of cervical cancer (CC) and its underlying mechanisms by means of network pharmacology and molecular docking.

Background:
Brucea javanica is a traditional Chinese herbal medicine used for the treatment of malaria and cancers, but its mechanism of action in CC is unknown.

Objective: The objective of the study is screening of active chemical constituents of Brucea javanica by Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and investigating their potential targets involved in CC therapy.

Methods: The GeneCards database was used for the disease targets of CC, the drug–compound–disease target network was constructed by using the Cytoscape 3.8.0 software. Then, the key targets in the protein–protein interaction (PPI) network were identified, and the “clusterProfiler” was used for the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The qRT-PCR, CCK-8, and flow cytometry were used to assess the expression levels of specific target genes in CC cells, as well as their effects on cell proliferation, apoptosis, and reactive oxygen species (ROS) levels, respectively. Protein–compound complex analysis was performed using molecular dynamics simulation.

Results: A total of 15 active compounds and their 86 treatment targets were obtained from the Brucea javanica analysis, in which 51 target genes were associated with the CC-related disease targets. Then, a PPI analysis identified 12 key genes (including EGFR, TP53, BCL2, AKT1, JUN, TNF, CASP3, IL6, MMP9, ERBB2, CCND1, and PTGS2) that were related to oxidative stress, PI3K-Akt, IL-17, p53, and JAK-STAT pathways, inflammatory response, and apoptosis pathways. In addition, AKT1 showed upregulation at the mRNA level in SiHa cells, and the knockdown of AKT1 significantly reduced the proliferation of CC cells and increased apoptosis and ROS levels. Molecular docking and dynamics simulations revealed a close binding between the active compounds and targets.

Conclusions: The present research comprehensively examined the active compounds, potential targets, and pathways of Brucea javanica in CC treatment, providing a novel insight for CC treatment.