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. 2024 Jan 11;29(2):362.
doi: 10.3390/molecules29020362.

Uncovering the Anti-Angiogenic Mechanisms of Centella asiatica via Network Pharmacology and Experimental Validation

Bingtian Zhao  1 , Yuanyuan Li  1 , Binya Wang  1 , Jing Liu  1 , Yang Yang  2   3 , Qianghua Quan  2   3 , Quan An  2   3 , Rong Liang  1 , Chunhuan Liu  1 , Cheng Yang  1
Affiliations

Uncovering the Anti-Angiogenic Mechanisms of Centella asiatica via Network Pharmacology and Experimental Validation

Bingtian Zhao et al. Molecules. .

Abstract

Background: Centella asiatica (CA) has been used to address cancer for centuries in traditional Chinese medicine (TCM). Previous studies demonstrated its anti-angiogenesis efficacy, but the underlying mechanism of its action remains to be further clarified. This study aims to investigate the underlying mechanisms of CA and its triterpenes in anti-angiogenesis for cancer therapeutics through network pharmacology and experimental validation.

Methods: Cytoscape was used to construct a network of compound-disease targets and protein-protein interactions (PPIs) from which core targets were identified. GO and KEGG analyses were performed using Metascape, and the AutoDock-Vina program was used to realize molecular docking for further verification. Then, VEGF165 was employed to establish an induced angiogenesis model. The anti-angiogenic effects of CA were evaluated through assays measuring cell proliferation, migration, and tubular structure formation.

Results: Twenty-five active ingredients in CA had potential targets for anti-angiogenesis including madecassoside, asiaticoside, madecassic acid, asiatic acid, and asiaticoside B. In total, 138 potential targets for CA were identified, with 19 core targets, including STAT3, SRC, MAPK1, and AKT1. A KEGG analysis showed that CA is implicated in cancer-related pathways, specifically PD-1 and AGE-RAGE. Molecular docking verified that the active components of CA have good binding energy with the first four important targets of angiogenesis. In experimental validation, the extracts and triterpenes of CA improved VEGF165-induced angiogenesis by reducing the proliferation, migration, and tube formation of human umbilical vein endothelial cells (HUVECs).

Conclusions: Our results initially demonstrate the effective components and great anti-angiogenic activity of CA. Evidence of the satisfactory anti-angiogenic action of the extracts and triterpenes from CA was verified, suggesting CA's significant potential as a prospective agent for the therapy of cancer.

Keywords: Centella asiatica; anti-angiogenesis; cancer; network pharmacology; triterpene.

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Conflict of interest statement

Authors Yang Yang, Qianghua Quan, Quan An were employed by the company Yunnan Baiyao Group Shanghai Science & Technology Co., Ltd. and East Asia Skin Health Research Center. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
CA and angiogenesis-related targets, disease–drug–pathway–target network, and PPI network in colon cancer treatment. (a) Venn diagram of potential targets for the anti-angiogenesis of CA; (b) compound–target network of CA for anti-angiogenesis; (c) PPI network of CA for anti-angiogenesis; (d) core target of PPI network.
Figure 2
Figure 2
Analysis of GO and KEGG enrichment. (a) Top 10 GO terms in the biological process (BP), cellular component (CC), and molecular function (MF) categories (p < 0.05); (b) top 20 KEGG pathways (p < 0.05).
Figure 3
Figure 3
The structure of five core components from CA.
Figure 4
Figure 4
A heat map of binding energies between important active components of CA and the core targets of angiogenesis.
Figure 5
Figure 5
Six extracts (B1–B6) and five core components from CA inhibit the proliferation of HUVECs compared to resveratrol as a positive control. The p-value, ## p ≤ 0.01 in contrast to NS group, * p ≤ 0.05, ** p ≤ 0.01 and *** p ≤ 0.001 compared to Model group.
Figure 5
Figure 5
Six extracts (B1–B6) and five core components from CA inhibit the proliferation of HUVECs compared to resveratrol as a positive control. The p-value, ## p ≤ 0.01 in contrast to NS group, * p ≤ 0.05, ** p ≤ 0.01 and *** p ≤ 0.001 compared to Model group.
Figure 6
Figure 6
Six extracts (B1–B6) and five core components from CA inhibit the migration of HUVECs compared to resveratrol as a positive control. The p-value, * p ≤ 0.05, and ** p ≤ 0.01 compared to Model group.
Figure 6
Figure 6
Six extracts (B1–B6) and five core components from CA inhibit the migration of HUVECs compared to resveratrol as a positive control. The p-value, * p ≤ 0.05, and ** p ≤ 0.01 compared to Model group.
Figure 7
Figure 7
Six extracts (B1–B6) and five core components from CA inhibit the node formation of HUVECs compared to resveratrol as a positive control. The p-value, * p ≤ 0.05, and *** p ≤ 0.001 compared to Model group.
Figure 7
Figure 7
Six extracts (B1–B6) and five core components from CA inhibit the node formation of HUVECs compared to resveratrol as a positive control. The p-value, * p ≤ 0.05, and *** p ≤ 0.001 compared to Model group.
Figure 8
Figure 8
Six extracts (B1–B6) and five core components from CA inhibit the tube formation of HUVECs compared to resveratrol as a positive control. The p-value, * p ≤ 0.05, compared to Model group.
Figure 8
Figure 8
Six extracts (B1–B6) and five core components from CA inhibit the tube formation of HUVECs compared to resveratrol as a positive control. The p-value, * p ≤ 0.05, compared to Model group.
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