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. 2023 Jan 25:2023:1638966.
doi: 10.1155/2023/1638966. eCollection 2023.

Systematically Investigating the Pharmacological Mechanism of Momordica grosvenori in the Treatment of Spinal Cord Injury by Network Pharmacology and Experimental Verification

Jiling Wang  1 , Zihong Yang  2 , Jie Jiang  2 , Yang Xv  3   4 , Xiuwei Tan  1 , Ruyu Chen  3 , Fengxin Li  3 , Changqiu Li  3 , Yiji Su  3   4
Affiliations

Systematically Investigating the Pharmacological Mechanism of Momordica grosvenori in the Treatment of Spinal Cord Injury by Network Pharmacology and Experimental Verification

Jiling Wang et al. Evid Based Complement Alternat Med. .

Abstract

Objective: This study aimed to explore the molecular mechanism of Momordica grosvenori (MG) in spinal cord injury (SCI) by network pharmacology analysis.

Methods: We searched for potential active MG compounds using the TCMSP database and the BATMAN-TCM platform. The Swiss target prediction database was used to find MG-related targets and the targets of SCI from the CTD, GeneCards, and DrugBank databases. Following that, a protein-protein interaction (PPI) study was carried out. Cytoscape software was used to calculate the hub gene, and R software was used to evaluate the Gene Ontology (GO) and KEGG enrichment pathways. Finally, molecular docking between the hub protein and important compounds was performed. We verified STAT3, MAPK1, HSP90AA1, PIK3R1, PIK3CA, and RXRA potential targets by quantitative PCR.

Results: We obtained 293 MG-anti-SCI targets with potential therapeutic utility by intersecting 346 MG-related targets and 7214 SCI-related targets. The top 10 identified genes, ranking in descending order of value, were SRC, STAT3, MAPK1, HSP90AA1, PIK3R1, PIK3CA, RXRA, AKT1, CREBBP, and JAK2. Through enrichment analysis and literature search, 10 signaling pathways were screened out. The molecular docking of important drugs and hub targets revealed that some had a higher binding affinity. The results of quantitative PCR indicated that MAPK1, RXRA, and STAT3 were expressed differently in in vitro experiments.

Conclusion: In conclusion, the current work indicated that MG might play an anti-SCI role via multicomponent, multitarget, and multichannel interaction, which presents a novel idea for further research into the precise mechanism of MG-anti-SCI interaction.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The overall flowchart of this study.
Figure 2
Figure 2
Venn diagram for MG-related targets and SCI-related targets.
Figure 3
Figure 3
MG-active compounds-targetgenes-SCI network.
Figure 4
Figure 4
PPI network constructed with STRING.
Figure 5
Figure 5
The bar chart of top 10 GO (BP, CC, and MF) enriched items. (a) Biological process (BP), (b) cellular component (CC), and (c) molecular function (MF).
Figure 6
Figure 6
The bar chart of top 10 KEGG enriched pathways.
Figure 7
Figure 7
Molecular docking maps of 10 hub target genes to kaempferol.
Figure 8
Figure 8
The relative mRNA expression of significantly different genes. (a) The relative mRNA expression of STAT3. (b) The relative mRNA expression of MAPK1. (c) The relative mRNA expression of RXRA. (d) The relative mRNA expression of PIK3CA. (e) The relative mRNA expression of HSP90AA1. (f) The relative mRNA expression of PIK3R1 (∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001 compared to LPS group).
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