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. 2022 Jul 14:13:932039.
doi: 10.3389/fphar.2022.932039. eCollection 2022.

The potential mechanism of Longsheyangquan Decoction on the treatment of bladder cancer: Systemic network pharmacology and molecular docking

Zhang Cheng  1   2 , Fangdie Ye  1   2 , Chenyang Xu  1   2 , Yingchun Liang  1   2 , Zheyu Zhang  1   2 , Xinan Chen  1   2 , Xiyu Dai  1   2 , Yuxi Ou  1   2 , Zezhong Mou  1   2 , Weijian Li  1   2 , Yiling Chen  1   2 , Quan Zhou  1   2 , Lujia Zou  1   2 , Shanhua Mao  1   2 , Haowen Jiang  1   2   3
Affiliations

The potential mechanism of Longsheyangquan Decoction on the treatment of bladder cancer: Systemic network pharmacology and molecular docking

Zhang Cheng et al. Front Pharmacol. .

Abstract

Our goal was to explore the bioactive constituents of Longsheyangquan (LSYQ) Decoction and elucidate its mechanisms on the treatment of bladder cancer (BCa). A total of 38 compounds were selected based on their pharmacokinetic properties in three large traditional Chinese medicine (TCM) databases. 654 putative targets of LSYQ Decoction were predicted using a structure-based, reverse-docking algorithm online, of which 343 overlapped with BCa-related protein-coding genes. The protein-protein interaction (PPI) network was constructed to perform module analysis for further Gene Ontology (GO) annotations and Kyoto Encyclopedia Genes and Genomes (KEGG) pathway enrichment analysis, which identified CDK2, EGFR, MMP9 and PTGS2 as hub targets. The TCM-compound-target network and compound-target-pathway network together revealed that quercetin, diosmetin, enhydrin and luteolin were the main components of LSYQ Decoction. Finally, molecular docking showed the affinity between the key compounds and the hub target proteins to verify the accuracy of drug target prediction in the first place. The present study deciphered the core components and targets of LSYQ Decoction on the treatment of BCa in a comprehensive systemic pharmacological manner.

Keywords: Longsheyangquan Decoction; bladder cancer; molecular docking; network pharmacology; target; traditional Chinese medicine.

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Conflict of interest statement

The 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
The scheme for investigation of mechanisms of LSYQ Decoction on the treatment of BCa.
FIGURE 2
FIGURE 2
The TCM-compound-target network with 698 nodes and 2,861 edges. TCMs, active compounds and targets were represented by green round rectangular-, orange circular- and blue diamond-shaped nodes, respectively. The greater the Degree value of a node was, the larger the size and lower the transparency were in the network.
FIGURE 3
FIGURE 3
The 343 overlapping targets of LSYQ Decoction and BCa were identified by a Venn diagram.
FIGURE 4
FIGURE 4
The process of screening the hub targets. The left panel showed the initial PPI network (339 nodes and 6,471 edges) of overlapping candidate targets. The middle panel showed the median-filtered PPI network with 133 nodes and 3,323 edges. The right panel (Cluster One) was generated as a result of MCODE module analysis from the middle panel. Cluster One had 48 nodes and 960 edges with a MCODE score of 40.85.
FIGURE 5
FIGURE 5
Enrichment analyses of Cluster One for the top 20 GO annotations and top 25 KEGG pathways (A) GO analysis of biological process terms (B) GO analysis of cellular component terms (C) GO analysis of molecular function terms (D) KEGG pathway analysis.
FIGURE 6
FIGURE 6
Composition and enrichment analyses of Cluster Two (A) Cluster Two had 43 nodes and 261 edges with a MCODE score of 12.43 (B) Significantly enriched GO BP/CC/MF terms and KEGG pathways of Cluster Two were displayed in the Nightingale rose diagram, with the number above each petal representing the gene count enriched in this term. The larger the petal, the lower the adjusted p-value (all the adjusted p-value were under 0.01).
FIGURE 7
FIGURE 7
The compound-target-pathway network for the top 25 KEGG pathways in Cluster One. Pathways, compounds and targets were represented by green triangular-, orange circular- and blue diamond-shaped nodes, respectively. The greater the Degree value of a node was, the larger the size and lower the transparency were in the network.
FIGURE 8
FIGURE 8
Molecular docking of four typical core compounds with four hub target proteins (A) The binding energy heatmap with a deeper color suggesting a more stable binding (B) The molecular docking between CDK2, MMP9 and quercetin or diosmetin. The yellow and orange ligands represented quercetin and diosmetin, respectively. The enlarged view on the right showed the interactions of ligands and amino acid residues of CDK2 and MMP9.
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