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Tumor Discovery Mechanism of Buddleja officinalis against ESCC

2.7. Gene Ontology (GO) and Kyoto Encyclopedia of target gene networks had 24 nodes and 73 edges, as shown
Genes and Genomes (KEGG) pathway enrichment in Figure 2B. The PPI network files were subsequently
analysis visualized by Cytoscape 3.9.1. NetworkAnalyzer utilized
Initially, the potential target genes were converted to the “degrees” to highlight the importance of nodes, and
Entrez IDs using the R package (“org.Hs.eg.db, version = the top five nodes with high degrees were considered core
3.8”). Subsequently, GO biological functions and KEGG targets, that is, serum albumin (ALB), AKT1, insulin-
pathway analysis were visualized by the R packages like growth factor 1 receptor (IGF1), estrogen receptor
(“DOSE,” “clusterProfiler,” and “Pathview”). (ESR1), and fibroblast growth factor receptor 1 (FGFR1)
(Figure 2C and Table 3).
2.8. Docking for dominant ingredients
3.3. GO and KEGG analyses
We investigated the docking of selected active components To further examine whether the biological functions
identified from the BO-ESCC PPI network onto the of the candidates are associated with ESCC, the terms
receptors of threonine protein kinase (AKT1) using
AutoDock software. The names, molecular weights, and subdivided in three distinct ontologies, that is, biological
three-dimensional structures of BO ingredients were process (BP), cellular component (CC), and molecular
function (MF), were enriched in GO and KEGG analyses
initially acquired from PubChem (https://pubchem.ncbi. by R programming language. In the BP group (Figure 3A),
nlm.nih.gov/). Next, the three-dimensional structure of
ingredients was derived from the RCSB protein data bank the results suggested that BO might regulate ESCC-
(http://www.rcsb.org/). Finally, the AutoDock software related BPs, such as organ growth, gland development,
was utilized to facilitate the preparation of ligands and and reproductive structure development. Subsequently,
targets essential for docking. Afterward, for the target the majority of the GO terms are associated with secretory
proteins, the water molecules of the crystal structures granule lumen, cytoplasmic vesicle lumen, and vesicle
were removed, hydrogenation was performed, amino lumen (Figure 3B). In the BP group (Figure 3C), the GO
acids were modified, energy was optimized, and the force terms mainly included transmembrane receptor protein
field parameters were adjusted to satisfy the low-energy kinase activity, glycosaminoglycan binding, and nuclear
conformations of the ligand structures. Subsequently, receptor activity. In addition, 41 signaling pathways
the AKT1 and key active components were molecularly were identified through KEGG pathway analysis as
docked, with the affinity (kcal/mol) value representing significantly enriched (P < 0.05). Figure 4 displays a bar
the binding ability between targets and ligands. Finally, plot showcasing the top 20 important pathways. The
the docking results were observed and analyzed using signaling pathways that are closely related to ESCC include
Discovery Studio software. MAPK signaling pathway, adhesion junction pathway,
and gastric cancer pathway. The gastric cancer pathway is
3. Results closely associated with the MAPK signaling pathway and
is involved in processes such as activation of oncogenes,
3.1. Establishment of the BO active ingredients inactivation of tumor suppressor genes, dysregulation
database of cell cycle control, and impairment of apoptosis in
Six dominant ingredients of BO were retrieved from the gastric cancer. In addition, MAPK signaling pathway, the
TCMSP and HERB databases, including acacetin, linarin, most relevant signaling pathway according to counting
luteolin, butyrospermyl acetate, procyanidin B1, and numbers, is illustrated in Figure 5. The network revealed
neobyakangelicol (Table 1). that BO is associated with the treatment of ESCC through
multiple targets and multiple pathways. Figure 6 shows
3.2. Potential targets of BO for inhibiting ESCC and a compound-target-pathway network centered on the
visualization of PPI network inhibition of ESCC.
By searching the GeneCard and DisGeNET databases, 3.4. Docking of BO dominant ingredients to AKT1
a total of 3640 ESCC target genes were generated after
excluding duplicates. The results of the Venny 2.1 online The six dominant ingredients of BO can bind to AKT1
tool showed that 24 shared BO-ESCC targets were receptor proteins to varying degrees as ligands, and
obtained (Figure 2A and Table 2). To further clarify the the lower vina scores indicate stronger and more stable
relationships among these overlapping target genes, PPI binding capacity between ligands and receptors (Table 4).
network analysis was performed, indicating that these The vina scores of linarin, procyanidin B1, acacetin,

Volume 3 Issue 1 (2024) 4 https://doi.org/10.36922/td.2312