In:
Anti-Cancer Agents in Medicinal Chemistry, Bentham Science Publishers Ltd., Vol. 23, No. 16 ( 2023-10), p. 1838-1847
Abstract:
To study the pharmacological mechanism of procyanidin B2 (PCB2) on chronic myeloid leukemia
(CML) by integrating network pharmacological methods systematically. Methods: Firstly, the potential target genes of PCB2 were predicted by the pharmacological database and analysis
platform (TCMSP and Pharmmapper). Meanwhile, the relevant target genes of CML were collected from GeneCards and DisGene. Pooled data were collected to screen for common target genes. Furthermore, the above intersection genes
were imported into the String website to construct a protein-protein interaction (PPI) network, and the Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were further analyzed.
Besides, molecular docking was performed to verify the possible binding conformation between PCB2 and candidate targets. Finally, MTT and RT-PCR experiments of K562 cells were performed to verify the above results of network
pharmacology. Results: A total of 229 PCB2 target genes were retrieved, among which 186 target genes had interaction with CML.
The pharmacological effects of PCB2 on CML were related to some important oncogenes and signaling pathways. The top ten core targets predicted by Network Analysis were as follows: AKT1, EGFR, ESR1, CASP3, SRC, VEGFA,
HIF1A, ERBB2, MTOR, and IGF1. Molecular docking studies confirmed that hydrogen bonding was the main interaction force of PCB2 binding targets. According to the molecular docking score, the following three target proteins were
most likely to bind to PCB2: VEGFA (-5.5 kcal/mol), SRC (-5.1 kcal/mol), and EGFR (-4.6 kcal/mol). After treatment of PCB2 for 24h, mRNA expression levels of VEGFA and HIF1A decreased significantly in K562 cells. Conclusion: Through integrating network pharmacology combined with molecular docking, the study revealed the
potential mechanism of PCB2 anti-chronic myeloid leukemia.
Type of Medium:
Online Resource
ISSN:
1871-5206
DOI:
10.2174/1871520623666230526122524
Language:
English
Publisher:
Bentham Science Publishers Ltd.
Publication Date:
2023
SSG:
15,3
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