Title:Mechanism of Compound Kushen Injection in the Treatment of Acute Myeloid Leukemia from the Analysis Perspectives
Volume: 21
Issue: 1
Author(s): Jia Zeng, Huiqun Tian, Le Kang, Qian Wu, Shiwen Liu, Yugang Xiao, Hongwei Shao, Guangrui Huang*Song Liu*
Affiliation:
- School of Life Science, Beijing University of Chinese Medicine, Beijing, 100029, People's Republic
of China
- School of Pharmacy & Clinical Pharmacy (School of Integrative Pharmacy), Guangdong Pharmaceutical University,
Guangzhou, 510006, People's Republic of China
- Guangdong Province Key
Laboratory for Biotechnology Drug Candidates, Guangdong Pharmaceutical University, Guangzhou, 510006, People's
Republic of China
- Key Specialty of Clinical Pharmacy, The First Affiliated Hospital of Guangdong Pharmaceutical University,
Guangzhou, 510080, People's Republic of China
- Guangdong Provincial Key Laboratory of Advanced Drug Delivery
Systems, Guangdong Pharmaceutical University, Guangzhou, 510006, Guangdong, People's Republic of China
Keywords:
Acute myeloid leukemia, compound kushen injection, network pharmacology, molecular dynamics, molecular docking, PPI.
Abstract:
Background: Chemotherapy resistance often occurs in the conventional treatment with
AML and results in poor cure rates. CKI was found to have a good therapeutic effect when it was
combined with other chemotherapy drugs in the clinical treatment of AML. However, the underlying
mechanism is unclear. Therefore, this study aims to preliminarily describe the pharmacological activity
and mechanism of CKI through comprehensive network pharmacology methods.
Objective: This study aimed to explore the possible mechanism of Compound Kushen Injection
(CKI) in the treatment of acute myeloid leukemia (AML) by using network pharmacology, molecular
docking, and molecular dynamics techniques.
Methods: Active compounds of CKI were identified based on the Traditional Chinese Medicine Systems
Pharmacy (TCMSP) database, and the related targets of the active compounds were predicted using
Swiss Target Prediction; AML-related targets from Gene Cards and Online Mendelian Inheritance in
Man (OMIM) were collected. Protein-protein interaction (PPI) network was constructed, and its mechanism
was predicted through Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes
(KEGG) enrichment. The protein-protein interaction (PPI) network construction, module partitioning,
and hub node screening were visualized by using the Cytoscape software and its plugins. These
module partitionings were also verified by using molecular docking and molecular dynamics modeling.
Results: Fifty-six active ingredients corresponding to 223 potential targets were identified. Biological
function analysis showed that 731, 70, and 137 GO entries were associated with biological processes,
cellular components, and molecular functions, respectively. A total of 163 KEGG pathways were
identified. Network analysis showed that the key anti-AML targets of CKI are MAPK3, EGFR, SRC,
PIK3CA, and PIK3R1 targets, which are involved in the PI3K/Akt and Ras/MAPK signaling pathways
or related crosstalk pathways.
Conclusion: Our results suggested that the key anti-AML targets of CKI, such as MAPK3, EGFR,
SRC, PIK3CA and PIK3R1, are involved in the PI3K/Akt and Ras/MAPK signaling pathways or related
crosstalk pathways. Concentrating on the dynamic and complex crosstalk regulation between
PI3K/Akt and Ras/MAPK signal pathways and related signal pathways may be a new direction in
anti-AML therapy in the future.
