Analytical and Quantitative Cytopathology and Histopathology
2021, Volume 43, Issue 6
Research Article
Network Pharmacology Analysis of Quchiling for Alzheimer’s Disease Treatment
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1
Department of Pharmacy, People's Hospital of Ganzhou, Ganzhou, Jiangxi341000, China
2
Department of Pharmacy, Xingguo County People’s Hospital, Ganzhou, China
3
Department of Pharmacy, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
Abstract
OBJECTIVE: To study Quchiling as a treatment for Alzheimer’s disease (AD) using the method of network pharmacology analysis. AD is a progressive neurodegenerative disease without effective drugs for its treatment in clinic. The multi-target compounds from traditional Chinese medicine (TCM) have been paid more and more attention. STUDY DESIGN: We analyzed the pharmacodynamic molecule-target network of Quchiling (a TCM compound include Guangdong Piper Kadsura, schisandra fruit, and acorus gramineus) and AD’s target network by using the method of network pharmacology analysis. In total, 62 specific predicted compounds were screened out in the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and the encyclopedia of traditional Chinese medicine (ETCM) databases, and 152 corresponding targets were predicted. In a GEO database of the brain of AD patients and normal controls, a total of 50 genes, with 22 genes upregulated and 28 genes downregulated, were screened out. In addition, the compound-target network of lipid-soluble components of Quchiling entering to the blood/brain tissues were also analyzed, and the corresponding compound-target-signaling pathway were also revealed by Cytoscape software. The main targets of the Quchiling enriched in AD included FOS, AR, ADRB1, ADRB2, PTGS2, HMOX1, CHRM1, SLC6A3, SLC6A4, ADRA2A, GSTP1, ESR1, ESR2, GAD2, and ADRA1A. RESULTS: The results of the KEGG pathway for gene mapping analysis show that part of the targets were mapping in neuroactive ligand-receptor interaction pathways, calcium signaling pathways, dopaminergic synapse pathways, and apoptotic pathways. The results of GO analysis from the Database for Annotation, Visualization and Integrated Discovery (DAVID) database showed that the drug targets FOS, PTGS2, SLC6A2, SLC6A3, and SLC6A4 were enriched in neuroprotection, and the drug targets FOS, AR, ADRB1, ADRB2, PTGS2, HMOX1, CHRM1, SLC6A3, SLC6A4, ADRA2A, GSTP1, ESR1, ESR2, GAD2, ADRA1A were enriched in AD. CONCLUSION: By integrating the above GEO differential genes with AD genes in GeneCards/OMIM database, the final 1,133 AD-related disease genes were retrieved. After intersecting the 1,133 AD-related genes and the above 152 drug targets, 48 overlapping genes between GEO/GeneCards/OMIM and drug targets were found. © Science Printers and Publishers, Inc.
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Volume 43, Issue 6
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