AUTHOR=Ye Xian-wen , Wang Hai-li , Cheng Shui-qing , Xia Liang-jing , Xu Xin-fang , Li Xiang-ri 

TITLE=Network Pharmacology-Based Strategy to Investigate the Pharmacologic Mechanisms of Coptidis Rhizoma for the Treatment of Alzheimer's Disease

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=Volume 14 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2022.890046

DOI=10.3389/fnagi.2022.890046

ISSN=1663-4365

ABSTRACT=Background: Alzheimer's disease (AD) is becoming a more prevalent public health issue in today's culture. There is a lack of effective drugs to treat AD.
Objective: This study focuses on network pharmacology to clarify the mechanism of Coptidis Rhizoma's (CR) multi-target impact on Alzheimer's disease.
Methods: The Phytochemical-compounds of CR have been accessed from TCMSP and Symmap database or based on HPLC . The values of oral bioavailability (OB) ≥ 30% and Drug Like (DL) ≥ 0.18 or blood ingredient were used to screen the active components of CR; the interactive network of targets and compounds was constructed by STRING and Cytoscape platform, and the network was analyzed by Molecular Complex Detection (MCODE); GO function, KEGG and metabolic pathway enrichment of targets were carried out with Metascape, David and MetaboAnalyst platform; Based on Cytohubb, the potential efficient targets were screened by Maximal Clique Centrality (MCC) and Degree, the correlation between potential efficient targets and Aβ, Tau pathology was analyzed by Alzdata database, and the genes related to aging were analyzed by Aging Altas database, and finally, the core targets were obtained; The binding ability between ingredients and core targets evaluated by molecular docking, and the clinical significance of core targets was assessed with GEO database.
Results: 19 active components correspond to 267 therapeutic targets for AD, of which 69 is potentially effective; In module analysis, RELA, TRAF2, STAT3, and others are the key targets of each module; Among the 6 core targets, RELA, MAPK8, STAT3, and TGFB1 have clinical therapeutic significance; GO function, including 3050 BP, 257 MF, 184 CC, whose functions are mainly related to antioxidation, regulation of apoptosis and cell composition; the HIF-1 signaling pathway, Glutathione metabolism is the most significant result of 134 KEGG signal pathways and four metabolic pathways, respectively; Most of the active components have an excellent affinity in docking with critical targets.
Conclusion: The pharmacological target prediction of CR based on molecular network pharmacology paves the way for networking multi-level strategy. The study of CR in AD treatment shows a bright prospect for curing neurodegenerative diseases.