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. 2021 Mar 31;22(7):3612.
doi: 10.3390/ijms22073612.

The Main Alkaloids in Uncaria rhynchophylla and Their Anti-Alzheimer's Disease Mechanism Determined by a Network Pharmacology Approach

Peng Zeng  1 , Xiao-Ming Wang  1 , Chao-Yuan Ye  1 , Hong-Fei Su  1 , Qing Tian  1
Affiliations

The Main Alkaloids in Uncaria rhynchophylla and Their Anti-Alzheimer's Disease Mechanism Determined by a Network Pharmacology Approach

Peng Zeng et al. Int J Mol Sci. .

Abstract

Alzheimer's disease (AD) is a growing concern in modern society, and effective drugs for its treatment are lacking. Uncaria rhynchophylla (UR) and its main alkaloids have been studied to treat neurodegenerative diseases such as AD. This study aimed to uncover the key components and mechanism of the anti-AD effect of UR alkaloids through a network pharmacology approach. The analysis identified 10 alkaloids from UR based on HPLC that corresponded to 90 anti-AD targets. A potential alkaloid target-AD target network indicated that corynoxine, corynantheine, isorhynchophylline, dihydrocorynatheine, and isocorynoxeine are likely to become key components for AD treatment. KEGG pathway enrichment analysis revealed the Alzheimers disease (hsa05010) was the pathway most significantly enriched in alkaloids against AD. Further analysis revealed that 28 out of 90 targets were significantly correlated with Aβ and tau pathology. These targets were validated using a Gene Expression Omnibus (GEO) dataset. Molecular docking studies were carried out to verify the binding of corynoxine and corynantheine to core targets related to Aβ and tau pathology. In addition, the cholinergic synapse (hsa04725) and dopaminergic synapse (hsa04728) pathways were significantly enriched. Our findings indicate that UR alkaloids directly exert an AD treatment effect by acting on multiple pathological processes in AD.

Keywords: AD pathology; Alzheimer’s disease; Uncaria rhynchophylla; alkaloids; network pharmacology.

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Conflict of interest statement

The authors declare that there are no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Flowchart of the study.
Figure 2
Figure 2
Structures of the main alkaloids extracted from Uncaria rhynchophylla (UR).
Figure 3
Figure 3
Protein–protein interaction (PPI) network construction for target proteins of UR alkaloids against Alzheimer’s disease (AD). (A) A Venn diagram was applied to obtain the intersection between the 10 UR alkaloids and AD targets. (B) Panther classification was used categorize common targets of UR alkaloids against AD. (C) Target proteins involved in protein modification as enzyme (PC00260). (D) PPI network of UR alkaloids against AD. Nodes represent target proteins, and edges represent interactions among targets. The numbers below the nodes indicate the degree. The darker the color and the larger the node are, the greater the degree is.
Figure 4
Figure 4
PPI network clusters of common targets of both UR alkaloids and in AD. (A–F) Clusters 1 to 6 were found with Molecular Complex Detection (MCODE), which can identify densely connected regions. The seed node of each cluster is indicated by red font. (G) Comparison of the MCODE scores of different clusters.
Figure 5
Figure 5
Potential alkaloid target-AD target network. Red nodes represent the main alkaloids extracted from UR, and the numbers beneath each node represent the number of UR targets against AD. Green nodes represent shared targets between potential targets of UR alkaloids and AD targets. UR: Uncaria rhynchophylla; AD: Alzheimer’s disease.
Figure 6
Figure 6
GO biological process (BP) (A) terms and the results of KEGG (B) pathway enrichment analysis of target proteins of UR alkaloids against AD. The X-axis represents the rich factor, the bubble size represents the number of targets enriched in terms, and the color indicates the p-value. (C) Schematic drawing of the Alzheimer disease pathway (hsa05010). Red font indicates the targets of UR alkaloids involved in the Alzheimer disease pathway.
Figure 7
Figure 7
Target-enriched KEGG pathway network for UR alkaloids against AD. Red nodes represent enriched KEGG pathways, and brown nodes represent target proteins.
Figure 8
Figure 8
Bioinformatics analysis of targets of UR alkaloids related to Aβ and tau pathology. (A) Radial bar plot showing targets of the alkaloids significantly correlated with tau, Aβ, or Aβ and tau. (B) PPI network of proteins associated with the pathology of Aβ and tau. The darker the color and the larger the node are, the higher the degree is. (C) Bubble chart of the top 20 biological process (BP) terms identified by GO enrichment analysis. The X-axis represents the rich factor, the bubble size represents the number of targets enriched in terms, and the color indicates the p-value. (D) KEGG pathway enrichment analysis of targets correlated with tau, Aβ, or Aβ and tau. Numbers next to bar graphs indicate the numbers of targets enriched in the terms.
Figure 9
Figure 9
(A–Q) Targets of UR alkaloids against AD in the control and AD groups of the GEO dataset. Entorhinal cortex, n = 39 in each group. Hippocampus, n = 66 in the healthy control group, n = 74 in the AD group. Temporal cortex, n = 39 in the healthy control group, n = 52 in the AD group. Values are presented as the mean ± SD.
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