Identification of potential targets of cinnamon for treatment against Alzheimer's disease-related GABAergic synaptic dysfunction using network pharmacology

Abstract

Cinnamon aqueous extract's active substance base remains unclear and its mechanisms, mainly the therapeutic target of anti-Alzheimer's disease (AD)-related GABAergic synaptic dysfunction, remain unclear. Here, 30 chemical components were identified in the aqueous extract of cinnamon using LC/MS; secondly, we explored the brain-targeting components of the aqueous extract of cinnamon, and 17 components had a good absorption due to the blood-brain barrier (BBB) limitation; thirdly, further clustering analysis of active ingredient targets by network pharmacology showed that the GABA pathway with GABRG2 as the core target was significantly enriched; then, we used prominent protein-protein interactions (PPI), relying on a protein-metabolite network, and identified the GABRA1, GABRB2 and GABRA5 as the closest targets to GABRG2; finally, the affinity between the target and its cognate active compound was predicted by molecular docking. In general, we screened five components, methyl cinnamate, propyl cinnamate, ( +)-procyanidin B2, procyanidin B1, and myristicin as the brain synapse-targeting active substances of cinnamon using a systematic strategy, and identified GABRA1, GABRB2, GABRA5 and GABRG2 as core therapeutic targets of cinnamon against Alzheimer's disease-related GABAergic synaptic dysfunction. Exploring the mechanism of cinnamon' activities through multi-components and multiple targets strategies promise to reduce the threat of single- target and symptom-based drug discovery failure.

Figure 1

Research strategy to find AD-related GABAergic synapse dysfunction by identifying the active ingredients of cinnamon aqueous extracts.

Figure 2

Total ion flow diagram of cinnamon aqueous extract in positive (A) and negative (B) ion modes.

Figure 3

Analysis of cerebral cinnamon targets and corresponding components. The orange circles in the figure represent the active ingredients in the cinnamon water extract that can penetrate the BBB, and the circles with different colors in the middle represent different target types. The entire network graph represents the interaction between the compound and the target.

Figure 4

GO and KEGG pathway enrichment analysis of cinnamon and AD intersection targets. (A-C) GO-BP, MF, CC analyses respectively. (D) KEGG analysis.

Figure 5

Clustering analysis of cinnamon brain-entry targets. (A) Four clusters of cinnamon brain-entry targets. (B) PPI network diagram of brain-entry targets with corresponding targets. (C) GO-BP analysis corresponding to each cluster.

Figure 6

Pathways of brain active chemical compositions based on bioinformation analysis.

Figure 7

Computational procedure for prioritization of targets through network pharmacology. The pipeline for calculating target prioritization composes of 3 symbiotic blocks. The blue block searches metabolites from the Human Metabolome Database (HMDB) that interact with the GBRG2 protein, collates the metabolites, obtains the targets that interact with them, and screens them against drug availability in the Therapeutic Target Database (TTD). The grey module uses the STRING database to extract PPI from the proteins generated by the blue module and constructs a network from them. The green module uses molecular function (MF) annotations to calculate a GO-based semantic similarity score for the export of the blue module compared to GBRG2, ranking the proteins according to their similarity scores. The output of the green module was used to annotate the top 15 proteins in the network.

Figure 8

Integrated GBRG2-expanded multilayer biomolecular interaction network for candidate extraction and semantic similarity ranking of the proteins involved. (A) The complete network constructed using the major protein GBRG2 (orange nodes), linked to its direct metabolites (red nodes) which are linked to the proteins they interact with (blue nodes). We also show the metabolite-protein interactions (grey edges). (B) Semantic similarity ranking of proteins based on molecular function (MF SemSim) is highlighted, with the first 15 similar proteins. (C) The simplified network has only the main protein, with the top 12 similar proteins and metabolites shown separately, while the remaining proteins are grouped into modules and their interactions are merged.

Figure 9

3D docking of the active ingredient (ligand) of cinnamon aqueous extract against AD-related GABAergic synaptic dysfunction targets (receptors) (A-K) The binding effect of ligand and receptor are shown.