Using integrated GC-MS analysis, in vitro experiments, network pharmacology: exploring migao fatty oil active components/mechanisms against coronary heart disease

Abstract

Coronary heart disease (CHD) is one of the main diseases causing morbidity and mortality globally, with oxidative damage and lipid peroxidation associated with oxidative stress and atherosclerosis. Cinnamomum migao is a Miao ethnomedicine that has been shown to provide relief from CHD symptoms. A gas chromatograph-mass spectrometer (GC-MS) was used to determine the chemical components of ten batches of migao fatty oil (MFO), yielding a total of 35 chemical constituents. The antioxidant activity of MFO in vitro was assessed using the DPPH· and ABTS·⁺ assay methods, and both indicated good antioxidant activity. The network pharmacology predicted the active constituents of MFO and their therapeutic influence on the mechanism of oxidative damage-induced coronary heart disease (OD-CHD). Six compounds were discovered in MFO, including tau-cadinol acetate and dodecanoic acid, which may play a role in OD-CHD by acting on lipids and atherosclerosis, the PI3K-Akt signalling pathway, and other pathways. In conclusion, our study lays the foundation for investigating the use of MFO in the treatment of OD-CHD.

Keywords:
migao fatty oil; oxidative damage-induced coronary heart disease; antioxidant activity; network pharmacology; in vitro experiments

1 Introduction

In recent years, an increasing number of scientists have concentrated on investigating free radicals and redox pathways towards assisting in the prevention of cardiovascular disease, tumours, and other diseases and ageing (Hu et al., 2021; Liang et al., 2021; Panov & Dikalov, 2020). The free radicals in the cells of the human body are in a dynamic balance under normal conditions, and are continuously produced in the human body, resulting from pollution, radiation, sunlight exposure, and other factors. Because the body's antioxidant defence system cannot destroy them, excessive generation of free radicals damages cellular proteins, lipids, and DNA, causing cell necrosis and apoptosis (Ullah et al., 2017). Antioxidants are thus a critical component of the body's defence against oxidative damage (Gatasheh et al., 2021; Chen et al., 2021; Halliwell et al., 2021). They trap and neutralize free radicals, hence preventing free radical harm to the human body (Halliwell, 2020). Finding high-efficiency, low-toxicity, and reasonably priced antioxidants from natural medicines and foods has thus become an important direction of research in this field.

Coronary heart disease (CHD) is a highly prevalent cardiovascular disease with increasing morbidity and mortality as the population ages. There is much evidence suggesting that oxidation plays a key role in the progression of atherosclerosis at all stages (Zhong et al., 2019). Fatty acids, present in fatty oils, have special lipophilic and electron-stabilizing properties that make them a promising class of natural medical antioxidants (Sherratt & Mason, 2018). By quickly forming less harmful free radical compounds, protein free radical damage can be rapidly repaired, avoiding the emergence of cascades of new reactive species and therefore avoiding atherosclerosis and coronary heart disease (Gebicki & Nauser, 2021).

Migao is the dry ripe fruit of Cinnamomum migao H.W.Li which belongs to the Cinnamomum Trew family of Lauraceae. Migao can be soaked in water and eaten like kimchi, and it can also be used for seasoning in cooking. Both methods have a similar function of strengthening the spleen-stomach. The fruit can also be broken or powdered and ingested for heart pain in China, which can instantly ease the pain. Migao, according to Hmong medicine, is able to warm middle-jiao to dispel colds, regulate qi, and relieve pain. Migao may protect against acute myocardial ischemia injury by boosting antioxidant efficacy, according to modern pharmacological investigations. However, its antioxidant activity mechanism has yet to be acknowledged (Li & Yang, 2021). Researchers discovered that MFO has the ability to treat CHD, but the chemical composition of MFO was unknown and there was no standardised antioxidant test technique.

Despite significant developments in CHD, such as interventional and surgical therapy, the issue of providing effective and safe care to patients with circulatory failure caused by CHD is still a topic of conversation. Creating bioactive foods with several compositions is another means, in addition to creating medications to treat CHD, that may be used at various phases of the disease's development. This approach not only serves as a preventive precaution for those who have no clinical symptoms of the condition but also encourages the development of food treatment, which may be combined with medication or surgery.

To learn more about MFO's chemical composition and mechanism of action in the treatment of OD-CHD, we used a gas chromatograph-mass spectrometer (GC-MS) to analyse the compositions of 10 batches of MFO; we then used network pharmacology and molecular docking technology to predict the pharmacodynamic material basis and mechanism of MFO in the treatment of OD-CHD from a molecular perspective; simultaneously, the DPPH method and the ABTS·⁺ assay methods were employed to assess the in vitro antioxidant capabilities of MFO in order to develop a more acceptable test method for fatty oil antioxidants (Figure 1). The goal of this research is to establish a theoretical foundation for fully using Migao medicinal material resources, as well as to create the groundwork to produce Guizhou-area-specific medicinal material.

Figure 1
Integrated workflow for discovery of the potential mechanisms of MFO against OD-CHD.

2 Materials and methods

2.1 Materials and reagents

Ten batches of migao were identified as the dry ripe fruit of Cinnamomum migao H.W.Li by Professor Sun Qingwen of Guizhou University of Traditional Chinese Medicine (Table 1). The reagents used were 1,1-diphenyl-2-trinitrophenylhydrazine (DPPH, purity ≥ 97.0%), Tihibu (Shanghai) Chemical Industry Development Co., Ltd.; Diammonium 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonate) (ABTS, purity ≥ 98.0%), Hefei Bomei Biotechnology Co., Ltd.; potassium persulfate, potassium hydroxide, hexanes, sodium hydroxide, hydrochloric acid, methanol, ethanol absolute, petroleum ether (30-60 °C) and were all of analytical grade, plus homemade distilled water.

Table 1
Source information of Cinnamomum migao.

S/N	Latin name	Market address
S1	Litsea lancilimba	Luodian, Guizhou
S2	Litsea lancilimba	Luodian, Guizhou
S3	Litsea lancilimba	Luodian, Guizhou
S4	Litsea lancilimba	Cheheng, Guizhou
S5	Litsea lancilimba	Cheheng, Guizhou
S6	Litsea lancilimba	Anlong, Guizhou
S7	Litsea lancilimba	Gongli, Guizhou
S8	Litsea lancilimba	Tiane, Guangxi
S9	Litsea lancilimba	Tiane, Guangxi
S10	Litsea lancilimba	Wangmo, Guizhou

2.2 Analysis of Chemical Composition of MFO

Preparation of MFO

Extraction of MFO

MFO was extracted by the Soxhlet extractor method. The extraction solvent was petroleum ether, the ratio of material to liquid (g/mL) was 1: 15, and the temperature was 85 °C for the extraction. The extract was transferred to a weighing bottle after passing through a rotary evaporator, and dried in an oven at 105 °C for 1 h to obtain the MFO.

Preparation of methyl esterified MFO

To accurately weighed MFO (0.50 g) was and added 20 mL of 0.5 mol/mL potassium hydroxide-methanol solution, then placed it in a 60 °C water bath for 15 min, and removed to cool. Thereafter, 40 mL of 25% hydrochloric acid was added, placed in a 60 °C water bath for 15 min, and then removed to cool. Another 20 mL of n-hexane was added and mixed well. Finally, 20 mL of saturated sodium hydroxide was added and left to stand for 15 min. The supernatant was evaporated to dryness under reduced pressure to obtain methyl esterified MFO (Huang et al., 2020).

GC-MS analysis conditions

GC-MS was performed on an Agilent HP6890/5975C GC-MS (USA) to profile the chemical composition of each MFO. GC was equipped with an Rtx-5 MS(30 m×0.25 mm×0.25 μm) capillary column. Temperature programming: the column temperature was 100 °C, rose to 130 °C at the rate of 3 °C/min and then at 2 °C/min to 230 °C for 2 min. Running time 60 min. Vaporization chamber temperature 230 °C. The carrier gas was high purity helium (99.999%). The precolumn pressure was 18.49 psi, the carrier gas flow was 1.0 mL/min, the split ratio was 10:1, and the solvent delay time was 5.5 min. The ion source was an EI source, and its temperature was 230 °C; electron energy 70 eV. Emission current 34.6 μA; multiplier voltage 1953 V; the interface temperature was 280 °C; and the mass ranged from 50 to 500 amu.

Analysis of the composition of MFO

After obtaining mass spectral information from GC-MS, it was matched against the NIST 17 database. The peak area normalization method was used to express its relative percentage.

2.3 Determination of antioxidant activity

Preparation of MFO solutions

The MFO sample under 2.2.1 above, was prepared ensuring sample solutions with a mass concentration of 0.5, 1, 1.5, 2.0, 2.5 mg·mL^-1 using absolute ethanol.

DPPH ((2,2-Diphenyl-1-picrylhydrazyl)) free radical scavenging assay

The antioxidant activity of MFO was measured in terms of radical scavenging ability, using a DPPH plant assay. All measurements were performed as follows: an amount of 1.0 mL of the five different concentrations of liquid extract was added to 2.0 mL of the DPPH· ethanol solution with a mass concentration of 0.1 mmol L^-1, and the absorbance readings were taken after 30 min against the blank at 517 nm (Zhang et al., 2022b; Nie et al., 2022). The antioxidant capacity was calculated using the following Equation 1 where, (Ac: the absorbance of DPPH· solution and solvent, Ai: the absorbance of the sample solution and DPPH· solution, Aj: the absorbance of solvent solution and the sample):

$\text{Radical Scavenging Capacity (\%)}=\frac{Ac-(Ai-Aj)}{Ac}\times 100\%$ (1)

ABTS·⁺ (2,2′-azinobis-(3-ethylbenzothiazoline-6-sulphonate) free radical scavenging assay

ABTS·⁺ solution (7 mmol/L) and potassium persulfate solution (2.45 mmol/L) should be mixed in equal amounts. The reaction system was placed at room temperature and sheltered from light for 24 hours, diluted with anhydrous ethanol, the absorbance set at 734 nm (Jovanović et al., 2021; Aljobair, 2022), and the wavelength was 0.70 (± 0.002). In this way, the ABTS·⁺ working solution was obtained. All measurements were performed as follows: the amount of 2.0 mL of liquid extract was added to 2.0 mL of the ABTS·⁺ working solution, and the absorbance readings were taken after 6 min at 734 nm. The antioxidant capacity was calculated using the following Equation 2 (A_Sample-the absorbance of the sample and ABTS·⁺ working solution, A_Blank-the absorbance of ABTS·⁺ working solution and solvent, A_control-the absorbance of solvent solution and the sample)

$\text{Radical Scavenging Capacity}=\frac{A_{Blank}\text{-(}{A}_{Sample}\text{-}{A}_{Control})}{A_{Blank}}\times 100\%$ (2)

2.4 Network pharmacology analysis predicts mechanism of oxidation resistance

Screening of active ingredients of MFO

To obtain the active chemical ingredients, we used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) to screen the chemical components under section 2.2 above. Its screening conditions were oral bioavailability (OB) ≥ 30% and drug-likeness index (DL) ≥ 0.18 (Liu et al., 2022); or we used PubChem to obtain the 2D structure or Canonical Smiles information of the chemical components, and imported the information into the SwissADME database (http: https://www.swissadme.ch/) for screening (Oh et al., 2021). The filter conditions were that the (gastro-intestinal) GI absorption value was “high”, and the five amounts under Drug-likeness were “Yes”

Prediction of the active ingredient target of MFO

The Canonical Smiles of active ingredient were entered into the SwissTargetPrediction database (http://www.swisstargetprediction.ch/), and the species was defined as “homo sapiens”, followed by a probability > 0 screening (Zhu et al., 2022). It was merged with the predicted targets of the TCMSP database corrected by the UniProt database (https://www.uniprot.org), and the target genes of the MFO's active components were obtained after deduplication.

OD-CHD related targets gene screening

Using “Oxidation damage” and “Coronary Heart Disease” as the search keywords, we searched the GeneCards database (https://www.gene-cards.org) (Yu et al., 2022), and OMIM database (http://www.omim.org) (Wang et al., 2022b), to obtain potential targets associated with OD-CHD. The two disease database targets were combined and the repeat value was deleted to get the OD-CHD related targets.

Interaction network of component-target

We used the Venny 2.1.0 online mapping tool to draw a Venn diagram of the potential targets of the active ingredients of MFO and OD-CHD related targets, and to obtain the intersection targets of MFO and OD-CHD. The intersection targets were imported into Cytoscape 3.8.2 software to construct an interaction network of component targets.

Protein-Protein Interaction (PPI) network and core target genes

The common targets of MFO and OD-CHD were imported into the STRING database (http://string-db.org/) (Li et al., 2022), and the targets with interaction confidence greater than 0.4 were selected. Import it into Cytoscape 3.8.2 software to get PPI visualization network diagram. Finally, with the help of the “CytoHubba” plug-in of the software, the top 5 target genes were obtained, which were the core target genes.

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis

Using the Metascape database (http://metascape.org/), GO functional annotation and KEGG pathway enrichment analysis were performed on the intersection target genes of MFO and OD-CHD, and p < 0.01 was used as the screening condition (Wei et al., 2022). The enrichment results were displayed using the SRplot (http://www.bioinformatics.com.cn/ srplot).

Molecular docking verification

Six active ingredients were selected for molecular docking with the five key target genes. Pre-processing the protein receptor molecule was performed by using the Py MOL software after having downloaded the 3D structures of major possible target proteins from the RCSB PDB library (https://www.pdbus.org/) (Wu et al., 2022). We downloaded the 3D structures of key potential target proteins from the RCSB PDB database (https://www.pdbus.org/), and used the Py MOL software to pre-process the protein receptor molecule (Sun et al., 2022). The pre-treatment of active compound ligands was performed using OpenBabelGUI software. We imported the pre-processed potential targets and active compound components into the docking software Auto Dock for molecular docking. With the help of Py MOL software, the compounds with a higher docking score and more stable conformation were combined with the target protein to perform molecular docking visualisation analysis (Zhang et al., 2022a).

3 Results

3.1 Composition analysis of MFO

In the ten batches of MFO, a total of 35 fatty acid components were identified. Among them, eight fatty acid components, with a relative percentage of 54.73%, were among the 38 components that were isolated from S1. From S2 – S10 there were, respectively: S2 (relative percentage 85.75%), comprising 20 fatty acids from 53 components; S3 (91.73%), 11 fatty acids from 23 components; S4 (96.14%), eight fatty acids from 13 components; S5 (93.56%), five fatty acids from 10 components; S6 (96.01%), 9 fatty acids from 18 components; S7 (71.99%), eight fatty acids from 21 components; S8 (76.27%), 20 fatty acids from 67 components; S9 (88.98%), 4 fatty acids, from 7 components; and S10 (96.47%), 9 fatty acids from 14 components. There were 17 medium-chain fatty acids (MCFAs) and 18 long-chain fatty acids among the 35. The peak area normalization method was used to calculate the relative percentage content of each component (Table 2 and Figure 2.)

Table 2
Ten batches of MFO compositions (S1-S10) and relative percentage of constituents.

Compound Name	Formula	S1	S2	S3	S4	S5	S6	S7	S8	S9	S10
Thymol acetate	C12H16O2	0.52	0.23	0.39	0.53	0.61	0.33	1.31	0.19
Methyl decanoate	C11H22O2	18.72	46.06	61.34	51.76	54.26	53.71	16.76	15.32	35.87	36.76
Methyl dodecanoate	C13H26O2	15.46	30.89	23.88	40.16	36.04	38.76	40.55	27.3	44	35.44
(R)-lavandulyl (R)-2-methylbutanoate	C15H26O2	0.61						1.48
Guaiol acetate	C17H28O2	0.62						2	0.78	6.48
Isovaleric anhydride	C10H18O3	4.68
2-Methylbutanoic anhydride	C18H22O2	0.62
5-tert-Butyl-2,2'-dimethoxy-biphenyl	C18H22O2	5.94						4.59
4-Terpinenyl acetate	C12H20O2		0.06
Methyl octanoate	C9H18O2		0.08
Spirobicyclo[2.2.1]heptane-2,2'-(1',3'-dioxa-2'-oxocyclohex-5'-ene)], 1,6',7,7-tetramethyl-	C14H20O3		0.75	1.54					0.07
Neoisothujyl acetate	C12H20O2		0.29	0.33
β-Terpinyl acetate	C12H20O2		0.24	0.17	0.23
Geranyl propionate	C13H22O2		0.14
α-Terpinyl acetate	C12H20O2		0.1					2.2	0.07
Shisool formate	C11H18O2		0.2
Bornyl formate	C11H18O2		1.56
Tau-Cadinol acetate	C17H28O2		1.47	1.18					12.84		1.19
2,6,10-Trimethyl-12-acetoxy-2,6,10-dodecatriene-1-ol	C17H28O3		0.19
Methyl tetradecanoate	C15H30O2		0.45		0.44		0.69		0.65		0.73
Methyl palmitoleate	C17H32O2		0.26						1.37		2.01
Methyl palmitate	C17H34O2		0.83				0.29		3.86		4.76
Methyl elaidate	C19H36O2		0.86	0.79	0.54	1.21	0.71		3.78	2.63	6.84
Methyl vaccenate	C19H36O2		0.6	0.57	0.99				2.71		6.44
Isobornyl formate	C11H18O2			0.31
Borneol, trifluoroacetate (ester)	C12H17F3O2			1.23	1.49	1.44	0.9
Ethyl 1-Methylimidazole-2-carboxylate	C7H10N2O2						0.26		0.17
Decanoic acid	C10H20O2						0.36		2.78
6-Octen-1-one, 3,7-dimethyl-3-ethenyl-1-(4-methoxyphenyl)-	C19H26O2	7.56						3.1
Isothujyl acetate	C12H20O2								1.21
Proximadiol	C15H28O2								0.99
Lauric acid	C12H24O2								0.22
γ-Eudesmol acetate	C17H28O2								0.27
Methyl linoleate	C19H34O2		0.49						1.69		2.3
Methyl stearate	C19H38O2								0.2

Figure 2
GC-MS profile of 10 batches of MFO compositions.

3.2 Antioxidant activity in vitro

Because antioxidant activity varied in vitro, each of the ten batches had its own response characteristics and processes. There was no benchmark that effectively represented all chemicals' antioxidant capacity in complicated systems. Consequently, the antioxidant activity of the ten batches of MFO was determined using the DPPH· and ABTS·⁺ techniques, as indicated in Figure 3. The antioxidant activity of these were positively linked with the mass concentration. S2 displayed high antioxidant activity, according to ABTS·⁺ technology, with a clearance rate of 64.56% - 94.29%. The results of the DPPH· technique demonstrated that S1 had high antioxidant activity, with a clearance rate of 75.88% - 98.87%. Furthermore, we discovered that the clearance rate obtained by the DPPH· approach was often higher than that obtained by the ABTS·⁺ method, which could be owing to the DPPH· reagent's lipophilicity. This meant that when determining antioxidant activity in vitro, we could use a detection method that has features similar to the analyte.

Figure 3
In vitro antioxidant results of 10 batches of MFO using different methods.

We used the Manhattan Distance technique to perform cluster analysis and Pearson’s correlation analysis on the MFO from various origins in order to investigate the relationship between common components and the antioxidant activity. The antioxidant activity measured by the DPPH· method was positively correlated with the contents of methyl decanoate and methyl dodecanoate, whereas the antioxidant activity measured by the ABTS·⁺ method was negatively correlated with the contents of methyl decanoate and methyl dodecanoate, as shown in Figure 4. The features of migao were similar that of DPPH· since the common components are all fatty acids before methyl esterification, indicating that the DPPH· approach was better for determining the antioxidant activity of fatty oils. Figure 5 showed that S1 (September 2018), S2 (September 2019), S4 (September 2019) were the same class; S3 (October 2019) was a solitary class; S7 (October 2020) and S9 (October 2020) were the same class; S5 (October 2019) and S6 (October 2020) were the same class; S8 (October 2020) and S10 (October 2020) were the same class; and the collection time of this classification was closely related.

Figure 4
Results of Pearson correlation analysis.

Figure 5
Results of cluster analysis with Manhattan Distance technique.

3.3 Network pharmacology research

Active ingredients of MFO

TCMSP and SwissADME were used to screen the chemical compositions of 35 MFO under section “3.1” yielding a total of six MFO active ingredients (see Table 3).

Table 3
Active ingredient information of MFO.

PubChemCID	Chemical composition	Molecular structure	Screening conditions
			OB	DL	GI absorption	Druglikeness(Yes)
87232330	(R)-lavandulyl (R)-2-methylbutanoate		-	-	High	5
5363409	2,6,10-Trimethyl-12-acetoxy-2,6,10-dodecatriene-1-ol		-	-	High	5
564724	Trifluoroacetyl-epiisoborneol		-	-	High	5
14683249	Tau-Cadinol acetate		-	-	High	5
3893	Dodecanoic acid		23.59	0.04	High	5
240122	Guaiol acetate		-	-	High	5

Targets of active ingredients and OD-CHD

After sorting the prospective targets predicted by TCMSP and the SwissTargetPrediction website, a total of 320 potential targets were found. Thereafter after sorting out the GeneCards and OMIM databases, 1239 OD-related targets and 1434 CHD-related targets were found. In total 67 target genes at the intersection of MFO and OD-CHD were discovered using the Venny 2.1.0 online drawing tool(Figure 6).

Figure 6
MFO and OD-CHD intersection target genes.

Construction of “active ingredients-targets-OD-CHD” network

MFO's six active ingredients and the Venny online tool's 67 intersecting targets were combined in Cytoscape 3.8.2 software to create an “active ingredient-target-OD-CHD” network, as illustrated in Figure 7. There were 94 nodes and 198 edges in the network. 2,6,10-trimethyl-12-acetoxy-2,6,10-dodecatriene-1-ol, tau-cadinol acetate, (R)-lavandulyl (R)-2-methylbutanoate, dodecanoic acid, guaiol acetate, and trifluoroacetyl-epiisoborneol could interact with 24, 22, 21, 19, 18 and 2 target proteins, respectively, based on the degree value.

Figure 7
MFO “active ingredient-OD-CHD” network.

PPI network analysis

The STRING database (http://string-db.org/) was used to import the common targets of MFO and OD-CHD, and the results were shown using Cytoscape 3.8.2 software, as shown in Figure 8. The network included 67 nodes, which constituted 538 interaction relationships (in the network, the size and colour of nodes were positively correlated with the importance of nodes). Using the “CytoHubba” plugin, the top five target genes were AKT Serine/Threonine Kinase 1 (AKT1), Tumor Necrosis Factor (TNF), Epidermal Growth Factor Receptor (EGFR), Prostaglandin-Endoperoxide Synthase 2 (PTGS2), and Matrix Metallopeptidase 9 (MMP9), which were predicted to be closely related to OD-CHD.

Figure 8
PPI network of target genes at the intersection of MFO and OD-CHD.

GO and KEGG analysis

The intersection targets were added into the Metascape database, producing 5883 GO enrichment analysis results (p<0.01), comprising 531 molecular functions, 4027 biological processes, and 325 cellular components. The biological process included positive regulation of protein phosphorylation, cellular response to nitrogen compounds, positive regulation of cell migration, etc.; the cell composition included membrane raft, receptor complex, side of membrane, etc.; and the molecular functions included protein serine/threonine/tyrosine kinase activity, nuclear receptor activity, and heme binding, among other things. An SRplot was used to depict the top 10 enrichment results (Figure 9).

Figure 9
GO functional enrichment analysis bubble plot.

KEGG pathway enrichment analysis yielded a total of 239 entries (p < 0.01). Lipid and atherosclerosis, PI3K-Akt signalling pathway, Rap1 signalling pathway, MAPK signalling pathway, Fluid shear stress and atherosclerosis, and other pathways were involved in OD-CHD. The results of these five enrichments were visualized utilizing the SRplot platform (Figure 10).

Figure 10
MFO “target-pathway” interaction network.

Molecular docking verification

The top five core target genes of MFO and OD-CHD were selected for molecular docking with the top six active components of MFO, as shown in Table 4. The smaller the docking binding force value, the more stable the ligand-receptor binding was, and the greater the chance of interaction. Tau-Cadinol acetate had the lowest binding force to matrix metalloproteinase 9 (MMP9), with a value of -7.06 kcal mol^-1 (1 kcal ≈ 4.186 kJ). As demonstrated in Figure 11, components with low binding energies with proteins were chosen for the docking visualization.

Table 4
Molecular docking results.

Active ingredient	Binding energy/kcal·mol-1
	AKT1	TNF	EGFR	PTGS2	MMP9
2,6,10-trimethyl-12-acetoxy-2,6,10-dodecatriene-1-ol	-4.87	-4.00	-3.97	-3.12	-5.48
(R)-lavandulyl (R)-2-methylbutanoate	-3.74	-3.24	-3.09	-3.17	-4.97
tau-cadinol acetate	-5.35	-5.04	-4.55	-4.73	-7.06
dodecanoic acid	-3.25	-2.96	-3.27	-2.60	-3.73
guaiol acetatel	-5.81	-5.51	-4.99	-4.89	-6.74
trifluoroacetyl-epiisoborneo	-4.92	-4.61	-4.49	-3.37	-5.36

Figure 11
Molecular docking mode. (a)2,6,10-trimethyl-12-acetoxy-2,6,10-dodecatriene-1-ol- MMP9; (b) dodecanoic acid-MMP9; (c) guaiol acetatel-MMP9; (d) (R)-lavandulyl (R)-2- methylbutanoate-MMP9; (e) tau-cadinol acetate-MMP9; (f) trifluoroacetyl-epiisoborneo -MMP9.

4 Discussion

The antioxidant activity of 10 batches of MFO were examined in vitro in this study, and all showed good antioxidant activity. Increasing numbers of academics have focused on MCFAs in recent years. MCFAs have been shown in studies to not only reduce myocardial oxidative damage, but also to be converted by the liver into ketone bodies as an alternative energy source to compensate for cardiac injury (Saifudeen & Renuka, 2021). The MCFAs, capric acid and dodecanoic acid have proved to have good antioxidant properties (Mett & Müller, 2021; Mett, 2021). In addition, dodecanoic acid can also enhance mitochondrial respiration and glycolysis in cardiomyocytes, as well as suppress inflammatory gene expression (Venkatesan et al., 2022). The concentration of capric and dodecanoic acids were high in our 10 batches of MFO, ranging from 33.77%~90.86% of the total fatty oil. Migao is thus projected to be a new source of natural medications for the treatment of OD-CHD.

With the use of GC-MS, the chemical composition of MFO was determined, and data from the OD-CHD public database was combined. Network pharmacology was used to predict the potential targets and mechanisms of MFO in the treatment of OD-CHD. The top five targets of MFO in the treatment of OD-CHD were AKT1, TNF, EGFR, PTGS2, and MMP9. Pathway analysis showed that MFO mainly regulated lipids and atherosclerosis, PI3K-Akt occurs in the signalling pathway, Rap1 signalling pathway, and MAPK signalling pathway, and the fluid shear stress that influences atherosclerosis and other pathways may be targeted to treat OD-CHD.

Through the analysis of core genes and main pathways, MFO may be involved in the oxidation process, inflammatory response, endothelial dysfunction and other processes, to play a role in the treatment of OD-CHD. For example, AKT1 was the major AKT isoform in the heart and blood vessels, and the activation of AKT1 was associated with inflammation, oxidative stress, accumulation of oxidized lipids, and formed a positive feedback loop exacerbating the consequences of oxidative stress. Interfering with Akt1 signalling in vivo may therefore protect and improve survival under dyslipidaemia by reducing oxidative stress and the response to oxidized lipids (Wang et al., 2022a; Hu et al., 2020). Atherosclerosis is a chronic inflammatory condition in which lipid-rich plaques in the walls of arteries result in constriction. Elevated levels of low-density lipoprotein cholesterol (LDL) constitute major risk factors for atherosclerosis (Lau et al., 2021). LDL is oxidatively modified and accumulates in blood vessel walls. Oxidized low-density lipoprotein is involved in the production of adhesion molecules and the recruitment of monocytes to the subendothelial region, affecting oxidative stress, inflammation, and endothelial dysfunction. Monocytes multiply and develop into macrophages, hastening plaque formation, local inflammation, and thrombosis (Jia et al., 2022; Xiong et al., 2022). Therefore, for prevention, lipid aggregation and oxidation must be avoided. The vascular physiology and pathobiology of the vessel wall are influenced by fluid shear stress (FSS) acting on the vessel lumen. FSS has been shown to prevent the formation of atherosclerotic plaques by boosting endothelial denudation and vascular smooth muscle cell production, as well as upregulating endogenous antioxidant genes (Psefteli et al., 2018).

Rap1 is a member of the Ras family of small GTPases, and its activation improves vascular barrier function (Yamamoto et al., 2021). Rap1 mainly promotes nitric oxide release during laminar flow and mostly suppresses pro-inflammatory signals in the absence of laminar flow, hence guarding against atherosclerosis (Singh et al., 2021). Rap1 deficiency causes excessive nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activation and increased production of large reactive oxygen species. As a result, intervening in the Rap1 signalling pathway can help prevent atherosclerosis (Wong et al., 2018).

MFO may play a role in the therapy of OD-CHD by interfering with the pathways and targets mentioned above, as predicted by network pharmacology. This suggests that MFO can help OD-CHD by interacting with a variety of targets and pathways.

5 Conclusions

In this study, the anti-oxidative efficacy of MFO was confirmed using in vitro antioxidant tests, the chemical components of MFO were identified using GC-MS, and its mechanism of action in the treatment of OD-CHD was investigated using network pharmacology. The findings suggested that MFO treatment of OD-CHD had multi-component, multi-target, and multi-pathway characteristics, implying that oxidative stress, inflammatory response, endothelial dysfunction, and other processes might be involved. Further research into the mechanism of action of MFO in the treatment of OD-CHD is needed, and our findings will help.

• Practical Application: Migao fatty oil exerts preventive effects on coronary heart disease.

• Funding

  This work was financed by the National Nature Science Foundation of China - Guizhou Provincial People's Government Joint Fund (No.U1812403-2), co-financed by Guizhou Provincial Science and Technology Projects [ZK〔2022﹞463] and Guizhou Province Postgraduate Research Fund Project (YJSKYJJ〔2021﹞164).

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Publication Dates

• Publication in this collection
  28 Oct 2022
• Date of issue
  2022

History

• Received
  27 Aug 2022
• Accepted
  01 Oct 2022