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Article

Potential Hepatoprotective Effects of Chamaecyparis lawsoniana against Methotrexate-Induced Liver Injury: Integrated Phytochemical Profiling, Target Network Analysis, and Experimental Validation

1
Department of Pharmacognosy, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt
2
Department of Pharmacognosy, College of Pharmacy, King Saud University, P.O. Box 2457, Riyadh 11451, Saudi Arabia
3
Department of Pharmacology and Toxicology, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt
4
Department of Chemistry, School of Computer, Mathematical and Natural Sciences, Morgan State University, Baltimore, MD 21251, USA
*
Authors to whom correspondence should be addressed.
Antioxidants 2023, 12(12), 2118; https://doi.org/10.3390/antiox12122118
Submission received: 28 October 2023 / Revised: 4 December 2023 / Accepted: 5 December 2023 / Published: 14 December 2023
(This article belongs to the Special Issue Oxidative Stress in Liver Diseases - 2nd Edition)

Abstract

:
Methotrexate (MTX) therapy encounters significant limitations due to the significant concern of drug-induced liver injury (DILI), which poses a significant challenge to its usage. To mitigate the deleterious effects of MTX on hepatic function, researchers have explored plant sources to discover potential hepatoprotective agents. This study investigated the hepatoprotective effects of the ethanolic extract derived from the aerial parts of Chamaecyparis lawsoniana (CLAE) against DILI, specifically focusing on MTX-induced hepatotoxicity. UPLC-ESI-MS/MS was used to identify 61 compounds in CLAE, with 31 potential bioactive compounds determined through pharmacokinetic analysis. Network pharmacology analysis revealed 195 potential DILI targets for the bioactive compounds, including TP53, IL6, TNF, HSP90AA1, EGFR, IL1B, BCL2, and CASP3 as top targets. In vivo experiments conducted on rats with acute MTX-hepatotoxicity revealed that administering CLAE orally at 200 and 400 mg/kg/day for ten days dose-dependently improved liver function, attenuated hepatic oxidative stress, inflammation, and apoptosis, and reversed the disarrayed hepatic histological features induced by MTX. In general, the findings of the present study provide evidence in favor of the hepatoprotective capabilities of CLAE in DILI, thereby justifying the need for additional preclinical and clinical investigations.

1. Introduction

The liver, being the primary organ responsible for metabolism, plays a crucial role in various physiological processes such as storing liver sugar, synthesizing secretory proteins, and detoxifying harmful substances. Any dysfunction or injury to the liver can lead to adverse effects on the body, and in severe cases, it can even result in death. Consequently, liver-related issues have become a significant concern in public health. One of the common problems associated with liver function is drug-induced liver injury (DILI), which refers to the side effects caused by medications and is often the leading cause of acute liver failure. This condition can not only impede therapeutic progress but also restrict drug development and result in the discontinuation of specific medications from the market [1,2].
Methotrexate (MTX), also known as amethopterin, is a versatile medication that has been proven effective in treating a wide range of medical conditions. It is commonly prescribed for skin disorders such as psoriasis and refractory atopic dermatitis, as well as inflammatory and autoimmune diseases like rheumatoid arthritis, vasculitis, and Crohn’s disease. In addition, it is also used to treat various malignant disorders such as leukemia, lung, breast, and uterine cancers, as well as ectopic pregnancy [3,4,5,6].
Despite its effectiveness, methotrexate has a high efficacy/toxicity ratio, which can lead to multiorgan toxicities due to its lack of selective cytotoxicity [7]. This has raised concerns about its use, particularly in high doses or long-term treatments. Liver-related adverse effects are among the most important complications associated with methotrexate, with liver abnormalities ranging from asymptomatic elevations in liver enzymes to fibrosis and even fatal hepatic necrosis [8]. Oxidative stress is undeniably a significant factor in the development of methotrexate-related abnormalities and its cytotoxic effects [9,10,11,12]. The excessive production of reactive oxygen species (ROS) during methotrexate therapy can impair the antioxidant capacity of the liver and cause damage to cell membranes through lipid peroxidation. This ultimately leads to tissue damage [13,14,15]. Additionally, apoptosis, which is a crucial process for maintaining cellular homeostasis, becomes overactivated in adverse conditions [16]. The anticancer properties of methotrexate are attributed to its ability to induce apoptosis [17,18]. Regrettably, methotrexate-induced apoptosis can also affect healthy liver tissues [10]. ROS signaling can further contribute to methotrexate-induced apoptosis, thereby enhancing its cytotoxic effects [19].
Despite these potential toxicities and adverse effects, methotrexate remains a widely used and preferred first-line antirheumatic drug in many countries due to its affordability and effectiveness in treating various medical conditions. Its inclusion in the “World Health Organization’s List of Essential Medicines” highlights its importance in healthcare systems worldwide. Although concerns exist regarding its impact on the liver and potential tissue damage, the benefits of methotrexate outweigh these risks, making it a valuable treatment option for many patients [4,20,21]. Additionally, scientific reports and meta-analyses have emphasized its superior efficacy compared to other available drugs, further emphasizing its significance in medical treatments [21]. Consequently, efforts are underway to develop strategies that can protect the liver and enhance the overall safety profile of methotrexate in order to address its associated hepatotoxicity [22,23].
The therapeutic properties of medicinal herbs have garnered significant attention in recent years for treating a range of human ailments. These herbs have a broad safety profile and can effectively mitigate the cytotoxic effects of more hazardous drugs. As a result, it has become common practice to combine these compounds with methotrexate-based therapeutic approaches [24].
Chamaecyparis lawsoniana (Murr.) Parl., commonly referred to as Lawson’s cypress, is a popular ornamental plant belonging to the Cupressaceae family. It is native to North America and can also be found in several other countries, including Germany, France, the United Kingdom, Australia, and South Africa. This versatile plant has various applications, including in construction and railway sleeper production [25]. It also has a long history of traditional use in treating ailments such as stomach pain, tumors, and lipoma [26]. Previous studies have indicated that extracts from the leaves and bark of this plant have antibacterial, fungicidal, and antioxidant characteristics [27,28]. Nevertheless, until now, no research has been conducted to examine the phytochemical composition of the aerial parts of C. lawsoniana or its potential hepatoprotective effects.
Therefore, the main objectives of this study were to determine the chemical profile of the ethanolic extract of C. lawsoniana aerial parts (CLAE) and to investigate its potential efficacy in protecting against DILI, specifically an acute methotrexate hepatotoxicity model in rats. Further, its antioxidant, anti-inflammatory, and antiapoptotic properties were also investigated. This was achieved through an in silico approach followed by in vivo validation experiments.

2. Materials and Methods

2.1. Plant Material and Extraction

The aerial parts of Chamaecyparis lawsoniana (A. Murray) Parl. were collected in March 2023 from El-Orman Botanical Garden, located in Giza, Egypt. The taxonomic validation of the plant species was conducted by Eng. Therese Labib, a Plant Taxonomy Consultant at the Ministry of Agriculture and former director of the El-Orman Botanical Garden in Giza, Egypt. At the Herbarium of the Pharmacognosy Department, Faculty of Pharmacy, Zagazig University, a voucher specimen with the code ZU-Ph-Cog-0311 was preserved.
The dried powdered aerial parts (400 g) were macerated with 70% ethanol (3 × 1 L) for extraction. Under reduced pressure, the extract was evaporated to yield 65 g of viscous residue.

2.2. Analysis of CLAE Using UPLC-ESI-MS/MS Technique

CLAE (50 mg) was dissolved in a 1 mL solution containing water, methanol, and acetonitrile in a ratio of 50:25:25. The resulting mixture was subjected to vortexing for 2 min, followed by ultrasonication for 10 min. Subsequently, the mixture was centrifuged at 1000 rpm for 10 min. A volume of 50 µL of the sample solution was diluted with reconstitution solvent to a final volume of 1000 µL. From this diluted solution, 10 µL with a concentration of 2.5 µg/µL was prepared for UPLC-ESI-MS/MS analysis in negative mode. The analysis was performed using the ExionLCTM AD UPLC instrument and a TripleTOF 5600+ Time-of-Flight Tandem Mass Spectrometer (AB SCIEX) following the previously described method [29]. As a pre-column, in-line filter disks (0.5 µm × 3.0 mm, Phenomenex®, Torrance, CA, USA) were used, while the analytical column was X select HSS T3 (2.5 µm, 2.1 × 150 mm, Waters®, 40 °C, Milford, MA, USA). The temperature of the column and the flow rate were set at 40 °C and 0.3 mL/min, respectively. As mobile phases, buffers A and B were used; buffer A is a 5 mM ammonium format buffer, pH 8, containing 1% methanol, and buffer B is composed of 100% acetonitrile. Gradient elution was applied as follows: for 20 min, 90% solvent A and 10% solvent B were used, then for the next 5 min, a mixture of 10% solvent A and 90% solvent B was run, and for the last 3 min, the starting elution mixture was used. The tentative identification of the compounds was carried out based on their retention times (RTs), molecular weight, m/z of molecular ion [M−H], and by comparing the accurate mass information from their mass spectrometry (MS) and MS/MS spectra with the MS spectral data generated by the PeakViewTM software version 2.1. The peak area values were estimated using the Extracted Ion Chromatogram Manager in the PeakView software (AB SCIEX, version 1.2.0.3).

2.3. Network Pharmacology

2.3.1. Selection of the Bioactive Compounds of CLAE and Associated Targets

The Canonical SMILES formulas of CLAE constituents, identified by LC-MS, were collected from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/, accessed on 3 July 2023) or using ChemDraw v22.0.0.22 (PerkinElmer Informatics, Inc., Buckinghamshire, UK) and were then submitted to the SwissADME web tool (http://www.swissadme.ch/, accessed on 7 July 2023) [30] to retrieve their pharmacokinetic parameters. The selection of compounds was based on the Lipinski’s rule of five and a bioavailability score of ≥0.55.
The molecular targets associated with the bioactive constituents of CLAE were explored using the PharmMapper (https://www.lilab-ecust.cn/pharmmapper/, accessed on 11 July 2023) [31] and SwissTargetPrediction databases (http://www.swisstargetprediction.ch/, accessed on 11 July 2023) [32] and then authenticated in the UniProt database (https://www.uniprot.org/, accessed on 11 July 2023) [33]. The protein names were standardized, and the duplicate targets were eliminated.

2.3.2. Identification of DILI-Associated Targets

GeneCards (https://www.genecards.org/, accessed on 17 July 2023) [34,35], DisGeNeT (https://www.disgenet.org/search, accessed on 17 July 2023) [36], and Online Mendelian Inheritance in Man (OMIM, https://www.omim.org/, accessed on 17 July 2023) [37] were used for the collection of the DILI-related targets using “Drug-induced hepatotoxicity” as the keyword, then the UniProt IDs and gene symbols of the collected targets were obtained from UniProt and the duplicate targets were removed.

2.3.3. The Establishment of the Protein–Protein Interaction (PPI) and Compound–Target Networks

In Microsoft Excel, the overlaps between the bioactive CLAE components and DILI targets were determined and then illustrated as a Venn diagram. The STRING database v12.0 (https://string-db.org/, accessed on 27 July 2023) [38] was used to construct a PPI network of the overlapped targets at a confidence level of >0.7. Following the construction of the PPI network, a compound–target network was also established connecting the bioactive compounds of CLAE with the overlapping targets. The Cytoscape 3.9.1 software program (NIGMS, Bethesda, MD, USA) [39] was employed to display the networks. The targets and compounds were ranked based on the Degree value using the CytoHubba plugin in Cytoscape [40].

2.3.4. Analysis of Gene Ontology and KEGGs Pathway Enrichment

The Database for Annotation, Visualization, and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/tools.jsp, accessed on 28 July 2023) [41] was employed to conduct the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGGs) pathway enrichment. A significance level of p < 0.05 was employed as a cutoff. Homo sapiens (Human) was selected as the organism, and the data sources GO biological process, GO cellular component, GO molecular function, and KEGGs were chosen. The findings were presented in the form of horizontal bar plots using the SRPlot online toolkit (http://www.bioinformatics.com.cn/en, accessed on 28 July 2023).

2.4. Molecular Docking

To further validate the results obtained from the network analysis, molecular docking analysis was performed to evaluate the potential binding activity and interaction between the three highly ranked compounds, namely sequoiaflavone, 3-hydroxysandaracopimaric acid, and 3,7-dimethylquercetin, and the top eight core targets.

2.4.1. Protein and Ligand Preparation

The three-dimensional (3D) crystal structures of the proteins, including cellular tumor antigen p53 (TP53; PDB ID: 8DC4/2.40 Å) [42], interleukin-6 (IL6; PDB ID: 4NI9/2.55 Å) [43], tumor necrosis factor (TNF-α; PDB ID: 2AZ5/2.10 Å) [44], heat shock protein 90-alpha (HSP90AA1; PDB ID: 8AGI/2.10 Å) [45], epidermal growth factor receptor (EGFR; PDB ID: 7T4I/2.61 Å) [46], interleukin-1 beta (IL1B; PDB ID: 1T4Q/2.10 Å) [47], apoptosis regulator Bcl-2 (BCL2; PDB ID: 7LHB/2.07 Å) [48], and caspase-3 (CASP3; PDB ID: 3KJF/2.00 Å) [49], were attained from the Protein Data Bank (http://www.rcsb.org, accessed on 29 July 2023) [50]. The Biovia Discovery Studio visualizer v21.1.0.20298 [51] was employed to eliminate the co-crystallized ligands, water molecules, ions, and repeated chains. Then, the Dock Prep module in the USCF Chimera 1.17.3 software [52] was used to modify the protein structures by adding polar hydrogens and Gasteiger charges. The modified structures were saved as PDBQT protein receptor files.
The 3D structures of the selected bioactive compounds of CLAE were retrieved from the PubChem database and subsequently converted to dockable pdbqt formats using OpenBabel 2.4.1 [53].

2.4.2. Determination of the Grid Coordinates of the Active Sites

For each protein, a grid box was placed on the active site to determine the corresponding grid coordinates using the Auto Dock Vina suite in the USCF Chimera software v.1.17.3. However, for proteins IL6 and IL1B, no co-crystallized ligands were available. As a result, the Computed Atlas for Surface Topography of Proteins server (CASTp; http://sts.bioe.uic.edu/castp/index.html, accessed on 29 July 2023) [54] was used first to predict the active pocket, followed by the determination of the respective coordinates. The centers and sizes of the grid boxes, as well as the amino acid residues of the active sites, are revealed in Table S1.

2.4.3. Docking Simulation and Visualization

The molecular docking of the key components onto target proteins was processed using AutoDock Vina 1.1.2. The default docking parameters were set with an energy range of 4 and an exhaustiveness of 8 in order to generate 10 distinct poses of ligand molecules. The docking scores were expressed in kcal/mol, with a lower score indicating a stronger binding affinity. For each ligand, the docked pose with the best score and least root mean square deviation (RMSD) value was selected. Additionally, for the confirmation process of the active site, the co-crystallized ligands for TNF, HSP90AA1, EGFR, Bcl-2, and CASP3 were also re-docked. The visualization of the molecular interactions between proteins and ligands was achieved using Maestro v13.6.122 software (Schrödinger Release 2023-3: Maestro, Schrödinger, LLC, New York, NY, USA, 2023) and the Biovia Discovery Studio Visualizer v21.1.0.20298 (BIOVIA Dassault Systemes, San Diego, CA, USA).

2.5. In Vivo Experiments

2.5.1. Animals

Twenty-four adult male Wistar rats, weighing 210 ± 20 g, were purchased from the animal unit in the Faculty of Veterinary Medicine, Zagazig University, Zagazig, Egypt. Throughout the adaptation period and the experiment, the rats were housed in the animal house unit in the Faculty of Pharmacy, Zagazig University, Zagazig, Egypt, and maintained under optimal conditions of temperature (22 ± 3 °C), humidity (60 ± 10%), and a 12/12 h light/dark cycle. Water and a normal chow diet were accessible ad libitum.

2.5.2. Ethical Statement

The followed research protocol here was approved by the Institutional Animal Care and Use Committee at Zagazig University, Egypt, and given the approval number ZU-IACUC/3/F/207/2023. The recommendations of the Weather All report and the National Institutes of Health Guide for the care and use of laboratory animals were strictly followed.

2.5.3. Drugs and Vehicles

MTX was obtained from MYLAN (Haupt Pharma GmbH, Münster, Germany), and tween 80 was purchased from Sigma–Aldrich (St Louis, MO, USA). CLAE was prepared in commercially available corn oil with 10% tween 80. All other used chemicals are of analytical grade.

2.5.4. Experimental Protocol

Induction of MTX-Hepatotoxicity

Following two weeks of acclimatization, the experiment was launched. Hepatotoxicity was developed in all groups (except for the control one) by a single i.p injection of 20 mg/kg MTX [11] on the fifth day of the experiment. For the control, the rats received a single i.p injection of saline as an MTX vehicle.

Study Groups

The animals were randomly assigned into four groups (n = 6 rats each) as follows; the control group (animals received a single i.p injection of saline on the fifth day of the experiment plus 10% tween 80 in corn oil, as the extract vehicle, by gavage throughout the experiment), the MTX vehicle group (animals received a single i.p injection of MTX on the fifth day of the experiment plus 10% tween 80 in corn oil by gavage throughout the experiment), and the CLAE 200 and CLAE 400 groups (animals received a single i.p injection of MTX on the fifth day of the experiment plus CLAE in 10% tween 80/corn oil throughout the experiment at 200 and 400 mg/kg/day, gavage, respectively). CLAE or vehicle administration began from the start of the experiment and continued for five days after the MTX injection (for a total experiment period of 10 days).

2.5.5. Blood and Tissue Samples Preparation

At the closure of the experiment, blood samples were withdrawn from retro-orbital plexus by means of heparinized microcapillary tubes and under light anesthesia with sodium pentobarbital (50 mg/kg, i.p) [55]. The collected blood samples were allowed to stand and clot for 30 min at 4 °C and were then centrifuged at 3000× g at 4 °C for another 20 min. Serum was aspirated, aliquoted, and immediately stored at −80 °C for later biochemical analysis. Euthanasia was ensured by cervical dislocation, liver was then excised immediately, rinsed with ice cold saline, and blotted dry on tissue paper. Each collected liver was divided into two portions: one of them was fixed 10% formalin for histopathological examination, while the other was flash-frozen using liquid nitrogen and then stored at −80 °C for later assays.

2.5.6. Assessment of Serum Biomarkers

Liver Function Biomarkers

To assess liver function, alanine transaminase (ALT), aspartate transaminase (AST), and alkaline phosphatase (ALP) were measured in serum using commercially available colorimetric kits from Spinreact Co. (Girona, Spain). The manufacturer’s instructions were followed precisely, and measurements were carried out in duplicate.

2.5.7. Assessment of Hepatic Biomarkers

Oxidative Stress Biomarkers

The hepatic malondialdehyde (MDA) level, as an index of lipid peroxidation, as well as the hepatic reduced glutathione (GSH) level and superoxide dismutase (SOD) activity, as indicators of the hepatic antioxidant capacity, were measured in liver homogenates using Bio-Diagnostic Co. (Giza, Egypt) colorimetric kits. The measurements were performed in duplicates and in accordance with the manufacturer’s instructions.

Proinflammatory Cytokines

Proinflammatory cytokine, TNF-α, was measured in liver homogenates using a rat TNF-α ELISA kit purchased from BT LAB (Shanghai, China). The measurements were conducted in duplicates, following the instructions provided by the manufacturer.

Apoptotic Biomarkers

For the hepatic apoptosis assessment, apoptotic regulators Bcl-2 and Bax, as well as the proapoptotic caspase-3 content, were measured in liver homogenates using rat ELISA kits (BCL2L1, BAX, and CASP3, respectively) BT LAB (Shanghai, China). All assays were conducted in duplicate as per the manufacturers’ instructions.

2.5.8. Immunohistochemical Staining

Serial sections of 4 μm thicknesses were cut from paraffin blocks of livers and then further processed for immunohistochemical staining as follows: (1) Sections were immersed into a 10 mM citrate buffer (pH 6.0) and heated at 98 °C in a water bath for 30 min and then washed with water, (2) 3% hydrogen peroxide in methanol was added to sections for 15 min to block the endogenous peroxidase activity, (3) Sections were incubated with horse serum for 10 min at room temperature to block non-specific binding, (4) Sections were incubated overnight at 4 °C with anti-p53 polyclonal antibody (Invitrogen, Carlsbad, CA, USA) at 1:100 dilution as a proapoptotic biomarker, or with anti-Bcl-2 (Santa Cruz Biotechnology Inc., Paso Robles, CA, USA) at 1:50 dilution as an antiapoptotic biomarker, (5) Sections were incubated with secondary biotinylated antibody and avidin–biotin complex (Vectastain® ABC-peroxidase kit, Vector Laboratories, Burlingame, CA, USA, (6) The color was developed by adding 3,3-diaminobenzidine (DAB) solution, and, (7) Finally, the images were captured using light microscopy (LEICA ICC50W) in the Anatomy and Embryology department by an expert pathologist who screened the entire section and captured the most representative images for each group. The images were analyzed using the Image J software plugin (version 1.53v), immunohistochemistry (IHC) profiler, to calculate the percentage of positive areas (areas stained with brown color) according to the method previously described [56].

2.5.9. Histopathological Examination

Paraffinized livers were sectioned at 5 μm thickness using a microtome (Leica RM 2155, Newcastle upon Tyne, UK). Then, sections were deparaffinized in xylene, gradually hydrated, and then stained with hematoxylin and eosin (H&E). An expert pathologist, blinded to the study groups, screened the entire section and captured the most representative images for each group using light microscopy (LEICA ICC50W) in the Anatomy and Embryology department. Portal tract inflammation was graded as none, mild, moderate, and severe (0–3), where 0 = no portal inflammation, 1 = sprinkling of inflammatory cells in 1/3 of portal tracts, 2 = increased inflammatory cells in 1/3–2/3 of portal tracts, and 3 = dense packing of inflammatory cells in 0.2/3 of portal tracts [57].

2.5.10. Statistical Analysis

All data were represented as mean ± standard error of the mean (SEM). Statistical analysis was conducted using Graph pad prism software version 9.4.1 (681) (Graph Pad Software Inc., La Jolla, CA, USA). The statistical significance of differences between the groups was performed using a one-way analysis of variance (ANOVA) followed by Tukey’s Post hoc test. A significant difference was assumed for values of p less than 0.05. For histology scoring, the statistical significance of differences between groups was performed using the Kruskal–Wallis test followed by Dunn’s multiple comparisons test.

3. Results

The present investigation implemented a systematic experimental approach (Figure 1) to reveal the chemical composition of CLAE, utilizing ultra-performance liquid chromatography–electrospray tandem mass spectrometry (UPLC-ESI-MS/MS). The identified compounds were further analyzed through in silico techniques, including network pharmacology and molecular docking analysis, to investigate their interactions with the DILI molecular targets. To validate the findings in vivo, a rat model of liver injury induced by MTX was employed, followed by subsequent functional and immunohistochemical assessments.

3.1. UPLC-ESI-MS/MS Profiling

According to MS mass, MS2 fragmentation data and patterns, and literature reports, 61 chemical constituents were identified, categorized into flavonoids and glycosides, phenolic, diterpene, carboxylic, sugar acids, fatty acids, lignans, and other compounds. Retention time, pseuomolecular ion peak [M-H], MS2, and the related literature of the identified metabolites of CLAE are listed in Table 1. Figure S1 shows the total ion chromatogram (TIC) of CLAE in negative mode.
Table 1. Phytochemical profiling of the ethanolic extract of Chamaecyparis lawsoniana aerial parts by LC-ESI-MS/MS in negative mode.
Table 1. Phytochemical profiling of the ethanolic extract of Chamaecyparis lawsoniana aerial parts by LC-ESI-MS/MS in negative mode.
No.Rt.[M-H]MS2 Fragments (m/z)Tentative IdentificationClassRef.
1.1.068133.014115, 71Malic acidCarboxylic acid[58]
2.1.119173.045155, 111, 137, 73, 93Shikimic acidCarboxylic acid[59]
3.1.158135.030117, 99, 73, 75L-Threonic acidSugar acid[59]
4.1.163329.091167Vanillic acid glucosidePhenolic acid glycoside[60]
5.1.183191.056173, 85Quinic acidCarboxylic acid[29]
6.1.211335.054299, 191, 137Caffeoylshikimic acidPhenolic acid derivatives[61]
7.1.237377.086341Disaccharid adductDisaccharid[62]
8.1.275315.071153Protocatechuic acid hexosidePhenolic acid glycoside[29]
9.1.301355.116193, 149, 175, 134Ferulic acid-O-glucosidePhenolic acid glycoside[63]
10.1.379341.10959, 71, 89, 101, 113, 143SucroseDisaccharid[62]
11.1.405337.092191, 163, 119Coumaroylquinic acidPhenolic acid derivatives[64]
12.1.458357.119195Dihydro-ferulic acid hexosidePhenolic acid glycoside[65]
13.4.162507.164345Syringetin-3-O-glucosideFlavonol glycoside[66]
14.5.339489.143313, 2835,7-Dihydroxy-8,2’-dimethoxyflavone 7-glucuronideFlavone glucuronide[67]
15.5.537385.186223, 153RoseosideNorisoprenoid glucoside[64]
16.5.564385.186223, 179Sinapoyl D-glucosidePhenolic acid glycoside[68]
17.5.645431.192385, 223, 153Roseoside (formate adduct)Norisoprenoid glucoside[64]
18.5.648593.153447, 431, 285kaempferol-3-O-glucoside-7-O-rhamnosideFlavonol glycoside[69]
19.5.751623.158487, 477, 461, 443, 315, 297VerbascosidePhenylethanoid glycosides[70]
20.5.775525.197329, 507Tricin-4′-O-(erythro-β-guaiacylglyceryl) ether (Salcolin A)Flavone derv.[71]
21.5.777623.160477, 315Isorhamnetin-3-O-rutinosideFlavonol glycoside[72]
22.5.777623.160461, 477Isorhamnetin 3-O-glucoside-7-O-rhamnosideFlavonol glycoside[73]
23.6.110373.149327Pinopalustrin (Nortrachelogenin)Dibenzylbutyrolactone lignan[74]
24.6.433609.146463, 447, 301Quercetin 3-rhamnoglucosideFlavonol glycoside[75]
25.6.615463.088301, 300, 179, 271, 255, 151 Quercetin-3-O-glucosideFlavonol glycoside[64]
26.6.633609.111447, 285kaempferol dihexosideFlavonol glycoside[76]
27.6.860593.152431, 385, 311, 269Apigenin diglucosideFlavone glycoside[77]
28.6.882363.144315, 179, 167(7R,8R)-3-Methoxy-3’,4,7,9,9’-pentahydroxy-8,4’-oxyneolignanLignan
[78]
29.7.264447.092301, 179, 151, 271Quercitrin (Quercetin -3-O-rhamnoside)Flavonol glycoside[64]
30.7.316477.103315, 314, 285Isorhamnetin 3-O-GlucosideFlavonol glycoside[79]
31.7.416327.217327, 229, 211, 171, 1139,12,13-trihydroxyoctadeca-10,15-dienoic acid (Malyngic acid)Fatty Acid[80]
32.7.518287.056259, 151Dihydrokaempferol (Aromadendrin)Flavanonol [72]
33.7.538699.135 Agathisflavone -O-hexosideBiflavonoid glycoside[81]
34. 7.586577.156269, 225, 201, 149Apigenin 7-O-neohesperidoside (rhoifolin) Flavone glycoside[82]
35. 7.861329.138314, 2993,7-dimethylquercetinFlavonol[83]
36. 7.862341.141311, 283, 2574’,5,6,7-Tetramethoxyflavone (Scutellarein tetramethyl ether)Flavone [84]
37. 7.887435.149273, 167Phlorizin (phloretin glucoside)Dihydrochalcone glycoside[29]
38. 7.976461.107461, 299, 284Dihydro-methoxyisoflavone O-hexoside
(Tectoridin)
Flavone glycoside[85]
39. 8.052461.108315, 314Isorhamnetin-O-rhamnosideFlavonol glycoside[86]
40. 8.220519.187459, 357, 315, 314, 299, 285Hexosyl-acyl-isorhamnetinFlavonol glycoside[87]
41. 8.283417.082285, 284, 255 Kaempferol-3-O-arabinosideFlavonol glycoside[88]
42. 8.692557.244539, 509, 361Secoisolariciresinol guaiacylglyceryl etherButanediol lignan[89]
43. 8.865555.224525, 507, 329, 195, 165Lariciresinol-4’-guaiacylglyceryl etherTetrahydrofuranolignan [89]
44. 9.366537.273417, 375, 399AgathisflavoneBiflavonoid[81]
45. 9.639543.276335Pharboside C Diterpene acid glycoside[90]
46. 9.948271.062151NaringeninFlavanone [72]
47. 10.454137.02493ProtocatechualdehydePhenolic aldehyde[91]
48. 10.955521.087329, 359Lariciresinol glucosideTetrahydrofuranolignan glycoside[92]
49. 11.580551.096457, 431, 413, 389, 3457-O-methylamentoflavone (Sequoiaflavone)Biflavonoid[93]
50. 11.629551.097457, 431, 413, 389, 390, 3454′-O-methylamentoflavone (Bilobetin)Biflavonoid[94]
51. 14.081333.2583158alpha-8-Hydroxy-12-oxo-13-abieten-18-oic acidDiterpene acid[95]
52. 14.433302.911259, 219Copalic acidDiterpene acid[74]
53. 16.038565.115533, 389, 374Isoginkgetin (4′,4″ dimethylamentoflavone)Biflavonoid[94]
54. 16.416564.773471, 445, 403Robustaflavone 7,4′-dimethyl etherBiflavonoid[94]
55. 16.715357.099342, 313Matairesinol Dibenzylbutyrolactone lignans[96]
56. 17.152359.222344, 313CyclolariciresinolAryltetralin diol lignan[89]
57. 18.682329.175285, 313, 311CarnosolPhenolic diterpene[74]
58. 21.153317.212299, 2053-Hydroxysandaracopimaric acidDiterpene acid[97]
59. 21.191317.21229912alpha-hydroxy-8,15-isopimaradien-18-oic acidDiterpene acid[98]
60. 21.202301.218253, 205ent-kaurenoic acidDiterpene acid[99]
61. 21.269715.328641, 375, 301Ganoleucoin Jlanostane triterpenoid[100]

3.1.1. Identification of Phenolic, Carboxylic, Sugar, Diterpene Acid and Fatty Acids

According to the UPLC-ESI-MS/MS analysis conducted in negative mode, CLAE displayed a diverse range of acids that were classified into various categories, including phenolic acid conjugates, carboxylic acids, sugar acids, diterpene acids, and fatty acids.
Phenolic acid conjugates were predominantly observed as phenolic acid hexosides, such as compounds 4, 8, 9, and 12, which released hexosyl (162 Da) to produce corresponding phenolic acids, including vanillic, protocatechuic, ferulic, and dihydroferulic acids. Other phenolic acid conjugates, such as caffeoylshikimic acid 6 and coumaroylquinic acid 11, were also identified.
In addition to these, carboxylic acids, such as malic and shikimic acids, sugar acid as L-threonic acid, diterpene acids, including 8alpha-8-Hydroxy-12-oxo-13-abieten-18-oic acid, copalic acid, 3-hydroxysandaracopimaric acid, 12alpha-hydroxy-8,15-isopimaradien-18-oic acid, and ent-kaurenoic acid, and diterpene acid glycoside pharboside C, as well as fatty acids, such as 9,12,13-trihydroxyoctadeca-10,15-dienoic acid, were also characterized. Generally, the primary fragmentation pathway for these acids involved the loss of CO (28 Da), CO2 (44 Da), and H2O from the deprotonated peak [M-H].

3.1.2. Identification of Flavonoid and Glycosides

Flavonoid aglycones and glycosides are considered the major compounds detected in CLAE; these compounds belong to different subclasses such as flavonol, flavone, flavanonol, biflavonoid, dihydrochalcone, and flavanone.
Biflavonoids represent the majority of the subclasses in the extract, where six biflavonoids were tentatively identified, including three 3′, 8″ biapigenin-type biflavones (IC3′–IIC8″) as 7-O-methylamentoflavone 49, 4′-O-methylamentoflavone 50, and Isoginkgetin 53, one 3′, 6″ biapigenin-type biflavone (IC3′–IIC6″) as robustaflavone 7,4′-dimethyl ether 54, and two 6, 8″ biapigenin-type biflavones (IC6–IIC8″) as agathisflavone-O-hexoside 33 and agathisflavone 44. Compounds 49, 50, and 53 are amentoflavone-type biflavones, and they underwent a similar fragmentation pathway. The [M-H] ion of compound 49 at m/z 551 produced several characteristic daughter ions, such as the [M-H-C6H6O] ion at m/z 457, which is coming from the neutral loss of phenol on flavonoid part II, [M-H-C7H4O2] ion at m/z 431, which was attributed to the 0,2IIA-ion, [M-H-C7H6O3] ion at m/z 413 which corresponded to the 0,2IIA-H2O ion, [M-H-C9H6O3] ion at m/z 389 ion which corresponded to the base peak, which illustrated that the product ion passed a retro cyclization fragmentation, including the 0 and 4 bonds on flavonoid part II, and [M-H-C10H6O5] ion at m/z 345 which corresponded to the 0,4IIA-CO2 ion. Compounds 50 and 53 also yielded diagnostic fragments for this type of biflavone. Basically, the most important diagnostic fragmentation -ve ESI mode of amentoflavone-type biflavones is that involving the cleavage of the C–ring of flavonoid part II at position 0/4. The MS2 fragmentation pathways of IC3′–IIC6″ linked biflavones, such as robustaflavone 7,4′-dimethyl ether 54, displayed similarities and differences in comparison with amentoflavone-type biflavones. Compound 54 produced fragments at m/z 471, 445, and 403 in a similar way as amentoflavone-type biflavones. But the chances are greater in the case of robustaflavone type for the cleavage of C–ring to occur on flavonoid part I, such as at position 1/4 and 1/3, and after retro cyclization, which produced the 1,4IB-ion at m/z 427, 1,3IB- ion at m/z 401.
Other flavonoid aglycones were tentatively identified as flavanonol (dihydrokaempferol 32), flavonol (3,7-dimethylquercetin 35), flavone (scutellarein tetramethyl ether 36), and flavanone (naringenin 46). The identification of these aglycones was established by the corresponding [M-H] as well as the MS2 fragmentation pattern for each compound.
Flavonoids are mostly present in the form of glycosides, which are easily cleaved in MS2 fragmentation, producing the corresponding aglycone. Three peaks related to Kaempferol were detected at [M-H] at m/z 593, 609, and 417, they gave a fragment at m/z 285, corresponding to the aglycone Kaempferol, which attributed to the elimination of glucose and rhamnose (compound 18), two molecules of glucose (compound 26), and arabinose (compound 41). Peaks 21, 22, 30, 39, and 40 exhibited the same base peak at m/z 315 corresponding to the isorhamnetin aglycone through the neutral loss of rutinosyl (308 Da), indicating the presence of isorhamnetin-3-O-rutinoside 23, glucosyl, and rhamnosyl (162, 146 Da), indicating the presence of isorhamnetin 3-O-glucoside-7-O-rhamnoside 24, glucosyl (162 Da), confirming isorhamnetin 3-O-glucoside, the loss of rhamnosyl (146 Da) in the case of isorhamnetin-O-rhamnoside 41, and the loss of acylhexosyl (204 Da) in hexosyl-acyl-isorhamnetin 40. In a similar way, quercetin glycosides (compounds 24, 25, and 29), apigenin glycosides (compounds 27 and 34), syringetin-3-O-glucoside 13, 5,7-Dihydroxy-8,2’-dimethoxyflavone 7-glucuronide 14, phloretin glucoside 37, and diosmetin 7-O-glucoside were tentatively identified.
Other flavonoid conjugates were detected as compound 20 of the molecular ion peak [M-H] at m/z 525, and MS2 fragmentation produced a characteristic peak for the aglycone tricin and identified as salcolin A (tricin-4′-O-(erythro-β-guaiacylglyceryl) ether).

3.1.3. Identification of Lignans and Their Glycosides

Different classes of lignans and glycosides were identified in the extract as dibenzylbutyrolactones (23, 55), butanediol (42), tetrahydrofurano (43, 48), aryltetralin diol lignans (56), and neolignan (28); they exhibited different fragmentation patterns which were compared with the reported data.

3.1.4. Identification of Miscellaneous Compounds

Disaccharide (sucrose), norisoprenoid glucoside (roseoside), phenylethanoid glycosides (verbascoside), phenolic aldehyde (protocatechualdehyde), phenolic diterpene (carnosol), and lanostane triterpenoid (ganoleucoin J) were also identified.

3.2. Network Pharmacology-Based Analysis

3.2.1. Identification of Bioactive Constituents of CLAE

In order to identify the potential bioactive components, a total of 54 secondary metabolites of CLAE were subjected to screening for their pharmacokinetic and drug-likeness properties, as detailed in Table S2. Among these compounds, 31 exhibited high bioavailability scores (OB ≥ 0.55) and satisfied Lipinski’s rule of five, a widely accepted criterion for assessing drug likeness. Consequently, these 31 compounds were selected for further investigation, outlined in Table S3.

3.2.2. Determination of the Overlapping Molecular Targets of CLAE Bioactive Compounds and DILI

In order to ascertain the molecular targets related to the bioactive components of CLAE, the databases PharmMapper and SwissTargetPrediction were employed. Following the elimination of duplicates, a total of 958 targets were yielded (Table S4). Subsequently, the DILI-associated molecular targets were identified from three disease-related databases: DisGeNeT, GeneCards, and OMIM. After removing duplicates, 801 targets were obtained from an initial 1114 (Table S5). Of these targets, 195 (Table S6) were found to overlap with the 958 targets associated with CLAE bioactive compounds (Figure 2).

3.2.3. PPI Network of the Common Targets

To comprehend the hepatoprotective mechanism of CLAE against DILI, the interactions between the common target proteins were analyzed. The 195 overlapping targets were submitted into the STRING database to generate an interconnected network that shows the correlations among these targets. After removing the disconnected nodes, the entire network displayed a total of 185 targets (Figure 3A).
A Degree value-based ranking was performed on the core targets in the PPI network, which was determined by the number of connecting edges. The complete ranking of all the genes can be found in Table S7, whereas the top 20 targets are presented in Figure 3B and Table 2. TP53, IL6, TNF-α, HSP90AA1, EGFR, IL1B, BCL2, and CASP3 are among the top eight targets.

3.2.4. Top CLAE Compounds Associated with DILI Targets

In Cytoscape, a compound–target network (Figure S2) was constructed to find out the most significant CLAE compounds related to the 195 DILI targets. These compounds were subsequently arranged by their Degree value (Table 3). The top three compounds were sequoiaflavone, 3-hydroxysandaracopimaric acid, and 3,7-dimethylquercetin.

3.2.5. Enrichment Analysis of the Common Targets

The present study conducted an enrichment analysis to confirm the relevant characteristics of the 195 disease–compound common targets on biological and functional levels. The GO analysis yielded a total of 722 GO items, comprising biological processes (BPs), cellular components (CCs), and molecular functions (MFs) with p < 0.05. Bar graphs were generated for the top 10 GO items, as illustrated in Figure 4a. The most prominent BP involved the response to xenobiotic stimulus, negative regulation of the apoptotic process, and the xenobiotic metabolic process. The top CC categories were cytosol, extracellular exosome, and macromolecular complex, while the top MF categories comprised enzyme binding, identical protein binding, and protein homodimerization activity. Supplementary Tables S8–S10 provide detailed information on the GO analyses.
Additionally, KEGGs pathway enrichment analysis (p < 0.05) was performed on the 195 common targets of CLAE and DILI to identify the potential hepatoprotective pathways. The top 30 pathways, including pathways in cancer, the AGE-RAGE signaling pathway in diabetic complications, fluid shear stress, and atherosclerosis, are shown in Figure 4b based on the number of enriched genes, fold changes, and p value. The results of the KEGGs pathway are represented in detail in Table S11.

3.3. Molecular Docking Simulation

In order to assess the binding affinity of CLAE compounds to the key target proteins associated with DILI pathogenesis, a molecular docking analysis was conducted using AutoDock Vina software v.1.1.2. The analysis focused on the top three CLAE compounds: sequoiaflavone, 3-hydroxysandaracopimaric acid, and 3,7-dimethylquercetin (Table 3), and the top eight DILI targets: TP53, IL6, TNF-α, HSP90AA1, EGFR, IL1B, BCL2, and CASP3 (Table 2). The ligand molecules were docked within the designated grid box that was generated around the active site of each protein.
Table 4 displays the results of the docking analysis, which includes the docking scores, interacting amino acid residues at the active sites, and associated bond types. In accordance with Autodock Vina, a lower docking score indicates a stronger ligand–receptor association, with a score below −7 kcal/mol indicating a high binding affinity [101]. The interaction complexes with docking scores below −7 kcal/mol are illustrated in Figure 5, Figure 6 and Figure 7 organized in ascending order of score values for each ligand.
The findings revealed that sequoiaflavone exhibited the highest binding affinity for all the proteins analyzed in this study. Significantly, the most favorable results were observed with HSP90AA1, EGFR, BCL2, TNF-α, and TP53 exhibiting docking scores of −10.27, −10.14, −10.13, −9.429, and −9.060 kcal/mol, respectively.
As depicted in Figure 5, the interaction complex between sequoiaflavone and HSP90AA1 manifested a total of twelve intermolecular interactions. Among these, three were attributed to hydrogen bonds, wherein sequoiaflavone interacted with Ser50 and Gly97 through conventional hydrogen bonding, and with Asn51 via Pi-donor–hydrogen bond. On the other hand, the docked complex of sequoiaflavone and EGFR displayed remarkably fifteen intermolecular bonds that involved four conventional hydrogen bonds with Leu718, Thr790, Met793, and Thr854, along with one carbon–hydrogen bond with Lys745. Furthermore, it was observed that sequoiaflavone and BCL2 exhibited nine intermolecular interactions, including a single conventional hydrogen bonding with Glu136. Additionally, the interaction between sequoiaflavone and TNF-α is mediated by ten intermolecular linkages, including two conventional hydrogen bonds formed with GlnA61 and TyrB119, as well as two additional carbon–hydrogen bonds with LysB98 and IleB118 residues located beyond the active site. Sequoiaflavone was found to form fifteen intermolecular bonds with TP53, including two conventional hydrogen bonds with Leu145 and Val147, as well as a carbon–hydrogen bond with Ser229.
As illustrated in Figure 6, the interaction analysis revealed the presence of seven intermolecular interactions between 3-hydroxysandaracopimaric acid and TNF-α. Notably, three conventional hydrogen bonds were identified, with one being associated with the SerB60 residue and the remaining two with the TyrB151 residue. Moreover, the interaction between 3-hydroxysandaracopimaric acid and EGFR resulted in the formation of nine intermolecular bonds, which included two conventional hydrogen bonds that were established with Thr790 and Thr854. In addition, eleven intermolecular interactions were detected between 3-hydroxysandaracopimaric acid and BCL2, where a conventional hydrogen bond was formed with Glu136 residue.
Furthermore, it was observed that 3,7-dimethylquercetin demonstrated a significant potential in its ability to bind with TP53, TNF-α, HSP90AA1, EGFR, and BCL2. The docking scores for these interactions were −7.112, −7.258, −7.945, −7.868, and −7.394 kcal/mol, respectively. According to the findings presented in Figure 7, the compound 3,7-dimethylquercetin exhibited an interaction with TP53 through eighteen intermolecular associations, including two conventional hydrogen bonds with Cys220 and Thr230. Additionally, the interaction between 3,7-dimethylquercetin and TNF-α was characterized by nine intermolecular bonds, four of which were conventional hydrogen bonds with GlyA121, TyrA151, and TyrB151. As well, the intermolecular connection between 3,7-dimethylquercetin and HSP90AA1 was established through the formation of eight bonds, comprising a conventional hydrogen bond and a carbon–hydrogen bond, with the Asn51 residue. In relation to the interplay between 3,7-dimethylquercetin and EGFR, a total of twelve intermolecular connections were identified. These included four conventional hydrogen bonds with Thr790, Met793, and Thr854, as well as a carbon–hydrogen bond with Leu718. Moreover, it was observed that 3,7-dimethylquercetin exhibited intermolecular interactions with BCL2 via ten connections. Notably, two conventional hydrogen bonds were identified at the active site, specifically with Ala100 and Phe104. Additionally, a further hydrogen bond was detected with the Arg146 residue, which is situated beyond the active site.

3.4. In Vivo Validation

3.4.1. CLAE Improved Liver Function

As depicted in Figure 8A–C, a significant impairment of liver function was exhibited in the vehicle-treaded MTX group, indicating liver injury, as expressed by elevated levels of circulating liver enzymes (ALT, AST, and ALP) compared to the control group. Hepatoprotective effects of CLAE at both doses were evident by the significant reductions in the circulating levels of ALT, AST, and ALP when compared to the vehicle-treated MTX group (Figure 8A,B,C, respectively). The higher dose of CLAE exhibited a more efficient improvement in liver function and hence hepatoprotection compared to the smaller one, indicating the dose-dependent effect of CLAE.

3.4.2. CLAE Alleviated Hepatic Oxidative Stress

As presented in Figure 9A–C, MTX intoxication elicited pronounced hepatic oxidative stress, as manifested by a significant increase in the lipid peroxidation product MDA and significant attenuation of the hepatic antioxidant capacity, as depicted by a decline in the SOD activity and GSH level when compared to the control group. Comparable to the vehicle-treated MTX group, both doses of CLAE significantly alleviated MTX-induced oxidative stress, where there was a significant reduction in hepatic MDA, while enhanced SOD activity and GSH level in the liver was observed upon CLAE administration, indicating the antioxidant potential of CLAE (Figure 9A–C).

3.4.3. CLAE Reduced Hepatic Inflammation

As shown in Figure 9D, the vehicle-treated MTX group exhibited significant elevation in the proinflammatory cytokine, TNF-α, indicating hepatic inflammation compared to the control group. On the other hand, CLAE significantly reduced the hepatic TNF-α content in a dose-dependent manner in comparison with the vehicle-treated MTX group.

3.4.4. CLAE Attenuated Apoptosis (Immunostaining and Biochemical Findings)

MTX intoxication induced hepatic apoptosis, as manifested by increased positive areas of p53 staining, a proapoptotic biomarker, in hepatocyte nuclei, whereas reduced positive areas of Bcl-2-staining, antiapoptotic protein, and weak cytoplasmic immune reactivity were noticed in immunostained liver sections when compared to the control group (Figure 10A). Further, biochemical measurements revealed declined antiapoptotic Bcl-2, while the proapoptotic biomarkers Bax and caspase-3 were increased in the vehicle-treated MTX group in comparison with the control one (Figure 10B,C,D, respectively).
CLAE, in a dose-dependent manner, attenuated MTX-induced hepatic apoptosis with the remarkable downregulation of p53 immunoexpression along with the upregulation of cytosolic Bcl-2 in immunostained liver sections (Figure 10A–C). CLAE dose-dependently increased hepatic Bcl-2, while both hepatic Bax and caspase-3 (Figure 10D–F) were reduced compared to the vehicle-treated MTX group.

3.4.5. CLAE Improved Liver Histology (Histopathological Findings)

As displayed in Figure 11B, features of hepatopathy were observed upon the examination of H&E-stained liver sections from rats of the vehicle-treated MTX group, where most of the hepatocytes exhibited dark-stained nuclei, while few were normal. Wide separations between hepatocyte plates were depicted due to sinusoids dilatation. Inflammatory cell infiltrations close to the dilated and congested portal vein, as well as proliferated bile ductulus, were detected in the region of the portal tract. On the contrary, the control group exhibited normal hepatic architecture, where each hepatic lobule consisted of anastomosing radially distributing hepatocytes. The hepatocytes were polygonal in shape with well-defined boundaries. Their cytoplasm was acidophilic, and the majority of cells had a single rounded, vesicular, and centrally placed nucleus, whereas some cells appeared to be binucleated. The hepatic sinusoids were seen as narrow spaces in between adjacent plates of hepatocytes and lined by flat endothelial cells and Kupffer cells. The hepatic portal tracts were seen at the periphery of the lobule. Portal tracts had branches of the portal vein, hepatic artery, and bile duct (Figure 11A).
Upon examination of the liver section from rats who received the lower dose of CLAE, partial restoration of liver histological features was depicted. Some dispersed inflammatory cells through the parenchyma of the liver could be noticed. Some hepatocytes still showed dark-stained nuclei and few cellular infiltrations. Double bile ducts and dilated sinusoid could be observed (Figure 11C). Interestingly, increasing the dose of CLAE restored most of the histological features, which appear near normal patterns (Figure 11D). The vehicle-treated MTX group exhibited significantly increased portal tract inflammation scores compared to the control, while CLAE dose-dependently reduced the injury scores (Figure 11E).

4. Discussion

Despite the recent therapeutic advancements and significant progress in medicine, hepatic diseases continue to pose a universal health challenge. Therefore, the exploration of novel and potent drugs against liver injury is a worthwhile pursuit. While synthetic drugs have been used to treat liver diseases, they have been shown to be carcinogenic and cause severe side effects. In contrast, herbal products are cost-effective, better compatible with the human body, have lower side effects, and are easier to store. Moreover, plants are a rich source of bioactive constituents such as phenolic acids and flavonoids, making the herbal approach a viable alternative to conventional therapy [102].
Therefore, the present study focused on investigating the protective potential of Chamaecyparis lawsoniana aerial parts ethanolic extract (CLAE) against DILI, with a specific emphasis on liver injury caused by MTX. The research methodology was based on phytochemical profiling, which was subsequently complemented by network pharmacology and docking studies, followed by preclinical validation. By adopting the comprehensive approach, the study has successfully identified the most biologically significant components of CLAE, along with their potential molecular targets and mechanisms of action in mitigating MTX-induced liver injury.
The phytochemical profile of CLAE was investigated using UPLC–ESI–MS/MS analysis in negative mode. According to the retention time, pseuomolecular ion peak [M-H], MS2 fragmentation patterns, as well as the available literature, 65 phytochemicals were tentatively characterized, mainly including flavonoids, particularly bioflavonoids, and glycosides, diterpene and phenolic acids, and lignans.
Previous studies have extensively investigated the hepatoprotective effects of various components from these identified chemical classes. Flavonoids, in particular, have gained recognition for their ability to provide a substantial hepato-protective effect through diverse mechanisms. A wide range of approximately 100 bioflavonoids have been documented for their hepatoprotective activity [103]. Notably, amentoflavone, a biflavonoid, has demonstrated significant hepatoprotective activity through various mechanisms [104,105]. Moreover, significant hepatoprotective properties in diverse models of DILI have been demonstrated by other subtypes of flavonoids, specifically quercetin and its related compounds such as quercetin 7-rhamnoside, 3′-O-methyl quercetin, and quercetin-3-O-glucuronide [106,107].
Additionally, several medicinal plants containing diterpene acids, such as Juniperus phoenicea [108] and Rosmarinus officinalis [109], have been found to protect the liver from damage caused by carbon tetrachloride (CCl4). Additionally, extracts from Cupressus sempervirens leaves, rich in biflavones and phenolic acids, showed significant hepatoprotective properties against both CCl4-induced and paracetamol-induced damage [110,111]. Juniperus sabina aerial parts, containing diterpene acids, lignans, and flavonoids, also demonstrated promising hepatoprotective activity against CCl4-induced damage [112].
In recent years, the focus of biomedical research has shifted towards identifying pharmacological targets from active ingredients found in medicinal plants, with the ultimate goal of developing novel therapies. The emergence of network pharmacology as a systematic paradigm presents a unique opportunity to explore traditional medicines and has become a pioneering research field in drug discovery and development. This advancement has paved the way for a better understanding of the complex bioactive components found in various medicinal plants [113]. The application of the network pharmacology approach in this investigation led to the discovery of 195 significant potential targets of CLAE in DILI. Among these targets, the top eight, namely TP53, IL6, TNF-α, HSP90AA1, EGFR, IL1B, BCL2, and CASP3, were deemed particularly noteworthy.
Molecular docking is a computerized approach that predicts the most effective way for a ligand to attach to a receptor, forming a stable complex. It is a valuable tool for identifying potential drug targets by analyzing the binding ability of small molecules and the active pocket of the protein. A low energy complex and a compatible ligand can result in strong activity [114].
To shed light on the potential mechanisms underlying the hepatoprotective effects of CLAE against DILI, a molecular docking simulation was carried out on the three most significant bioactive compounds present in CLAE, namely sequoiaflavone, 3-hydroxysandaracopimaric acid, and 3,7-dimethylquercetin, against eight key DILI targets, including IL6, TNF-α, HSP90AA1, EGFR, IL1B, BCL2, and CASP3.
Apoptosis is a crucial intracellular process that functions as a self-destruct program, playing a pivotal role in maintaining cellular homeostasis and eliminating irreparable damaged cells [115]. Its regulation involves a complex network of genes, including TP53, which induces cell apoptosis by controlling the translocation of antiapoptotic Bcl-2 and pro-apoptotic Bax proteins. The activated p53 alters the permeability of the cell membrane, facilitating the release of cytochrome c from the mitochondria into the cytoplasm. Subsequently, this process triggers the activation of cleaved caspase3, initiating cell degradation [116]. This process holds a significant importance in the context of liver injury [117] since evidence suggested that the p53 protein accumulates in individuals with various inflammatory liver diseases. Inhibiting the p53 signaling pathway has been demonstrated to enhance drug-induced hepatocyte injury by regulating the mitochondrial apoptosis pathway. Consequently, this presents a promising therapeutic strategy for effectively treating liver injury [118]. During molecular docking, TP53 exhibited a robust binding affinity towards the CLAE components sequoiaflavone and 3,7-dimethylquercetin. Within the Bcl-2 active pocket, sequoiaflavone, 3-hydroxysandaracopimaric acid, and 3,7-dimethylquercetin displayed promising binding energies, suggesting their potential for actively contributing to the hepatoprotective effect by modulating apoptosis.
On the other hand, inflammation constitutes a significant factor in the development of drug-induced toxicities, including those caused by MTX. This is due to the generation of free radicals and associated oxidative stress, which are known to initiate inflammatory responses. As a result, proinflammatory cytokines such as TNF-α, IL-1β, and IL-6 are secreted, leading to tissue injury [119]. However, this study showed that the investigated CLAE constituents could have the potential to downregulate these mediators by interacting with their active sites, particularly TNF-α, alleviating the inflammation associated with DILI.
Furthermore, a correlation between heat shock protein 90 (HSP90) and hepatic injury was previously reported, and it was observed that HSP90 inhibitors exhibited a protective effect on various organs [120,121]. Additionally, the EGFR is implicated in the pathogenesis of both cirrhosis and hepatocellular carcinoma (HCC), with its hepatic expression increasing during cirrhosis [122]. Studies have suggested that inhibiting EGFR may offer a promising therapeutic strategy for reducing fibrogenesis and preventing HCC in patients with high-risk cirrhosis [123,124]. The results from the docking analysis revealed that sequoiaflavone and 3,7-dimethylquercetin could possess inhibitory properties against HSP90. Furthermore, these compounds also exhibited the ability to inhibit EGFR, along with 3-hydroxysandaracopimaric acid. This dual inhibition potential may play a crucial role in safeguarding the liver against hepatotoxicity.
Based on the simulation results, the compounds displayed favorable affinities for binding to the targeted proteins. It is noteworthy to highlight that sequoiaflavone exhibited an exceptionally strong binding affinity towards all the targeted proteins. These findings imply that these components might possess synergistic hepatoprotective effects through multiple mechanisms. Consequently, CLAE shows promise as a preventive approach against DILI caused by these proteins.
To achieve a comprehensive appraisal, it is essential to perform an experimental validation as this furnishes supplementary evidence and verification of the conclusions derived from computational analysis. Consequently, this study employed a preclinical model of MTX-induced liver injury in rats to investigate the potential hepatoprotective effects and underlying mechanism of action of CLAE.
In this study, MTX intoxication elicited hepatotoxicity, as manifested by significant augmentation in circulating liver function enzymes (AST, ALT, and ALP) and disrupted histological architecture, which is consistent with previous studies [125,126]. However, the administration of CLAE demonstrated hepatoprotective potential, as expressed by significant dose-dependent decrease in AST, ALT, and ALP circulating levels, and the restoration of normal hepatic histological features, where the smaller dose of CLAE elicited partial restoration, while an increasing dosage reinstated the majority of these characteristics, closely resembling normal patterns.
Ample evidence suggests that MTX-induced multiorgan injury involves oxidative stress, which is a consequence of ROS activation [10,127,128] and results in a decline in antioxidant defenses [129], which is consistent with our findings where challenging rats with MTX significantly augmented the MDA level while attenuating the GSH level and SOD activity in liver. CLAE depicted significant antioxidant potential by reducing hepatic MDA levels while enhancing the hepatic antioxidant capacity expressed as SOD activity and GSH levels, thereby alleviating MTX-induced oxidative stress. High-dose MTX-associated oxidative stress triggered the release of proinflammatory cytokines, which further contributes to tissue injury [130,131]; this supports our results where elevated hepatic TNF-α following MTX intoxication was found. CLAE significantly and dose-dependently reduced hepatic inflammation by reducing TNF-α levels. ROS overproduction during MTX therapy provokes DNA damage and triggers apoptotic pathways, as reported in several studies [126,132]. In this study, MTX upregulated p53, proapoptotic Bax, and caspase-3, while it downregulated antiapoptotic Bcl-2, thus inducing apoptotic changes, adding to MTX-induced hepatotoxicity. CLAE attenuated MTX-induced hepatic apoptosis by downregulating p53 expression while upregulating cytosolic Bcl-2, as depicted in immunostained liver sections. CLAE dose-dependently enhanced hepatic Bcl-2 while decreasing Bax and caspase-3.
Collectively, these findings highlight the potential hepatoprotective benefits of CLAE in reversing the detrimental effects of MTX-induced hepatopathy, and this effect may be attributed to one or more of its bioactive components. Further research and investigation are warranted to fully understand the mechanisms underlying this restoration and to explore the clinical implications of these findings.

5. Conclusions

In conclusion, our research findings, supported by comprehensive in silico and in vivo studies, present compelling evidence for the hepatoprotective properties of CLAE in DILI, with a specific focus on MTX-induced liver injury. Moreover, our investigations have elucidated the underlying mechanism of action of CLAE. Nevertheless, additional preclinical and clinical studies are imperative to assess the efficacy and safety of CLAE in DILI cases, and to evaluate any potential long-term complications that may arise.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/antiox12122118/s1, Figure S1: UPLC-ESI-MS/MS total ion chromatograms of CLAE in negative ion mode; Figure S2: CLAE compounds-DILI targets network; Table S1: Target proteins, the corresponding grid coordinates, and amino acid residues of the active sites; Table S2: Pharmacokinetics and the drug-likeness properties of CLAE constituents; Table S3: Bioactive compounds of CLAE; Table S4: Molecular targets of CLAE bioactive compounds; Table S5: Molecular targets associated with DILI; Table S6: Molecular targets of CLAE associated with DILI; Table S7: Core genes in PPI network ranked by the Degree method; Table S8: Detailed information of GO analysis for biological processes; Table S9: Detailed information of GO analysis for cellular components; Table S10: Detailed information of GO analysis for molecular functions; Table S11: Detailed information of KEGGs pathway analysis.

Author Contributions

Conceptualization, E.F., R.O., S.S.E.-S., S.P., S.G., A.M.E.-S., M.M.E.-D. and N.T.; Methodology, E.F., S.S.E.-S. and N.T.; Software, E.F.; Investigation, E.F., R.O., S.S.E.-S., S.P., S.G. and N.T.; Validation, E.F., S.S.E.-S. and N.T.; Formal analysis, E.F., R.O., S.S.E.-S., S.P. and N.T.; Resources, R.O., S.P., A.M.E.-S. and M.M.E.-D.; Data curation, E.F., R.O., S.S.E.-S. and N.T.; writing—original draft preparation, E.F., S.S.E.-S. and N.T.; Writing—review and editing, R.O., S.P., S.G., A.M.E.-S. and M.M.E.-D.; Supervision, A.M.E.-S. and M.M.E.-D.; Project administration, E.F., A.M.E.-S., M.M.E.-D. and N.T.; Funding acquisition, R.O., S.P. and S.G. All authors have read and agreed to the published version of the manuscript.

Funding

The present research has been financially supported by the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia, under the project number IFKSUOR3–135.

Institutional Review Board Statement

The Institutional Animal Care and Use Committee of Zagazig University has granted approval for the animal study protocol (protocol code number ZU-IACUC/3/F/207/2023, dated 22 June 2023).

Informed Consent Statement

Not applicable.

Data Availability Statement

All data and materials used are available in the manuscript and Supplementary Materials.

Conflicts of Interest

The authors declare that they have no conflicts of interest to disclose.

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Figure 1. A flowchart depicting the experimental design of this study, encompassing phytochemical, network pharmacological, molecular docking, and in vivo experimental studies to explore the impact of CLAE in DILI.
Figure 1. A flowchart depicting the experimental design of this study, encompassing phytochemical, network pharmacological, molecular docking, and in vivo experimental studies to explore the impact of CLAE in DILI.
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Figure 2. Overlapping molecular targets between DILI and CLAE bioactive compound. CLAE, Chamaecyparis lawsoniana aerial parts extract; DILI, drug-induced liver injury.
Figure 2. Overlapping molecular targets between DILI and CLAE bioactive compound. CLAE, Chamaecyparis lawsoniana aerial parts extract; DILI, drug-induced liver injury.
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Figure 3. Protein–protein interaction (PPI) network of CLAE molecular targets associated with DILI. (A) PPI network. (B) Top 20 targets in the PPI network ranked by their Degree values.
Figure 3. Protein–protein interaction (PPI) network of CLAE molecular targets associated with DILI. (A) PPI network. (B) Top 20 targets in the PPI network ranked by their Degree values.
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Figure 4. Enrichment analysis compound–disease interacting proteins, (a) GO analysis, (b) KEGGs pathways. The Degree of color intensity is directly proportional to the number of genes, with intense violet representing the highest level.
Figure 4. Enrichment analysis compound–disease interacting proteins, (a) GO analysis, (b) KEGGs pathways. The Degree of color intensity is directly proportional to the number of genes, with intense violet representing the highest level.
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Figure 5. Three-dimensional and two-dimensional representations of the interaction complexes of sequoiaflavone with HSP90AA1, EGFR, BCL2, TNF-α, TP53, IL1B, CASP3, and IL6. The plots have been arranged in ascending order according to their respective docking score values.
Figure 5. Three-dimensional and two-dimensional representations of the interaction complexes of sequoiaflavone with HSP90AA1, EGFR, BCL2, TNF-α, TP53, IL1B, CASP3, and IL6. The plots have been arranged in ascending order according to their respective docking score values.
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Figure 6. Three-dimensional and two-dimensional representations of the interaction complexes of 3-hydroxysandaracopimaric acid with TNF-α, EGFR, and BCL2. The plots have been arranged in ascending order according to their respective docking score values.
Figure 6. Three-dimensional and two-dimensional representations of the interaction complexes of 3-hydroxysandaracopimaric acid with TNF-α, EGFR, and BCL2. The plots have been arranged in ascending order according to their respective docking score values.
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Figure 7. Three-dimensional and two-dimensional representations of the interaction complexes of 3,7-dimethylquercetin with TP53, TNF-α, HSP90AA1, EGFR, and BCL2. The plots have been arranged in ascending order according to their respective docking score values.
Figure 7. Three-dimensional and two-dimensional representations of the interaction complexes of 3,7-dimethylquercetin with TP53, TNF-α, HSP90AA1, EGFR, and BCL2. The plots have been arranged in ascending order according to their respective docking score values.
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Figure 8. Effect of 10 days administration of Chamaecyparis lawsoniana extract (CLAE) at 200 and 400 mg/kg/day, gavage on impaired liver function induced by single i.p injection of methotrexate (MTX) at a dose of 20 mg/kg on the fifth day of the experiment. Liver function is presented as serum levels of alanine aminotransferase (ALT, (A)), aspartate aminotransferase (AST, (B)), and alkaline phosphatase (ALP, (C)). Values are presented as mean ± SEM (n = 6/group). Statistical analysis was conducted using one-way analysis of variance (ANOVA) followed by Tukey’s Post hoc test. **** p < 0.0001, ** p < 0.01, and * p < 0.05.
Figure 8. Effect of 10 days administration of Chamaecyparis lawsoniana extract (CLAE) at 200 and 400 mg/kg/day, gavage on impaired liver function induced by single i.p injection of methotrexate (MTX) at a dose of 20 mg/kg on the fifth day of the experiment. Liver function is presented as serum levels of alanine aminotransferase (ALT, (A)), aspartate aminotransferase (AST, (B)), and alkaline phosphatase (ALP, (C)). Values are presented as mean ± SEM (n = 6/group). Statistical analysis was conducted using one-way analysis of variance (ANOVA) followed by Tukey’s Post hoc test. **** p < 0.0001, ** p < 0.01, and * p < 0.05.
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Figure 9. Effect of 10 days administration of Chamaecyparis lawsoniana extract (CLAE) at 200 and 400 mg/kg/day, gavage on hepatic oxidative stress and inflammation induced by single i.p injection of methotrexate (MTX) at a dose of 20 mg/kg on the fifth day of the experiment. Oxidative status is expressed by hepatic content of malondialdehyde (MDA, (A)), superoxide dismutase (SOD, (B)), and reduced glutathione (GSH, (C)). Inflammatory status is expressed by proinflammatory cytokine tumor necrosis factor-α (TNF-α, (D)). Values are presented as mean ± SEM (n = 6/group). Statistical analysis was conducted using one-way analysis of variance (ANOVA) followed by Tukey’s Post hoc test. **** p < 0.0001, *** p < 0.001, ** p < 0.01, and * p < 0.05.
Figure 9. Effect of 10 days administration of Chamaecyparis lawsoniana extract (CLAE) at 200 and 400 mg/kg/day, gavage on hepatic oxidative stress and inflammation induced by single i.p injection of methotrexate (MTX) at a dose of 20 mg/kg on the fifth day of the experiment. Oxidative status is expressed by hepatic content of malondialdehyde (MDA, (A)), superoxide dismutase (SOD, (B)), and reduced glutathione (GSH, (C)). Inflammatory status is expressed by proinflammatory cytokine tumor necrosis factor-α (TNF-α, (D)). Values are presented as mean ± SEM (n = 6/group). Statistical analysis was conducted using one-way analysis of variance (ANOVA) followed by Tukey’s Post hoc test. **** p < 0.0001, *** p < 0.001, ** p < 0.01, and * p < 0.05.
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Figure 10. Effect of 10 days administration of Chamaecyparis lawsoniana extract (CLAE) at 200 and 400 mg/kg/day, gavage on hepatic apoptosis induced by single i.p injection of methotrexate (MTX) at a dose of 20 mg/kg on the fifth day of the experiment. (A) depicts representative micrographs of immunohistochemically stained liver sections for p53 expression (arrowhead) and Bcl-2 expression of different study groups (×400 and Scale bar, 50 μm). Positive immune reaction for the target protein is demonstrated by a brown color. (B,C) are the quantification of p53 and Bcl-2, respectively. The hepatic contents of Bcl-2 (D), Bax (E), and caspase-3 (F) were also shown. Values are presented as mean ± SEM (n = 6/group). Statistical analysis was conducted using one-way analysis of variance (ANOVA) followed by Tukey’s Post hoc test. **** p < 0.0001, *** p < 0.001, ** p < 0.01, and * p < 0.05.
Figure 10. Effect of 10 days administration of Chamaecyparis lawsoniana extract (CLAE) at 200 and 400 mg/kg/day, gavage on hepatic apoptosis induced by single i.p injection of methotrexate (MTX) at a dose of 20 mg/kg on the fifth day of the experiment. (A) depicts representative micrographs of immunohistochemically stained liver sections for p53 expression (arrowhead) and Bcl-2 expression of different study groups (×400 and Scale bar, 50 μm). Positive immune reaction for the target protein is demonstrated by a brown color. (B,C) are the quantification of p53 and Bcl-2, respectively. The hepatic contents of Bcl-2 (D), Bax (E), and caspase-3 (F) were also shown. Values are presented as mean ± SEM (n = 6/group). Statistical analysis was conducted using one-way analysis of variance (ANOVA) followed by Tukey’s Post hoc test. **** p < 0.0001, *** p < 0.001, ** p < 0.01, and * p < 0.05.
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Figure 11. Photomicrographs of HE-stained sections of liver tissue showing histological features of different studied groups, control group (A), vehicle-treated methotrexate (MTX) group (B), Chamaecyparis lawsoniana extract (CLAE) at 200 and 400 mg/kg/day, gavage (C,D, respectively). Normal vesicular central nucleus (arrow), sinusoids (S), portal vein (PV), bile duct (Bd), dark pyknotic nuclei (curved arrow), dilated sinusoids (*S), inflammatory cellular infiltrations (IFs). (×400 and Scale bar, 50 μm). (E) shows scoring of histopathological changes in portal tract inflammatory cells. Hepatotoxicity was induced by single i.p injection of MTX at a dose of 20 mg/kg on the fifth day of the experiment, and CLAE administration started five days prior to MTX injection and continued for another 5 days. Statistical analysis for histopathological scoring was performed using Kruskal-Wallis test and Dunn’s test for multiple comparisons. ** p < 0.01, and * p < 0.05.
Figure 11. Photomicrographs of HE-stained sections of liver tissue showing histological features of different studied groups, control group (A), vehicle-treated methotrexate (MTX) group (B), Chamaecyparis lawsoniana extract (CLAE) at 200 and 400 mg/kg/day, gavage (C,D, respectively). Normal vesicular central nucleus (arrow), sinusoids (S), portal vein (PV), bile duct (Bd), dark pyknotic nuclei (curved arrow), dilated sinusoids (*S), inflammatory cellular infiltrations (IFs). (×400 and Scale bar, 50 μm). (E) shows scoring of histopathological changes in portal tract inflammatory cells. Hepatotoxicity was induced by single i.p injection of MTX at a dose of 20 mg/kg on the fifth day of the experiment, and CLAE administration started five days prior to MTX injection and continued for another 5 days. Statistical analysis for histopathological scoring was performed using Kruskal-Wallis test and Dunn’s test for multiple comparisons. ** p < 0.01, and * p < 0.05.
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Table 2. Top common targets ranked by the Degree method.
Table 2. Top common targets ranked by the Degree method.
RankTarget NameScore
1TP5359
2IL650
3TNF46
3HSP90AA146
5EGFR44
6IL1B43
7BCL242
8CASP337
8JUN37
10ALB36
11MMP935
12HIF1A34
13ESR130
14PTGS229
15STAT128
16MAPK326
17ERBB225
18MAPK124
19MAPK823
19JAK223
Table 3. Bioactive compounds of CLAE ranked by the Degree method.
Table 3. Bioactive compounds of CLAE ranked by the Degree method.
RankCompound Score
1Sequoiaflavone105
23-Hydroxysandaracopimaric acid104
23,7-Dimethylquercetin104
412α-hydroxy-8,15-isopimaradien-18-oic acid103
5Robustaflavone 7,4′-dimethyl ether102
6Bilobetin100
64′,5,6,7-Tetramethoxyflavone (Scutellarein tetramethyl ether)100
88alpha-8-Hydroxy-12-oxo-13-abieten-18-oic acid99
8Carnosol99
10Isoginkgetin97
11Matairesinol94
12Caffeoylshikimic acid93
13secoisolariciresinol guaiacylglyceryl ether92
14ent-Kaurenoic acid90
15Ferulic acid O-glucoside89
15Roseoside89
17lariciresinol-4′-guaiacylglyceryl ether88
17cyclolariciresinol88
19Sinapoyl D-glucoside87
19Malyngic Acid87
21Copalic acid86
21Naringenin86
23Coumaroylquinic acid82
24Pinopalustrin (Nortrachelogenin)80
24Kaempferol-3-O-arabinoside80
26Aromadendrin77
27Quinic acid76
28Phlorizin74
29Vanillic acid glucoside68
30L-Threonic acid59
31Protocatechualdehyde42
Table 4. Molecular docking results of the top three CLAE bioactive constituents against the top eight target proteins.
Table 4. Molecular docking results of the top three CLAE bioactive constituents against the top eight target proteins.
Target ProteinLigandDocking Score (kcal/mol)Interacting Amino Acid Residues Bond Type
TP53
(8DC4)
Sequoiaflavone−9.060Glu221
Ser229
Leu145 and Val147
Val147, Pro151, Pro222, and Pro223
Pro223
Cys220
Amide-Pi Stacked
Carbon–Hydrogen
Conventional Hydrogen
Pi-Alkyl
Pi-Sigma
Pi-Sulfur
3-Hydroxysandaracopimaric acid−6.291Pro151, Pro222, and Pro223
Val147
Alkyl
Conventional Hydrogen
3,7-Dimethylquercetin−7.112Leu145 and Val147
Glu221
Cys220 and Thr230
Val147, Pro151, and Pro222
Pro222 and Pro223
Cys220
Gly154 and Thr155
Alkyl
Amide-Pi Stacked
Conventional Hydrogen
Pi-Alkyl
Pi-Sigma
Pi-Sulfur
Unfavorable Donor–Donor
Co-crystallized ligand−7.040Pro223
Glu221
Cys220
Val147, Pro151, Pro222, and Pro223
Thr230
Val147
Cys220
Alkyl
Amide-Pi Stacked
Conventional Hydrogen
Pi-Alkyl
Pi-Donor–Hydrogen
Pi-Sigma
Pi-Sulfur
IL6
(4NI9)
Sequoiaflavone−7.444Leu33
Lys41 and Arg40
Arg168 and Lys171
Ser37
Alkyl
Pi-Alkyl
Pi-Cation
Pi-Donor–Hydrogen
3-Hydroxysandaracopimaric acid−4.837Leu33, Arg40, and Lys171Alkyl
3,7-Dimethylquercetin−6.277Leu33
Ser37
Arg40, Arg168, and Lys171
Lys171
Ser37
Arg168
Alkyl
Carbon–Hydrogen
Pi-Alkyl
Pi-Cation
Pi-Donor–Hydrogen
Unfavorable Donor–Donor
* TNF-α
(2AZ5)
Sequoiaflavone−9.429ProA117
LysB98 and IleB118
GlnA61 and TyrB119
LysA98
TyrA119
TyrB119
Alkyl
Carbon–Hydrogen
Conventional Hydrogen
Pi-Cation
Pi-Pi Stacked
Pi-Pi T-shaped
3-Hydroxysandaracopimaric acid−8.56SerB60 and TyrB151
TyrA119 and TyrB119
TyrA119
Conventional Hydrogen
Pi-Alkyl
Pi-Sigma
3,7-Dimethylquercetin−7.258LeuA57 and IleA155
GlyA121, TyrA151, and TyrB151
TyrA59
TyrA59
Alkyl
Conventional Hydrogen
Pi-Alkyl
Pi-Pi Stacked
Co-crystallized ligand−9.076GlyA121
TyrB59, TyrB119, and TyrB151
TyrA119
Halogen (Fluorine)
Pi-Alkyl
Pi-Sigma
HSP90AA1
(8AGI)
Sequoiaflavone−10.27Asn51
Ser50 and Gly97
Ala55, Met98, and Val 168
Asp54
Asn51
Met98
Ser52
Amide-Pi Stacked
Conventional Hydrogen
Pi-Alkyl
Pi-Anion
Pi-Donor–Hydrogen
Pi-Sigma
Van Der Waals
3-Hydroxysandaracopimaric acid−6.905Ala55, Lys58, and Met98
Gly132
Gly132
Gly135
Alkyl
Conventional Hydrogen
Unfavorable Acceptor–Acceptor
Carbon–Hydrogen
3,7-Dimethylquercetin−7.945Lys58 and Ile96
Asn51
Asn51
Ala55 and Met98
Met98
Alky
Carbon–Hydrogen
Conventional Hydrogen
Pi-Alkyl
Pi-Sulfur
Co-crystallized ligand−9.931Ile96, Met98, and Leu107
Asp93, Gly97, Asn106, and Thr184
Phe138
Ala55
Met98
Alkyl
Conventional Hydrogen
Pi-Alkyl
Pi-Sigma
Pi-Sulfur
EGFR
(7T4I)
Sequoiaflavone−10.14Lys745
Leu718, Thr790, Met793, and Thr854
Val726 and Ala743
Leu718, Val726, and Leu844
Cys797
Phe723
Carbon–Hydrogen
Conventional Hydrogen
Pi-Alkyl
Pi-Sigma
Pi-Sulfur
Pi-Pi T-shaped
3-Hydroxysandaracopimaric acid−8.331Leu718, Val726, Ala743, and Leu844
Thr790 and Thr854
Alkyl
Conventional Hydrogen
3,7-Dimethylquercetin−7.868Leu718
Thr790, Met793, and Thr854
Val726, Ala743, and Leu844
Leu718
Carbon–Hydrogen
Conventional Hydrogen
Pi-Alkyl
Pi-Sigma
Co-crystallized ligand−9.079Leu718, Val726, Ala743, Lys745, and Leu792
Asp800 and Glu804
Leu718, Gln791, and Asp800
Thr790, Met793, Phe795, Cys797, and Thr854
Val726 and Ala743
Leu718, Val726, and Leu844
Alkyl
Attractive Charge
Carbon–Hydrogen
Conventional Hydrogen
Pi-Alkyl
Pi-Sigma
IL1B
(1T4Q)
Sequoiaflavone−8.833Ala1
Val3
Val3, Asn7, Lys65, Lys88, and Ser153
Lys63 and Pro91
Ser43
Asn7
Alkyl
Carbon–Hydrogen
Conventional Hydrogen
Pi-Alkyl
Pi-Donor–Hydrogen
Unfavorable Donor–Donor
3-Hydroxysandaracopimaric acid−6.477Ser5
Ser43
Tyr68
Carbon–Hydrogen
Conventional Hydrogen
Pi-Alkyl
3,7-Dimethylquercetin−6.588Pro87
Ser43, Glu64, Leu62, and Lys65
Pro91
Val3
Ser5
Alkyl
Conventional Hydrogen
Pi-Alkyl
Unfavorable Acceptor–Acceptor
Unfavorable Donor–Donor
BCL2
(7LHB)
Sequoiaflavone−10.13Glu152
Glu136
Arg146 and Ala149
Tyr108
Leu137
Met115
Phe153
Amide Pi-Stacked
Conventional Hydrogen
Pi-Alkyl
Pi-Pi T-shaped
Pi-Sigma
Pi-Sulfur
Van Der Waals
3-Hydroxysandaracopimaric acid−7.917Met115, Leu137, Ala149, and Val156
Glu136
Phe104, Phe112, and Phe153
Glu136
Alkyl
Conventional Hydrogen
Pi-Alkyl
Unfavorable Acceptor–Acceptor
3,7-Dimethylquercetin−7.394Leu137 and Ala149
Ala100, Phe104, and Arg146
Arg146, Val148, and Ala149
Phe104
Alkyl
Conventional Hydrogen
Pi-Alkyl
Pi-Pi T-shaped
Co-crystallized ligand−12.78Ala100, Val133, Leu137, and Val156
Gly145
Arg107 and Asp111
Ala100, Asp103, and Asp111
Asp103 and Asn143
Glu152
Ala100, Phe112, Met115, Arg146, Val148, and Ala149
Tyr202
Tyr202
Alkyl
Amide Pi-Stacked
Attractive Charge
Carbon–Hydrogen
Conventional Hydrogen
Halogen (Cl, Br, I)
Pi-Alkyl
Pi-Donor–Hydrogen
Pi-Pi Stacked
CASP3
(3KJF)
Sequoiaflavone−8.477Trp214
Trp214
Asp253
Arg207
Asn208 and Phe250
Phe256
Conventional Hydrogen
Pi-Alkyl
Pi-Anion
Pi-Cation
Pi-Donor–Hydrogen
Pi-Pi Stacked
3-Hydroxysandaracopimaric acid−6.334Phe250
Asn208 and Phe250
Phe250
Carbon–Hydrogen
Conventional Hydrogen
Pi-Alkyl
3,7-Dimethylquercetin−6.261Arg207 and Ser251
Phe256
Trp206
Trp214
Conventional Hydrogen
Pi-Alkyl
Pi-Pi T-shaped
Unfavorable Donor–Donor
Co-crystallized ligand−8.20Arg207
Arg207, Asn208, Ser209, Trp214, and Phe250
Arg207, Asn208, and Ser251
Phe250 and Phe252
Phe256
Attractive Charge
Conventional Hydrogen
Carbon–Hydrogen
Pi-Alkyl
Pi-Pi Stacked/3.72
* The TNF-α model is based on the co-crystal structure of the TNF-α dimer.
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MDPI and ACS Style

Fikry, E.; Orfali, R.; El-Sayed, S.S.; Perveen, S.; Ghafar, S.; El-Shafae, A.M.; El-Domiaty, M.M.; Tawfeek, N. Potential Hepatoprotective Effects of Chamaecyparis lawsoniana against Methotrexate-Induced Liver Injury: Integrated Phytochemical Profiling, Target Network Analysis, and Experimental Validation. Antioxidants 2023, 12, 2118. https://doi.org/10.3390/antiox12122118

AMA Style

Fikry E, Orfali R, El-Sayed SS, Perveen S, Ghafar S, El-Shafae AM, El-Domiaty MM, Tawfeek N. Potential Hepatoprotective Effects of Chamaecyparis lawsoniana against Methotrexate-Induced Liver Injury: Integrated Phytochemical Profiling, Target Network Analysis, and Experimental Validation. Antioxidants. 2023; 12(12):2118. https://doi.org/10.3390/antiox12122118

Chicago/Turabian Style

Fikry, Eman, Raha Orfali, Shaimaa S. El-Sayed, Shagufta Perveen, Safina Ghafar, Azza M. El-Shafae, Maher M. El-Domiaty, and Nora Tawfeek. 2023. "Potential Hepatoprotective Effects of Chamaecyparis lawsoniana against Methotrexate-Induced Liver Injury: Integrated Phytochemical Profiling, Target Network Analysis, and Experimental Validation" Antioxidants 12, no. 12: 2118. https://doi.org/10.3390/antiox12122118

APA Style

Fikry, E., Orfali, R., El-Sayed, S. S., Perveen, S., Ghafar, S., El-Shafae, A. M., El-Domiaty, M. M., & Tawfeek, N. (2023). Potential Hepatoprotective Effects of Chamaecyparis lawsoniana against Methotrexate-Induced Liver Injury: Integrated Phytochemical Profiling, Target Network Analysis, and Experimental Validation. Antioxidants, 12(12), 2118. https://doi.org/10.3390/antiox12122118

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