Chemicals and Reagents
The various chemical and reagents used in the present study includes Paracetamol (Sigma–Aldrich, Germany), ketamine (Sigma–Aldrich, Germany), formalin (Sigma–Aldrich, Germany), Xylazine (Sigma– Aldrich, Germany), (Sigma–Aldrich, Germany) and Poncirin (Sigma–Aldrich, Germany). ELISA kits for the determination of TNF‐α, IL‐1β and IL-6 were purchased from the Thermo Fisher Scientific (Thermo Fisher Scientific, USA). All the chemical used in the present study were of analytical grades and diluted with normal saline 0.9 % (2 % DMSO). Neubauer hemocytometer (Feinoptik, Germany) was used for hematological analysis, while Hemoglobin (Hb) content was determined by Sahli’s haemoglobin meter. Liver function tests (LFTs) were analyzed by AMP diagnostic kits (Graz, Austria) according to manufacturer’s instructions. The primary and secondary antibodies were obtained from the Santa Cruz (Santa Cruz Biotechnology, Inc).
The animals (Male Albino BALB/c, age 8-9 weeks and weighing 28-31 gm) were obtained from the National Institute of Health (NIH, Islamabad). All the animal activities were performed in the department of pharmacy (pathogen free zone), Quaid-i-Azam University, Islamabad (Pakistan) and the study was approved by the animal ethical committee of Quaid-i-Azam University, Islamabad (Pakistan) (No. #BEC‐FBS‐QAU2018‐90). The experimental animals were housed under standard conditions such as temperature 23±0.5 °C and humidity of 50±5 % with 12 h light-dark cycles. “Principles of Lab Animals Care” from NIH publication were followed in all laboratory procedures (Zimmermann 1983). The behavioral activities were performed from 7.30 a.m. to 7.30 p.m. and animals were used once during the experiment. The number of animals were used less to avoid unnecessary harm and discomfort to the animals.
Grouping of animals
Animals were classified into six groups (n=8) such as normal control (normal saline with 2% DMSO), Paracetamol treated 640 mg/kg, Silymarin 50 mg/kg (dissolved in normal saline and 2 % DMSO) and three groups of Poncirin (5, 15, 30 mg/kg (dissolved in normal saline and 2 % DMSO)). The dose of the Poncirin was selected based on the previously reported study (Afridi et al. 2019; Khan et al. 2020; Ullah et al. 2020). All the drugs (Paracetamol, Silymarin and Poncirin) were administered via intraperitoneal (i.p.) route. The animals were pre-treated with the Poncirin and Silymarin before the induction of the Paracetamol-induced hepatic injury.
Body weight and Liver weight variation
The changes in the body weight of all the treated groups were assessed before (day 0) and after (day 8) the disease induction. The animals were weighted using digital electronic weighing balance and their respective weights were noted, while the changes in the body weights were during the course of the study were analyzed as reported previously (Afridi; et al. 2019). Similarly, the liver weight variation was performed to determine the in the changes in the liver weight variation following Paracetamol-induced liver injury and to observe the effect of the Poncirin treatment on the hepatic changes. The liver weight variations were determined as reported previously (Afridi et al. 2019; Ullah et al. 2020).
The food intake was assessed in all the treated groups before the commencement of disease induction and every day after the diseases induction (Afridi et al. 2019). The food was weighted, placed for each group and 24 h latter the amount consumed as well as the quantity of the feed used was calculated as described previously. The amount of the feed consumed in all the treated groups were compared (Afridi et al. 2019, Ullah et al. 2020).
The Kaplan-Maier analysis was used for the survival in all the treated groups following Paracetamol-induced liver injury. The effect Poncirin on the survival rate was evaluated daily for 8 days as reported previously (Afridi et al. 2019; Ullah et al. 2020).
Collection of Blood Samples and Organ
At the end of experiment the animals were euthanized with cervical dislocation as reported previously (Khan et al. 2019). Following cervical dislocation, the organs were removed carefully, rinsed, and washed with distilled water and placed in ice cold solution. For further analysis such as histological and biochemical analysis the tissues were processed according to the previously described methods (Khan et al. 2019; Ullah et al. 2020).
The hematological analysis was performed to assess the changes in the blood composition following induction of the Paracetamol-induced liver injury in all the treated groups. The blood was withdrawn directly from the cardiac puncture carefully, placed in EDTA tubes and analyzed as reported (Khan et al. 2019).
In order to separate the serum from the cellular components, the blood was centrifuged at 6000 rpm at 4°C for 10 min. The serum analysis such as alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate transaminase (AST) and bilirubin were analyzed in triplicate as reported previously (Ullah et al. 2020).
NO (Nitric Oxide) determination
The NO assay was performed using Griess reagent method and the effect of the Poncirin (5, 15, 30 mg/kg, i.p) was evaluated (Atiq, Shal et al. 2019). The NO concentration was determined in both the liver tissue and plasma in all the treated groups. The blood was collected directly from the cardiac puncture and centrifuged at (5000 rpm for 10 min at 4 0C) to separate the plasma from the cellular contents as reported previously (Khan et al. 2019).
Histopathological study of liver tissues
The histological changes in the liver tissue following induction of injury with the Paracetamol was evaluated using H and E staining (Atiq et al. 2019). The H and E staining was performed via previously reported method. The histological changes were quantified as normal, moderate and severe based on the hepatic cytoplasm inflammation, centrilobular necrosis, cellular hypertrophy, vacuolization and steatosis (Keppler et al. 2007). The histopathological changes were quantified by two independent histopathologist and scored double blindly (Kazmi et al. 2018). The Masson’s trichrome staining was performed to assess the changes in the liver parenchyma following Paracetamol-induced liver injury (Khan et al. 2020). The left lateral lobe was selected and sliced. The tissue were fixed in formalin and subjected to the Masson’s trichrome staining. The histological changes were quantified double blindly by the histopathologist as reported previously (Khan et al. 2020). The fibrosis score was calculated by selected minimum of 10 fields per slice and their mean was calculated. The extent of the fibrosis was graded from 0-4, while the 0 means no fibrosis and 4 indicates maximum fibrosis. The Periodic acid-Schiff (PAS) staining was performed to determine the glycogen accumulation in the liver tissue following Paracetamol-induced liver injury (Khan et al. 2020). The PAS staining was performed according to the previously reported method. The changes in the PAS staining were quantified ranging from normal to inflammation and even cirrhosis (Khan et al. 2020).
Effect of Poncirin on antioxidant and oxidative stress markers
The antioxidants and oxidative stress balance is significantly altered following Paracetamol-induced liver injury (Atiq et al. 2019). The various antioxidants such as GST, GSH, Catalase and SOD, while the oxidative stress marker such as MDA were analyzed and the effect of the Poncirin was evaluated as reported previously (Khalid et al. 2018).
Myeloperoxidase (MPO) activity
The MPO serves as a marker of the neutrophilic infiltration and neutrophils are the first cells to respond against the inflammatory insult (Shal et al. 2019). The neutrophilic infiltration into the liver following Paracetamol-induced liver injury was evaluated and the effect of the Poncirin was investigated. The MPO activity was determined in all the treated groups and the results were compared (Atiq et al. 2019).
Measurement of IL-1β, IL-6 and TNF-α production
The cytokines production in liver tissue following Paracetamol-induced liver injury were determined according to the previously described method (Shal et al. 2019; Zeeshan et al. 2019). The various cytokines that are commonly implicated in the numerous inflammatory disorders such as IL-1β, IL-6 and TNF-α were studied and the effect of the Poncirin was determined. At Day 8 of Paracetamol administration (i.p.), the liver tissue was removed, and their proteins were extracted from 100 mg tissue/ml PBS to which 0.4 M NaCl, 0.05% Tween 20, and protease inhibitors were added. The liver tissues were homogenized and centrifuged for 10 min at 3,000 g, and the supernatant was frozen at −80 °C for later quantification. The TNF-α, IL-1β, and IL-6 production was calculated using a commercially available TNF-α, IL-1β and IL-6 ELISA kit (eBioscience, Inc., San Diego, CA) (Rasheed et al. 2018).
The immunohistochemistry analysis was performed to assess the changes in the expression level of the various inflammatory signaling proteins such as NF-κB, JNK and COX-2 following Paracetamol-induced liver injury (Rasheed et al. 2018). The paraffin embedded tissues were treated with xylene, alcohol (graded wise), normal goat serum (NGS), primary antibodies and placed overnight. The next day primary antibodies were washed, while treated with secondary antibodies, avidin-biotin complex and stained with the DAB reagent as reported (Rasheed et al. 2018).
Prediction of target genes associated with Paracetamol-induced liver injury and genes target for Poncirin
The genes associated with the Paracetamol-induced liver injury from the PUBMED database (National center for biotechnology information (https://www.ncbi.nlm.nih.gov/)) with search query of “Paracetamol-induced liver injury” and humans (Xinqiang et al. 2020). A total of 434 genes were retrieved from the GeneBank search engine which were implicated in the pathogenesis of the Paracetamol-induced liver injury and filtered for Homo sapiens. Similarly, to retrieve the genes list related with the Poncirin various search engines were utilized such as Comparative toxicogenomics database (http://ctdbase.org/), Therapeutic targets database (http://bidd.nus.edu.sg/group/cjttd/) and traditional chines medicines system pharmacology database and an-alysis platform (http://lsp.nwu.edu.cn/index.php) as reported previously (Xinqiang et al. 2020). The Comparative toxicogenomics database was used to assess the gene interacting with the Poncirin. These interacting genes were plotted in the form of the cluster using String online software (https://string-db.org/). The Comparative toxicogenomics database using disease query to assess the interaction of the genes associated with the Poncirin (Xinqiang et al. 2020). Similarly, the genes that are related with the Poncirin were also assessed and the implication in other disease based on the similarity were analyzed (Shal et al. 2020; Xinqiang et al. 2020). Similarly, the Funrich analysis was performed for the functional enrichment and protein-protein interactions. Furthermore, the cellular component, transcription factors and molecular function based on the P value using Funrich enrichment analysis on the genes retrieved from Comparative toxicogenomics database (Xinqiang et al. 2020; Naveed et al. 2021).
Construction of the target gene network
The PUBMED database was used to retrieve the genes associated with the Paracetamol-induced liver injury and imported to the Cytoscape 3.7.1 software to create a network based on their interaction (Xinqiang et al. 2020). Furthermore, gene ontology enrichment analysis was performed to identify the interaction and to assess the systemic involvement of the concern genes. The 0.90 score was set as confidence level for minimal interaction (Ali et al. 2020; Xinqiang et al. 2020).
Molecular docking and active site prediction
The molecular docking analysis was performed using Autoock vina 4.2 software. The crystal structure of respective proteins were downloaded from the Protein Data Bank (http://www.pdb.org/) and saved as PDB file (Naveed et al. 2019; Khan et al. 2021). The protein were prepared i.e. energy was minimized, water molecules were removed, co-crystalized ligand were removed and hydrogens were added using Swiss PDB viewer and discovery studio visualizer_16 (Khan et al. 2020). The active site of the proteins were analyzed using CASTp online software and the amino acids within the active pockets were assessed within the chain of interest (Khan et al. 2020). The ligand (Poncirin) was prepared using ChemBioDraw_14, minimized and saved as SDF file. The ligand was then converted to PDB file using discovery studio visualizer_16 (Khan et al. 2020; Shal et al. 2021). The Autodock vina was used to assess the binding interaction of ligand with the proteins. The ligand and protein were converted to PDBQT, Grid parameter files and configuration file was generated (Khan et al. 2020; Xinqiang et al. 2020). Finally, the vina was used to assess the binding energy of the ligand with the protein targets. The results were visualized using discovery studio visualizer_16, while the ligand-protein complex 3D and 2D images were saved (Khan et al. 2020). The binding energies of the ligand-protein complex and mode of the interaction i.e. hydrogen boding, vander waal, salt bridges, π–π interaction, π-sigma bond, and many other hydrophobic interactions were shown. The number of hydrogen bonds and the maximum negative energies of the ligand-protein complex indicate stable complex (Naveed et al. 2019). Similarly, the ligand interaction was evaluated against the protein binding site of the DNA i.e. c-fos binding site of the DNA.
Validation of Molecular docking
The Molecular docking analysis was validated by re-docking the ligand following extraction from the protein target and RMSD value was calculated (Khan et al. 2020). The model is considered valid if the root mean square deviation is less than 2 Å. The ligRMSD software was used to determine the RMSD value of the docked ligand from the re-docked ligand and superimposed ligand were shown using discovery studio visualizer_16 (Khan et al. 2020).
Molecular Dynamics Simulation and Analysis
The AMBER20 simulation package was utilized to accomplish molecular dynamics simulation of Poncirin-1vkx complex. The protein parameters were generated using ff14SB whereas general Amber force field was applied assign Poncirin parameters (Khan et al. 2020). The complex was solvated explicitly in TIP3P water box where counter ions were added to achieve charge neutralization. The complex was the forwarded to energy minimization phase and subjected to 2500 rounds of steepest descent and conjugate gradients algorithms. Afterward, the complex was equilibrated via 1000 ps of heating and density equilibration in the presence of weak restraints. Pressure equilibration was achieved for 2 ns at temperature of 300 K. The production run was performed for 100 ns using NPT ensemble under periodic boundary conditions. Particle mesh Ewald method was considered to explain electrostatic interaction setting the cut-off value of 10 Å. The hydrogen bonds were constrained using SHAKE algorithm to keep the bond length at equilibrium. To evaluate complex structural stability, CPPTRAJ module was used (Khan et al. 2020).
Estimating MM-GBSA Binding Free Energies
Molecular mechanics energies combined with the generalized Born surface area (MM-GBSA) was run further to estimate binding free energies of the complex. Five hundred snapshots at regular intervals were selected and MM-GBSA analysis was performed as performed previously (Khan et al. 2020).
In silico pharmacokinetic analysis and toxicokinetic analysis
The pharmacokinetic analysis of the Poncirin was performed using Swiss ADME (absorption, distribution, metabolism, and elimination) software. The various parameters that were studied includes physicochemical properties, lipophilicity, water solubility, pharmacokinetics, drug likeness and medicinal chemistry aspects (Atiq et al. 2019, Xinqiang et al. 2020). Furthermore, the preADMEDT software utilized to assess the potential metabolites and the metabolites were predicted based on their probability such as Rank1, Rank2, Rank3 etc (Atiq et al. 2019). The aim of the in silico toxicity assessment was to determine the untoward effect of the Poncirin exposure against an organism using known route of administration such as oral, subcutaneous, intravenous, inhalation and inhalation (Atiq et al. 2019). The LD50 for the IP, oral, sub-cutaneous and IV route were computationally assessed, while the training set of the previously compounds were screened against the Poncirin based on the toxicity (Xinqiang et al. 2020). Furthermore, based on the GUSAR online software prediction, the Poncirin toxicity against the rodents was calculated. Furthermore, the Poncirin was assessed for further classification according to the Organization for Economic Co-operation and Development (OECD) chemical classification (Xinqiang et al. 2020). Based on the search query the software predicts the nature of the compound and gives the class of the compounds. Similarly, the PASS online software based approach was used to assess the potential activity of Poncirin and the activity was based on the probability of being active (pa) to the probability of being in active (pi) as reported (Xinqiang et al. 2020).
The data was analyzed as Mean ± S.D using SPPS version _18. The difference between different groups in the present study was determined using one way analysis (ANOVA) followed by Dunnett’s t test. P value less than 0.05 was chosen as statistically significant. The Graphpad Prism version_5 was used for the plotting of data.