Plant-Derived Bioactive Compounds as an Antidiabetic AgentView this Special Issue
Integrating In Silico and In Vitro Approaches to Screen the Antidiabetic Properties from Tabernaemontana divaricata (Jasmine) Flowers
The purpose of this study was to assess different in vitro biological activities such as phytochemical constituents, enzymatic antioxidant status, cytotoxicity through hemolytic activity, and antidiabetic potential of plant methanolic extract through glucose uptake by yeast cells. Further, using in silico approach by the SwissADME technique the drug-likeness rules for bioactive components were characterized, while potential interactions were identified via molecular docking of a ligand with target proteins by GOLD 5.3.0. The results showed that T. divaricata was rich in TPC and TFC, i.e., 62.32 ± 4.02 and 24.53 ± 0.61, respectively, and the cytotoxic potential was 10% towards human RBCs, while protein estimation revealed the presence of protein in the extract, which was 22.82 ± 4.6. DPPH assay in comparison with ascorbic acid and several enzymatic assays, such as CAT, SOD, and POD, showed maximum antioxidant potential, i.e.,15.9 ± 2.33%, 65.57 ± 13.4%, 3.02 ± 3.4, 15.87 ± 0.5, and 0.74 ± 0.2, respectively. Glucose uptake by yeast cells, i.e., α-amylase and α-glucosidase, showed a maximum antidiabetic potential such as 75.11 ± 1.44%, 41.81 ± 3.75%, and 35.9 ± 1.24%, respectively. Our results indicate that the methanolic extract of T. divaricata has antioxidant potential and inhibits α-amylase and α-glucosidase activity and possesses maximum antidiabetic potential. The results provide scientific proof that the medicinal plant being studied is a powerful source of natural antioxidant, antidiabetic, and medicinally significant substances. In silico study, using a molecular docking, unveiled that two compounds showed good interactions with 5kzw protein with considerable binding affinities and fulfilled docking parameters. It may conclude that T. divaricata is an important vegetable with a potent source of natural antioxidants and antidiabetic activity justifying its traditional use in green therapeutics.
Diabetes is a metabolic disorder characterized by a high level of glucose in the bloodstream triggered by inadequate insulin output or insulin activity . Diabetes is a dynamic chronic disease needing ongoing medical care with harm reduction approaches within glycemic control . Polyuria, polydipsia, dry mouth, itchy skin, blurry vision, nausea, and exhaustion are the typical physical symptoms of DM . Diabetes accounts for over 3.8 million deaths annually and is therefore the fifth leading cause of mortality . This disease is becoming disastrously underdeveloped (low-income) countries . Pakistan is amongst the ten countries that are expected to have high figures of people with diabetes by 2030 .
Diabetes increases the risk of several health problems and has a severe effect on the eye, kidney, foot, blood pressure, etc. . α-Amylase involves the starch hydrolysis into the small scraps of sugar . During diabetes, ROS are induced and cause β-cell glucose toxicity . Cytotoxic T lymphocytes (CTLs) are one of the types of T cells, and CTLs are triggered to clear cells associated with the virus .
Oxidative stress is caused by an increase in reactive oxygen species, which is the primary cause of diabetes and can have serious consequences. Enzymes including superoxide dismutase, glutathione, peroxidase, and catalase are involved in enzymatic defense systems [10, 11]. The peroxidases are a family of enzymes with the ability to oxidize different substrates using H2O2 . Antioxidants (e.g., superoxide dismutase (SOD), reduced glutathione (GSH), and other antioxidant enzymes) are generally providing tools to investigate the stress-related diabetes . Several natural antioxidants are present in plants, and usually, these are vitamins C and E, tannins, and flavonoids. These antioxidants have the competency to sustain or uphold β-cell administration, and in this way, they could diminish the glucose level in the blood. It has been found that medicinal plants, e.g., Coriandrum sativum, Fraxinus excelsior, Casearia esculenta, Caesalpinia bonducella, and Biophytum sensitivum, are more cost-effective, have fewer side effects, and are more persuasive in curing diabetes mellitus than conventional drugs .
Due to the high cost of pharmaceuticals, typical and traditional plants could be used to cure different diseases as 70 to 80% of the developing world depends on them . For this purpose, 800 plants could be considered for their antidiabetic potential . A plant species known as Tabernaemontana divaricata (TD) belongs to the family Apocynaceae, locally acknowledged as Tagar/Chandni/Crepe Jasmine. In contrast to Staphylococcus aureus and Escherichia coli, Tabernaemontana divaricata flower extract has strong antibacterial activity .
In silico approaches to the drug design has the benefit of reducing the time and expense of developing new targets. In silico methods that can describe interacting molecules and predict three-dimensional (3D) structures have been used to solve several biological problems. In this context, this study aimed to evaluate the phyto-components, total phenolic content (TPC), total flavonoid content (TFC), and in vitro biological properties such as DPPH (2,2-diphenyl-1-picrylhydrazyl) free radical scavenging, enzymatic antioxidant activities, hemolysis, and antidiabetic potentials of methanolic extract of T. divaricate flower. Further, to develop effective inhibitors, in silico analysis was performed to determine the interaction of identified antidiabetic compounds with the target protein.
2. Material and Methods
2.1. Determination of Total Phenolic and Flavonoid Contents (TPC and TFC)
By following the protocol of Singleton et al. , the TPC of methanolic extract of T. divaricata was evaluated. The absorbance for the mixtures of solutions was measured at 760 nm with gallic acid as a standard, and TPC results were expressed as milligram gallic acid equivalent per gram dry weight (mg GAE/g dw) in triplicates.
The procedure of Bao et al.  was followed to calculate the total flavonoid content (TFC) of T. divaricata. Eventually, the absorbance of the mixtures was measured against a reagent blank at 510 nm and TFC was noted in triplicate samples and presented as milligram quercetin per gram dry weight (mg QE/g dw).
2.2. Antioxidant Activity Assays
2.2.1. DPPH Free Radical Scavenging Assay
By following the protocol of Gyamfi et al. , the free radical scavenging capability of T. divaricata flower methanolic extract was evaluated against free radicals of DPPH. Ascorbic acid was used as a standard. The following formula was used to calculate the percentage inhibition of plant extract against DPPH free radicals:where AB is the absorbance of blank and AS is the absorbance of the sample.
2.2.2. Enzymatic Antioxidant Activities
The method proposed by Mohebbi et al.  was performed to measure thecatalase (CAT) activity. In this method, 0.1 mL of T. divaricata extract was added in 0.05 M K2HPO4 and 1.4 mL hydrogen peroxide (H2O2), which was taken as a substrate, and catalase enzymes were added for the decomposition of H2O2. The decomposition was detected using a UV spectrophotometer (UV-1601, Shimadzu, Germany) by calculating the reduction in the absorbance for 5 min at 240 nm. The results of this activity are denoted as μM of consumed H2O2/min/mg of protein. Similarly, peroxidase (POD) activity was checked in which guaiacol was used as hydrogen. The experiment was carried out by measuring the difference at 470 nm for 1 minute. The enzymatic activity was described as a unit (one activity unit defined as absorbance at 470 nm changes 0.001 per min) . The rate of inhibition in the photoreduction of nitroblue tetrazolium (NBT) by the mean of superoxide dismutase (SOD) enzymes was calculated to determine SOD operation. The reaction mixture used in this activity has 50 mM sodium phosphate buffer of pH 7.6, 50 mM sodium carbonate, 0.1 mM EDTA, 50 μM NBT, 12 mM·L-methionine, 10 μL riboflavin, and 100 μL crude extract within an exact having 3.0 mL volume. On the other hand, the control reaction was preceded in the absence of extract. The SOD behavior was measured by exposing the following reaction mixture to white light at room temperature for 15 minutes. After incubation for 15 min, the absorbance was noted at 560 nm with the help of a spectrophotometer .
2.3. Cytotoxicity through Hemolytic Activity
To estimate the hemolytic activity of plant extract against human red blood cells (RBCs), the method of Powell et al.  was followed. PBS was used as the negative control, while 0.1% Triton X-100 was served as a positive control. The absorbance at 576 nm was noted.
2.4. Antidiabetic Assays
2.4.1. α-Amylase Inhibition Assay
α-Amylase inhibitory activity of T. divaricata flower extract was assessed by following the procedure of Shai et al. . Various concentrations of extract were incubated in phosphate buffer of 0.1 mol/L at pH 6.8 and 2 U/mL porcine pancreatic amylase 500 μL for 20 minutes at 37°C. 1% starch of 200 μL was mixed in phosphate buffer of 0.1 mol/L with pH 6.8 and added to mixtures of extract. After incubation at 37°C for 1 h, 1 mL of color reagent (3,5dinitrosalicylic acid) was added to the mixtures, and finally, the absorbance was recorded at 540 nm after boiling this mixture for 10 minutes. Control was without inhibitor, and the percentage of inhibitory efficacies of the extract was measured using the following formula:
2.4.2. Intestinal α-Glucosidase Inhibitory Assay
The inhibitory capability of α-glucosidase was evaluated by following the procedure of Ademiluyi and Oboh  with some modifications. Different concentrations of the extract were mixed with a 100 μl solution of 1.0 U/mL α-glucosidase and phosphate buffer whose pH was adjusted to 6.8, and the mixtures were incubated for 15 minutes at 37°C. After this, 5 mmol/L solutions of PNPG with the amount of 50 μL in phosphate buffer 0.1 mol/L (pH 6.8) were poured into the solutions and incubated again for 20 minutes at 37°C. The absorbance of the control and sample was measured at 405 nm, and the percentage inhibitory activity of glucosidase was calculated using the following formula:where Acontrol is the absorbance of the mixture without extract and Asample is the absorbance of the mixture with the extract.
2.4.3. Glucose Uptake in Yeast Cells
The protocol of Cirillo  was used to perform glucose uptake in yeast cells. Suspension of yeast (1%) was centrifuged for 5 min at 4200 rpm. By taking supernatant 10% v/v yeast cells, the suspension was prepared. 2 mg of an extract was dissolved in 1 mL of DMSO. These mixtures were then added in the different molar concentrations of 1 mL solution of glucose and at 37°C incubated for 10 min. For starting the reaction, 100 μL of suspension was added to this mixture, then vortexed, and incubated again at 37°C for 60 min. The mixture was then centrifuged at 3800 rpm for 5 min, and for the estimation of glucose, the absorbance was taken at 520 nm. The percent increase in glucose uptake was calculated using the following formula:
The control consisted of all the reagents except plant extract, and metronidazole was used as a standard drug.
2.5. In Silico Study
2.5.1. SwissADME Analysis
Fourteen important bioactive compounds in the methanolic extract of T. divaricata flowers were selected due to their bioactive potential towards antitumor, antibacterial, and anti-inflammatory properties and to give better pharmacological activities [27–29]. These compounds, enlisted in Table 1, are subjected to a theoretical in silico ADME prediction study using the Web tool, SwissADME (http://www.sib.swiss). To predict suitable properties, 2D structural models of analyzed compounds were drawn in SDF format and transferred to the simplified molecular-input line-entry system (SMILES) format. The SwissADME server tool was used to measure physicochemical properties of the compounds such as molecular weight, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bonds, molar refractivity, lipophilicity (ALogP), and topological polar surface area (TPSA). The drug-likeness efficiency of the selected compounds was examined for first-round screening using Lipinski, Ghose, and Veber rules based on their physicochemical properties [30–32], and then, pharmacokinetics and medicinal properties were also examined.
Drug-likeness, bioavailability, and pharmacokinetic abilities are important parameters to predict the active potential molecules for the purpose of drug development. In the clinical trials, many potent medicines fail in the drug development phase because of their weak abilities. To ensure that the bioactive compounds of Tabernaemontana divaricata have drug-like characteristics, all of the compounds in this study were subjected to ADME and prediction experiments before molecular docking.
2.5.2. Molecular Docking Analysis
The compounds that went through the filter were docked with the target protein, resulting in improved docking studies that predicted the potential binding of inhibitor to the protein. According to the results of SwissADME, 9 of 26 compounds were chosen to describe the major compounds contained in the extracts. The three-dimensional structures of compounds and target protein were calculated using the Protein Data Bank (PDB) database. GOLD version 5.3.0 and BIOVIA Discovery Studio were used to perform docking calculations (http://www.3dsbiovia.com/) for designing and visualization .
(1) Protein Preparation for Dockings. For the molecular docking studies of the synthesized compounds, GOLD docking software version 5.3.0 was used. Protein Data Bank was used to obtain the coordinated crystal structure of the 5kzw protein (http://www.rcsb.org/pdb/home/home.do)  and saved in PDB format. Essential hydrogen atoms were added with the aid of GOLD. GOLD score is a function that mimics a molecular mechanism and has been optimized for calculating ligand-binding positions . Affinity (grid) maps of 10 Å and grid points with 0.75 Å spacing were generated .
(2) Ligand and Energy Minimization. For ligand’s energy minimization, the ChemDraw Ultra 12.0 and Chem3D Pro were used. The ligand atoms were given the Gasteiger partial charges. Rotatable bonds were described by merging nonpolar hydrogen atoms. The ligands were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov) . GOLD takes into account the degree of freedom in the binding site that corresponds to the reorientation of hydrogen bonds of donor and acceptor groups. Despite accounting for a small fraction of the total conformational space available, this degree of freedom accounts for a significant difference in binding energy values .
(3) Ligand-Protein Docking. For predicting the binding affinities of a variety of ligands, molecular docking protocols are commonly used . The parameters of molecular docking software were used to conduct the experiments (https://www.ccdc.cam.ac.uk/). The Lamarckian genetic algorithm (LGA) and the Solis and Wets local search method were used to simulate docking . The initial positions, orientations, and torsions of the ligand molecules were chosen at random. Each docking experiment was divided into ten separate runs, each of which was set to end after a maximum of 1.5 energy evaluations.
2.6. Statistical Analysis
The experimental results were performed in triplicate, and the data were expressed as mean ± S.E. One-way analysis of variance (ANOVA) was done for statistical analysis of data employing SPSS version 22.0. For statistical significance, was considered. Using GOLD version 5.3.0 and BIOVIA Discovery studio visualizer (http://www.3dsbiovia.com), docking calculations were carried out.
3.1. Phytochemical Assays
The estimated total phenolic content of T. divaricata methanolic extract ranged from 35.62 ± 5.31 to 62.32 ± 4.02. The estimated total flavonoid content of T. divaricata flower extract ranged from 13.95 ± 1.33 to 24.53 ± 0.61. The maximum quantity of total phenol and flavonoid was 1 mg, while the minimum was 31 μg as shown in Table 2.
3.2. Antioxidant Activities
Extract antioxidant activity was measured in comparison with ascorbic acid. The measured antioxidant potential ranges from 1.49 ± 0.33 to 15.9 ± 2.33, while ascorbic acid was 1.15 ± 0.58 to 65.57 ± 13.4. The antioxidant potential of the extract was less than ascorbic acid at maximum concentration; however, the potential was improved at lower concentration in comparison with ascorbic acid as shown in Table 2.
3.2.1. Enzymatic Antioxidant Activities
Enzymatic antioxidant activities by T. divaricata such as catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD), as shown in Table 3, were 3.99, 1.27, and 23.80 U/mg protein, respectively. The free radical scavenging, along with an increase in physiological antioxidants (e.g., CAT, SOD, and POD), was possibly due to the presence of the phytochemicals of this plant.
3.3. Cytotoxicity through Hemolytic Activity
Hemolytic activity of any compound is a sign of common cytotoxicity towards normal healthy cells. In this research, the extract exhibited 10% cytotoxicity towards human erythrocytes as shown in Table 3. Such findings demonstrated that if medicinal formulations from this plant are used at low concentrations, the parameters of the RBC membrane will not change. Further research is essential on this medicinal edible plant in the context of drug development and discovery.
3.4. Antidiabetic Potential
3.4.1. α-Amylase and α-Glucosidase Inhibitory
The estimated α-amylase concentration range of T. divaricata flower extract was 16.76 ± 3.97 to 41.81 ± 3.75. The average values of α-glucosidase inhibitory activity ranged from 17.88 ± 1.40 to 35.9 ± 1.24. The inhibition potential of both enzymes was maximum at 200 ug/mL and minimum at 50 ug/mL as shown in Table 4.
3.4.2. Glucose Uptake by Yeast Cells
The uptake of glucose was evaluated by incubation of yeast cells in different molar concentrations of glucose and T. divaricata extract. At 5, 10, and 25 mM glucose concentrations with 1, 2, and 3 mg/mL concentration of T. divaricata extract, the results showed that by rising the extract concentration the uptake of glucose percentage was increased, while it showed an inverse relation with the glucose molar concentration as described in detail in Figure 1, which shows the maximum absorbance at 5 mM of glucose and 3 mg/mL concentration of extract.
3.5. In Silico SwissADME Analysis
Due to weak drug-likeliness and pharmacokinetic characteristics, many potent drugs fail in clinical trials or later stages of drug discovery. All of the compounds in this sample were subjected to drug-likeness and ADME prediction tests before molecular docking to ensure that they had drug-like characteristics.
3.5.1. Physicochemical Properties
A drug's physicochemical properties have a significant effect on its metabolic destiny in the body. The results from Table 1 showed that the molecular weight of all compounds met the criterion (which should be ≤ 500 g/mol) except D-glucopyranoside (MW 504.44 g/mol) in accordance with one of the criteria laid down in the Lipinski rule of five. Of all the studied compounds, 17 compounds had less than 10 rotatable bonds, and others had more than 10, which is not acceptable. Further, the molar refractivity of all compounds was within the acceptable range (40 and 130) except squalene, 1-heptatriacotanol, and methyl ester, and these three compounds satisfy the criteria for oral bioavailability.
TPSA is another key parameter correlated with the drug's bioavailability. High oral bioavailability for passively absorbed compounds has TPSA < 140 Å2. Table 1 reveals that all the selected compounds were found to be polar with TPSA values ranging from 0.00 Å2 to 80.48 Å2 except D-glucopyranoside, desulphosinigrin, and lactose, which had the highest TPSA (>140 Å2). High solubility can facilitate complete absorption of the administered through oral administration, while low solubility limits the drug absorption in the gastrointestinal tract . Table 1 shows that all of the tested 26 compounds have good to moderate water solubility, with a log S value between −0.18 and −5.6, which may promote good oral adsorption.
3.5.2. Pharmacokinetic Properties
Interestingly, except for three compounds, as shown in Table 5, all were observed with high intestinal absorption and thus could penetrate very easily through the intestinal lining and be accessible to the cell membrane. To meet their molecular target, drugs that function in the central nervous system (CNS) need to move through the blood-brain barrier (BBB). However, for drug molecules with a peripheral target, little to no BBB permeation may be needed to prevent side effects on the central nervous system .
The blood-brain barrier (BBB) permeation expresses the relative affinity of the drug for the blood or brain tissue. Table 5 indicates that 15 compounds are estimated to have no penetration of the blood-brain barrier, and thus, the chance of CNS side effects is expected to be absent. P glycoprotein (P-gp) plays a significant role in protecting the central nervous system from xenobiotics . The predicted outcome shows that only 9 of 26 compounds are P-gp substrates and do not cause phospholipidosis. The other 17 compounds on the other hand are non-substrates of P-gp and are therefore required to induce phospholipidosis on the phenyl ring. The cytochrome P450 (CYP) superfamily is critical in drug removal through metabolic biotransformation . The less skin permeant the molecule is, the lower the log Kp (in cm/s) is. It is found that log Kp measurements of all the compounds evaluated are within the limits (−8.0 to −1.0) except D-glucopyranoside, desulphosinigrin, and lactose .
3.5.3. Lipophilicity and Drug-Likeness
The result of Table 6 showed that the log P values of all the compounds except benzene dicarboxylic acid, methylnonadecane, phthalic acid, 1-heptatriacotanol, and cyclopropane tetradecanoic acid. The selected compounds were found to be within the limits, i.e., between 0.7 and + 5.0, indicating that they should have strong permeability and oral absorption. Drug-likeness qualitatively tests a molecule's likelihood of being an oral drug candidate for bioavailability .
3.5.4. Rule of Five by Lipinski
As per Lipinski's rule of five , the drug is likely to be produced as a prospective oral drug if the applicant violates none or less than one of the following four conditions. The Abbot bioavailability score (BAS) is a rule-based semi-quantitative score that relies on a total charge, TPSA, and the Lipinski filter violation that distinguishes four compound groups. All of the selected molecules have a bioavailability score of 0.55, except for tetrazole, octadecadienoic acid, n-hexadecanoic acid, and lactose, indicating a chance of becoming the oral drug candidates .
In this investigation, 17 of 26 of the selected compounds did not pass ADME screening, leaving 9 candidate compounds for the molecular docking analysis (Table 6), thus demonstrating the potential usefulness of the series for drug-like compound growth.
3.5.5. Medicinal Chemistry
Pan-assay interference compounds or promiscuous compounds (PAINS) are substances with substructures that display a false reaction, irrespective of the protein receptor, with biologically potent output . Table 6 shows that all of the compounds return no PAINS alert. For all the candidates in the library, the synthetic accessibility (SA) scores were found to be less than 5 except for the 6 compounds that had scores more than 5, as shown in Table 6. The score of SA is normalized between 1 (easy synthesis) and 10 (very difficult synthesis). For most candidates in the library, the SA scores were found to be less than 5 and thus have strong synthesis feasibility.
The lead-like rule-based approach lets the medicinal chemist define the required molecule to start lead optimization. Interestingly, Table 6 shows that 10 compounds of 26 have one violation of lead-likeness, and these molecules are therefore considered appropriate for initiating lead optimization. Furthermore, as is evident from the radar depictions, 8 compounds with two violations are also found to meet the requirement for oral bioavailability.
3.5.6. Bioavailability Radar
The drug-likeness of a molecule can be quickly determined using the bioavailability radar. The pink-colored region is the required physiochemical space for oral bioavailability, and the molecule's radar plot must fall entirely into the field to be considered drug-like . The SwissADME prediction output revealed that 9 compounds had the optimal range of all six properties, which indicates that they have competent chemotherapeutic potential (Figure 2).
3.5.7. Molecular Docking
The molecular docking technique is used to calculate ligand-binding affinities and energies, which is essential in the structure-based drug design process. 3D protonation, energy minimization, and prediction of the active site for ligands were used to prepare the protein for molecular docking, with the parameters left at their defaults. Then, using GOLD version 5.3.0 software, ligands were docked with the target protein (5 kzw). In our study, 9 secondary metabolites from T. divaricata (Jasmine) flower were docked with α-glucosidase protein (5 kzw), which is the important protein for the key regulatory enzymes that are important in the diabetes management. To prevent sugar digestion and postprandial hyperglycemia, glucosidase, a digestive enzyme involved in carbohydrate digestion, must be inhibited. Table 7 contains a list of the compounds, which are downloaded from PubChem (https://pubchem.ncbi.nlm.nih.gov).
Following the selection of these nine compounds based on SwissADME findings, ChemDraw Ultra 12.0 and Chem3D Pro were used in GOLD docking for energy minimization of ligands. The coordinate crystal structure of the 5kzw protein was obtained from the Protein Data Bank and loaded into GOLD suite version 5.3.0 with a resolution of 0. GOLD 5.3.0 version was used to screen various docked complexes based on docking fitness and GOLD ratings. The GOLD program identified the most effective compound for interacting with the receptor of 2.70. The binding compatibility, i.e., docking score and fitness, was used to test the results. The best drug was selected with the highest binding affinity with the receptor molecule. As the ligand molecule, the number of hydrogen bonds formed and the bond distance between the active site and inhibited atomic coordinates were used to decide the final docked conformation for various chemicals. The GOLD docking scores for the phytochemicals are given in Table 8.
For each ligand, each docking routine returned the top ten rated docked poses. Compounds having maximum ligand-receptor binding energy and interactions with the receptor (<6 Å bond lengths) were predicted to be most effective. Cyclopropane tetradecanoic acid, 2-octyl-, methyl ester, 4-(4-methyl-2-biphenylyloxy) phthalonitrile showed the best interaction with α-glucosidase (PDB ID = 5kzw), and the protein having Gold fitness (39.28, 37.21) and GOLD docking score is -7.51and -6.53 including forming a hydrogen bond with LEU A: 777, ARG A: 779, ASN A: 780, THR A: 782, VAL A: 784, LEU A: 777, ARG A: 779, VAL A: 784, LEU A: 815, SER A: 848, TRP A: 849, CYS A: 850, and LEU A: 846, respectively. These molecules showed exceptionally good interaction with α-glucosidase protein. 1,6,10-dodecatriene, 7,11-dimethyl-3-methylene, 2-phenylthiolane, and cyclohexane propanoic acid, 3-oxo-, methyl ester showed moderate binding affinity (32.69, 29.14, and 28.29, respectively), and GOLD docking score is -4.03, 0.205, and 0.93, respectively, having the interaction of hydrogen bond with LEU A: 777, ARG A: 779, VAL A: 784, LEU A: 777, ARG A: 779, VAL A: 784, LEU A: 846, ARG A: 779, and VAL A: 784. Compounds (N-methylallylamine, propanamide, and cyclohexene, 3-ethenyl) had the least interaction in the range of 20.00, 19.16, and 23.83 with docking scores of -0.16, -0.59, and 0.14.1H-Tetrazol-5-amine compound showed least interactions with the range of fitness of 17.21 and docking score of 0.00.
2D view of protein-ligand interactions from the best poses produced by Discovery Studio showed that all molecules exhibited the same binding mode, as shown in Figure 3. ARG A: 779, LEU A: 777, and VAL A: 784 are three important interactions between these atoms and the residues.
Ethnobotanicals are widely used for the treatment of diabetic and oxidative stress-related conditions ; however, it still requires rigorous scientific validation. The amount of postprandial blood glucose is the key factor that must be controlled in T2D management . The drug intervention often has inexorable consequences, mostly hypoglycemia, gastrointestinal damage, and weight gain . Several studies have verified the antihyperglycemic properties of plant extracts and herbal formulations that could be used as antidiabetic tonics. Herbal medications are often thought to have fewer adverse side effects than prescription drugs .
The correlation was found between hypoglycemic events of medicinal plants to the presence of phenol and flavonoids . According to previous studies, flavonoids have an antidiabetic property and are a source of glucose uptake in tissue with relevance to oxidative stress during diabetic conditions . Antidiabetic activity is due to the co-adjuvant effect of bioactive compounds present in T. divaricata.
Plants have a phenolic compound that shows antioxidant activity to prevent tissue damage. Rauter et al.  reported phenolic content as antioxidants in selected Nigerian medicinal plants, such as A. platyneuron and B. nitida, in which the value of phenolic content ranged from 82.33 ± 0.30 to 11.67 ± 0.09 mg GAE/g, while Agbo et al.  reported that the phenolic content ranged from 97.77 ± 0.77 mg GAE/g. In our results, T. divaricate showed maximum phenolic content of 62.32 ± 4.02. Flavonoid is another parameter that is used for the determination of antioxidant activity in medicinal plants. In this study, the average range of flavonoid ranged from 13.95 ± 1.33 to 24.53 ± 0.61. Agbo et al.  reported flavonoid values in M. afzelii extract, i.e., 3.67 ± 0.00 mg QE/g, while Saeed et al.  reported the value of 59.6 ± 1.5 for methanolic plant extract of T. leptophylla.
Previous research has shown that diabetic beta cells produce reactive oxygen species (ROS), which are counteracted by the overexpression of antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), and peroxidase (POX). Antioxidants protect beta cells from oxidative damage by scavenging the free radicals produced, thus preventing diabetes from developing [27–29]. In transgenic mice, overexpression of SOD has been shown to prevent the development of diabetic complications. Since oxidative stress is linked to the development of diabetic complications and inflammation, this study aimed to assess Tabernaemontana divaricata's antioxidant activity.
Biological properties, such as the antioxidant property, are considered as an estimation of the nutritional and medicinal value of plants . The antioxidant activity of methanolic extract of T. divaricata flowers was estimated by DPPH assay. DPPH is a neutral, free radical that helps a stable molecule to tolerate an electron or hydrogen radical. The ability of natural antioxidants to reduce the DPPH free radical is assessed by a decrease in absorbance at 520 nm. In comparison with regular ascorbic acid, the extract showed strong scavenging activity. The lower the absorbance, the more the scavenging operation there was. As a result, the bioactive compounds in this plant can serve as antioxidants and aid in the treatment of a variety of diseases, including diabetes. Antioxidant properties of natural compounds are said to correlate with antidiabetic properties or vice versa. In this study, the given antioxidant activity of the T. divaricata flower extract could be connected to their good amount of TFC and TPC, which function as metal chelators, reduction agents, hydrogen donors, and singlet oxygen quenchers and free radical scavenger .
Toxicity is an important factor in the design of pharmaceutical drugs and an important starting point for hemolytic actions, providing principal knowledge on the interaction at the cellular level between biological entities and molecules. Hemolytic activity of any compound is a sign of common cytotoxicity towards normal healthy cells. In this research, MEAE exhibited 10% cytotoxicity toward human erythrocytes, as shown in Table 3. Such findings demonstrate that if medicinal formulations from this plant are used at low concentrations, parameters of the RBC membrane will not change. Reports on the toxic effects of A. esculentus are insufficient. A previous study conducted with aqueous and methanolic extracts of the A. esculentus fruit confirmed that there were no deaths up to a dose of 2000 mg/kg (p.o.) in Swiss mice (n = 6) for 7 days and no signs of toxicity , which may be one of the significant issues for considering it as an important vegetable for human use. Further research is essential on this medicinal edible plant in the context of drug development and discovery.
Dietary phenols and flavonoids, in accumulation to theirantioxidant effects, have been noticed to exert antihyperglycemic effects by binding to the transporters of glucose  and spirited digestive enzyme inhibition . The carbohydrate-digesting enzymes, α-glucosidase and α-amylase, digest dietary starch and produce glucose, resulting in surge of postprandial glucose. So, the inhibition of α-glucosidase and α-amylase activities is one of the primary approaches to managing hyperglycemic T2D patients.
T. divaricata has antidiabetic activity, according to alpha-amylase inhibitory tests. The percentage inhibitory activity of plant methanolic extract against alpha-amylase enzyme increased in a dose-dependent manner. The plant extract concentration of 50 g/ml showed a percentage inhibition of 28%, while 200 g/ml showed a percentage inhibition of 61%. At a high concentration of 200 g/ml, the extract inhibited the alpha-amylase enzyme by 50%. As a result of the current inhibitory studies, it has been discovered that the T. divaricata plant extract is successful in inhibiting the alpha-amylase enzyme, which helps to postpone the breakdown of starch into glucose and thus maintain glucose levels in diabetic patients. Dastjerdi et al.  observed α-amylase inhibition activity of some plant extracts of T. eucrium species values ranged from 41.59 ± 0.64 to 77.07 ± 0.49 at 1.56 mg/mL to 25 mg/mL. The α-amylase inhibitory activity of methanol plant extract is most likely by polar compounds that should be investigated further by isolating pure active compounds.
At 50–200 g/ml concentrations of T. divaricata extract, the percentage inhibition increased in a dose-dependent manner. For the highest and lowest concentrations, respectively, the percentage inhibition ranged from 60% to 31% (Table 4). Thus, by inhibiting the alpha-glucosidase enzyme, the extract of T. divaricata, which contains various natural bioactive compounds, helps to reduce the rate of carbohydrate digestion, lowering blood glucose levels and maintaining diabetic conditions.
Glucose uptake is one of the in vitro methods used to explore the antihyperglycemic effect of different compounds . The average values of glucose uptake by yeast cells in this study were 13.05 ± 1.3% to 69.5 ± 4.78%. Shehzadi et al.  reported the evaluation of antihyperglycemic activity through in vitro assays (0.2 to 26.3%) at 2 mg/mL, which was below the current research values. The results indicated all used concentrations under examination are capable of increasing the utilization and uptake of glucose in yeast cells.
The in silico prediction of molecular physicochemical parameters, bioavailability, and the pharmacokinetics have become more relevant for the investigation of productive potential drug molecules from a drug discovery standpoint . Theoretical experiments play a critical role in presenting accurate data in a timely and comfortable manner. Many free online platforms have recently been established for faster screening, reducing the time and expense of drug testing (no animal testing) . SwissADME is a modern comprehensive method developed by the Swiss Institute of Bioinformatics (SIB) that allows drug candidates to have their absorption, delivery, metabolism, and excretion (ADME) parameters estimated . At the outset of the drug development process, ADME properties, which determine either the potential drug's access to the target or its removal by the organism, are the required properties that must be evaluated for the drug to be selected. In silico experiments based on measured physicochemical requirements can be used to check these parameters. SwissADME also provides information on gastrointestinal absorption (GIA) and blood-brain barrier (BBB) permeability in humans. From twenty-six selected compounds, only eight compounds fulfilled the criteria of drug-likeness parameters. So, all of these nine compounds were further processed for molecular docking by GOLD.
To predict the affinity and behavior of small molecules and drug candidates, computational molecular docking is commonly used to predict the binding orientation to their protein targets . We used molecular docking to model various bioactive compounds isolated from the Jasmine plant that is known to inhibit glucosidase. Because of their low price and comparatively greater protection, with a low frequency of severe gastrointestinal side effects, plants or plant-based substances may be a suitable source of glucosidase inhibitors . Hydrogen bonds play a crucial role in the structure and interaction of protein-protein or ligand-receptor complexes. Hydrogen bonds are important in drug design to ensure that the drug is unique to the protein target. To back up the findings of this research, a molecular docking study was performed (cyclopropane tetradecanoic acid, 2-octyl-, methyl ester, 4-(4-methyl-2-biphenylyloxy) phthalonitrile), which showed excellent interaction with 5kzw protein having Gold fitness (39.28, 37.21) and GOLD docking score of -7.51 and -6.53 including the formation of hydrogen bond with amino acids residues (1,6,10-dodecatriene, 7,11-dimethyl-3-methylene, 2-phenylthiolane, and cyclohexane propanoic acid, 3-oxo-, methyl ester). These molecules showed exceptionally good interaction with α-glucosidase protein and can be considered as potential molecules that may prove to be beneficial in antiviral activity through their direct action on new castle disease . These compounds showed moderate binding affinity of 32.69, 29.14, and 28.29 and GOLD docking scores of -4.03, 0.205, and 0.93, respectively. N-methylallylamine, propanamide, cyclohexene, and 3-ethenyl have the least interaction in the range of 20.00, 19.16, and 23.83 and docking scores of -0.16, -0.59, and 0.14, while 1H-tetrazol-5-amine compound showed the least affinity towards 5kzw binding site.
Since diabetes mellitus is a global epidemic, effective drugs with less or no toxicity must be developed and one such way is the use of herbal medicines having no side effects. This study investigated the antidiabetic and antioxidant properties of T. divaricata extract and found promising inhibitors of two carbohydrate-related enzymes. T. divaricata has rich phenolic and flavonoid contents. As a flavonoid, it has great antidiabetic potential and also causes active uptake of glucose. The methanolic extract of T. divaricate has great potential for stimulation of α-amylase and α-glucosidase, so that it can be used to treat diabetes. In silico docking studies of phytoactive compounds from T. divaricata have been proven to have potential drug capabilities in terms of their pharmacokinetic and drug-likeness. The molecular docking analysis described some compounds that inhibited the targets related to diabetes mellitus and showed encouraging results with prominent inhibitory activity. This study shows that T. divaricata extract, which is rich in important bioactive compounds, can be used for diabetes. It is suggested to carry out long-term research work to recognize and isolate the active moieties responsible for antidiabetic property and to understand the mechanisms involved in glucose-lowering properties of the plant.
Data are available from authors on reasonable demand.
Conflicts of Interest
The authors declare that there are no conflicts of interest regarding the publication of this study.
The facilities and support provided by the Department of Zoology, Government College University Faisalabad, are highly acknowledged.
C. D. Deshmukh and A. Jain, “Diabetes mellitus: a review,” International Journal of Pure and Applied Biosciences, vol. 3, pp. 224–230, 2015.View at: Google Scholar
American Diabetes Association (ADA), “5. Lifestyle management: Standards of medical care in diabetes—2019,” Diabetes Care, vol. 42, no. 1, pp. S46–S60, 2019.View at: Publisher Site | Google Scholar
A. Meeinta, C. Rojwipaporn, R. Chanaporn et al., “Diabetes mellitus HbA1c and lung function do they are related,” Diabetes & its Complications, vol. 2, no. 3, pp. 1–6, 2018.View at: Publisher Site | Google Scholar
U. Yoon, L. L. Kwok, and A. Magkidis, “Efficacy of lifestyle interventions in reducing diabetes incidence in patients with impaired glucose tolerance, a systematic review of randomized controlled trials,” BMC Proceedings, vol. 6, pp. P28–P14, 2012.View at: Publisher Site | Google Scholar
S. B. Aynalem and A. J. Zeleke, “Prevalence of diabetes mellitus and its risk factors among individuals aged 15 years and above in Mizan-Aman town, a cross sectional study,” International Journal of Endocrinology, vol. 2018, Article ID 9317987, 7 pages, 2018.View at: Publisher Site | Google Scholar
D. R. Whiting, L. Guariguata, C. Weil, and J. Shaw, “IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030,” Diabetes Research and Clinical Practice, vol. 94, pp. 311–321, 2011.View at: Publisher Site | Google Scholar
P. Agarwal and R. Gupta, “Alpha-amylase inhibition can treat diabetes mellitus,” Research Review Journal of Medical Health Science, vol. 5, pp. 1–8, 2016.View at: Google Scholar
H. Kaneto, N. Katakami, M. Matsuhisa, and T. A. Matsuoka, “Role of reactive oxygen species in the progression of type 2 diabetes and atherosclerosis,” Mediators of Inflammation, vol. 2010, Article ID 453892, 11 pages, 2010.View at: Publisher Site | Google Scholar
Z. Sun and R. Albert, “Boolean models of cellular signaling networks,” Handbook of Systems Biology, Elsevier, Amsterdam, Netherlands, 2013.View at: Google Scholar
M. Nazıroğlu, “New molecular mechanisms on the activation of TRPM2 channels by oxidative stress and ADP-ribose,” Neurochemical Research, vol. 32, pp. 1990–2001, 2007.View at: Publisher Site | Google Scholar
R. Dringen, “Oxidative and antioxidative potential of brain microglial cells,” Antioxidants and Redox Signaling, vol. 7, pp. 1223–1233, 2005.View at: Publisher Site | Google Scholar
T. Zahidi, A. Lekchiri, T. Zahidi, W. Lekchiri, and A. Berrichia, “Extraction and comparison of two new peroxidases from leaves and roots of Brassica oleraceae var ramose,” Journal of Materials and Environmental Science, vol. 9, pp. 1398–1404, 2018.View at: Google Scholar
D. M. Kasote, S. S. Katyare, M. V. Hegde, and H. Bae, “Significance of antioxidant potential of plants and its relevance to therapeutic applications,” International Journal of Biological Sciences, vol. 11, pp. 982–991, 2015.View at: Publisher Site | Google Scholar
W. Kooti, M. Farokhipour, Z. Asadzadeh, D. Ashtary-Larky, and M. Asadi-Samani, “The role of medicinal plants in the treatment of diabetes, a systematic review,” Electronic Physician, vol. 8, no. 1, pp. 1832–1842, 2016.View at: Publisher Site | Google Scholar
M. S. Aslam and M. S. Ahmad, “Worldwide importance of medicinal plants, current and historical perspectives,” Recent Advances in Biology and Medicine, vol. 02, p. 88, 2016.View at: Publisher Site | Google Scholar
S. Ponnusamy, R. Ravindran, S. Zinjarde, S. Bhargava, and A. R. Kumar, “Evaluation of traditional Indian antidiabetic medicinal plants for human pancreatic amylase inhibitory effect in vitro,” Evidence-Based Complementary and Alternative Medicine, vol. 2011, Article ID 515647, 10 pages, 2011.View at: Publisher Site | Google Scholar
P. P. Bijeshmon and S. George, “Antimicrobial activity and powder microscopy of the flowers of Tabernaemontana divaricata R,” BR,” Indo American Journal of Pharmaceutical Research, vol. 4, pp. 1601–1605, 2014.View at: Google Scholar
V. L. Singleton, R. Orthofer, and R. M. Lamuela-Raventós, “Analysis of total phenols and other oxidation substrates and antioxidants by means of folin-ciocalteu reagent,” Methods in Enzymology, vol. 299, pp. 152–178, 1999.View at: Publisher Site | Google Scholar
J. Bao, Y. Cai, M. Sun, G. Wang, and H. Corke, “Anthocyanins, flavonols, and free radical scavenging activity of Chinese bayberry (Myrica rubra) extracts and their color properties and stability,” Journal of Agricultural and Food Chemistry, vol. 53, pp. 2327–2332, 2005.View at: Publisher Site | Google Scholar
M. Mohebbi-Fani, A. Mirzaei, S. Nazifi, and M. R. Tabandeh, “Oxidative status and antioxidant enzyme activities in erythrocytes from breeding and pregnant ewes grazing natural pastures in dry season,” Revue de Medecine Veterinaire, vol. 163, pp. 454–460, 2012.View at: Google Scholar
G. H. Onsa, N. bin Saari, J. Selamat, and J. Bakar, “Purification and characterization of membrane-bound peroxidases from Metroxylon sagu,” Food Chemistry, vol. 85, no. 3, pp. 365–376, 2004.View at: Publisher Site | Google Scholar
M. Kumar, A. J. Bijo, R. S. Baghel, C. Reddy, and B. Jha, “Selenium and spermine alleviate cadmium induced toxicity in the red seaweed Gracilaria dura by regulating antioxidants and DNA methylation,” Plant Physiology and Biochemistry, vol. 51, pp. 129–138, 2012.View at: Publisher Site | Google Scholar
W. A. Powell, C. M. Catranis, and C. A. Maynard, “Design of self-processing antimicrobial peptides for plant protection,” Letters in Applied Microbiology, vol. 31, pp. 163–168, 2000.View at: Publisher Site | Google Scholar
L. J. Shai, P. Masoko, M. P. Mokgotho et al., “Yeast alpha glucosidase inhibitory and antioxidant activities of six medicinal plants collected in Phalaborwa, South Africa,” South African Journal of Botany, vol. 76, pp. 465–470, 2010.View at: Publisher Site | Google Scholar
A. O. Ademiluyi and G. Oboh, “Soybean phenolic-rich extracts inhibit key-enzymes linked to type 2 diabetes (α-amylase and α-glucosidase) and hypertension (angiotensin I converting enzyme) in vitro,” Experimental & Toxicologic Pathology, vol. 65, pp. 305–309, 2013.View at: Publisher Site | Google Scholar
V. P. Cirillo, “Mechanism of glucose transport across the yeast cell membrane,” Journal of Bacteriology, vol. 84, pp. 485–491, 1962.View at: Publisher Site | Google Scholar
C. Kalaimagal, “Identification of bioactive compounds in flower of Tabernaemontana divaricata (l.) using gas chromatography–mass spectrometry analysis,” Asian Journal of Pharmaceutical and Clinical Research, vol. 12, pp. 129–132, 2019.View at: Publisher Site | Google Scholar
H. H. Rassem, A. Hamid Nour, and R. Mohamed Yunus, “Analysis of bioactive compounds for Jasmine flower via Gas chromatography-mass spectrometry (GC-MS),” Malaysian Journal of Fundamental and Applied Sciences, vol. 14, no. 2, pp. 198–201, 2018.View at: Publisher Site | Google Scholar
M. S. Ali Khan, A. M. Mat Jais, and A. Afreen, “Analogous and antioxidant activity mediated gastroprotective action of Tabernaemontana divaricata (L) R. Br. flower methanolic extract against chemically induced gastric ulcers in rats,” BioMed Research International, vol. 2013, Article ID 185476, 18 pages, 2013.View at: Publisher Site | Google Scholar
D. F. Veber, S. R. Johnson, H. Y. Cheng, B. R. Smith, K. W. Ward, and K. D. Kopple, “Molecular properties that influence the oral bioavailability of drug candidates,” Journal of Medicinal Chemistry, vol. 45, no. 12, pp. 2615–2623, 2002.View at: Publisher Site | Google Scholar
C. A. Lipinski, A. Lombardo, B. W. Dominy, F. Dominy, and P. J. Feeney, “Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings,” Advanced Drug Delivery Reviews, vol. 46, pp. 3–26, 2001.View at: Publisher Site | Google Scholar
A. K. Ghose, V. N. Viswanadhan, and J. J. Wendoloski, “A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery 1 A qualitative and quantitative characterization of known drug databases,” Journal of Combinatorial Chemistry, vol. 1, pp. 55–68, 1999.View at: Publisher Site | Google Scholar
Z. Bikadi and E. Hazai, “Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock,” Journal of Cheminformatics, vol. 1, p. 15, 2009.View at: Publisher Site | Google Scholar
S. S. Azam, A. Saroosh, N. Zaman, and S. Raza, “Role of N-acetylserotonin O-methyltransferase in bipolar disorders and its dynamics,” Journal of Molecular Liquids, vol. 182, pp. 25–31, 2013.View at: Publisher Site | Google Scholar
O. Trott and A. J. Olson, “AutoDock/Vina, improving the speed and accuracy of docking with a new scoring function, efficient optimization and multi-threading,” Journal of Computational Chemistry, vol. 31, pp. 455–461, 2010.View at: Publisher Site | Google Scholar
G. M. Morris, D. S. Goodsell, R. S. Halliday et al., “Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function,” Journal of Computational Chemistry, vol. 19, no. 14, pp. 1639–1662, 1998.View at: Publisher Site | Google Scholar
T. A. Halgren, “Characterization of MMFF94, MMFF94s, and other widely available force fields for conformational energies and for intermolecular-interaction energies and geometries,” Journal of Computational Chemistry, vol. 20, 1999.View at: Google Scholar
C. Y. Chung, H. Y. Chung, W. T. Sung et al., “Molecular docking for protein folding structure and drug-likeness prediction, WSEAS conference,” International Journal of Biology and Biomedicine, vol. 1, pp. 57–63, 2005.View at: Google Scholar
G. Li, H. Zhou, Y. Jiang et al., “Design and synthesis of 4-arylpiperidinyl amide and N-arylpiperdin-3-yl-cyclopropane carboxamide derivatives as novel melatonin receptor ligands,” Bioorganic & Medicinal Chemistry Letters, vol. 21, no. 4, pp. 1236–1242, 2011.View at: Publisher Site | Google Scholar
F. J. Solis and R. J. B. Wets, “Minimization by random search techniques,” Mathematics of Operations Research, vol. 6, no. 1, pp. 19–30, 1981.View at: Publisher Site | Google Scholar
I. A. Alswaidan, K. Sooknah, L. Rhyman et al., “2, 4-Ditellurouracil and its 5-fluoro derivative Theoretical investigations of structural energetics and ADME parameters,” Computational Biology and Chemistry, vol. 68, pp. 56–63, 2017.View at: Publisher Site | Google Scholar
M. F. Fromm, “P-glycoprotein a defense mechanism limiting oral bioavailability and CNS accumulation of drugs,” International Journal of Clinical Pharmacology & Therapeutics, vol. 38, no. 2, pp. 69–74, 2000.View at: Publisher Site | Google Scholar
G. Szakacs, A. Váradi, C. Ozvegy Laczka, and B. Sarkadi, “The role of ABC transporters in drug absorption distribution metabolism excretion and toxicity (ADME-Tox),” Drug Discovery Today, vol. 13, no. 9-10, pp. 379–393, 2008.View at: Publisher Site | Google Scholar
B. Testa and S. D. Kraemer, “The biochemistry of drug metabolism an introduction part 2 Redox reactions and their enzymes,” ChemInform, vol. 38, no. 23, pp. 257–405, 2007.View at: Publisher Site | Google Scholar
S. Meeran, V. Baskar, S. Syed Tajudeen, and T. K. Shabeer, “Design ADME profiling and molecular docking simulation of new isoniazid schiff base analogs as MtKasB Inhibitors,” Asian Journal of Chemistry and Pharmaceutical Science, vol. 6, pp. 20–34, 2018.View at: Google Scholar
J. B. Baell and G. A. Holloway, “New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays,” Journal of Medicinal Chemistry, vol. 53, no. 7, pp. 2719–2740, 2010.View at: Publisher Site | Google Scholar
T. J. Ritchie, P. Ertl, and R. Lewis, “The graphical representation of ADME-related molecule properties for medicinal chemists,” Drug Discovery Today, vol. 16, no. 1-2, pp. 65–72, 2011.View at: Publisher Site | Google Scholar
Z. M. Dastjerdi, F. Namjoyan, and M. E. Azemi, “Alpha amylase inhibition activity of some plants extract of Teucrium species,” European Journal of Biological Sciences, vol. 7, pp. 26–31, 2015.View at: Google Scholar
I. M. E. Lacroix and E. C. Y. Li-Chan, “Overview of food products and dietary constituents with antidiabetic properties and their putative mechanisms of action: a natural approach to complement pharmacotherapy in the management of diabetes,” Molecular Nutrition & Food Research, vol. 58, no. 1, pp. 61–78, 2014.View at: Publisher Site | Google Scholar
H. V. Rupasinghe, S. Sekhon-Loodu, T. Mantso, and M. I. Panayiotidis, “Phytochemicals in regulating fatty acid β-oxidation Potential underlying mechanisms and their involvement in obesity and weight loss,” Pharmacology & Therapeutics, vol. 165, pp. 153–163, 2016.View at: Publisher Site | Google Scholar
M. Qasim, Z. Abideen, M. Y. Adnan et al., “Antioxidant properties, phenolic composition, bioactive compounds and nutritive value of medicinal halophytes commonly used as herbal teas,” South African Journal of Botany, vol. 110, pp. 240–250, 2017.View at: Publisher Site | Google Scholar
B. Romano, E. Pagano, V. Montanaro, A. L. Fortunato, N. Milic, and F. Borrelli, “Novel insights into the pharmacology of flavonoids,” Phytotherapy Research, vol. 27, pp. 1588–1596, 2013.View at: Publisher Site | Google Scholar
A. P. Rauter, A. Martins, C. Borges et al., “Antihyperglycaemic and protective effects of flavonoids on streptozotocin–induced diabetic rats,” Phytotherapy Research, vol. 24, pp. S133–S138, 2010.View at: Publisher Site | Google Scholar
M. O. Agbo, P. F. Uzor, U. N. Nneji, C. U. Odurukwe, U. B. Ogbatue, and E. C. Mbaoji, “Antioxidant, total phenolic and flavonoid content of selected Nigerian medicinal plants,” Dhaka University Journal of Pharmaceutical Science, vol. 14, pp. 35–41, 2015.View at: Publisher Site | Google Scholar
N. Saeed, M. R. Khan, and M. Shabbir, “Antioxidant activity, total phenolic and total flavonoid contents of whole plant extracts Torilis leptophylla L,” BMC Complementary and Alternative Medicine, vol. 12, no. 1, p. 221, 2012.View at: Publisher Site | Google Scholar
M. R. Kumbhare, V. Guleha, and T. Sivakumar, “Estimation of total phenolic content, cytotoxicity and in–vitro antioxidant activity of stem bark of Moringa oleifera,” Asian Pacific Journal of Tropical Disease, vol. 2, pp. 144–150, 2012.View at: Publisher Site | Google Scholar
A. A. Ala, B. B. Olotu, and C. M. D. Ohia, “Assessment of cytotoxicity of leaf extracts of andrographis paniculata and aspilia Africana on murine cells,” Archives of basic and applied medicine, vol. 6, pp. 61–65, 2018.View at: Google Scholar
S. K. Doreddula, S. R. Bonam, D. P. Gaddam, B. S. R. Desu, N. Ramarao, and V. Pandy, “Phytochemical analysis antioxidant antistress and nootropic activities of aqueous and methanolic seed extracts of ladies finger (Abelmoschus esculentus L.) in mice,” The Scientific World Journal, vol. 2014, Article ID 519848, 14 pages, 2014.View at: Publisher Site | Google Scholar
L. A. Nistor Baldea, L. C. Martineau, A. Benhaddou-Andaloussi, J. T. Arnason, E. Lévy, and P. S. Haddad, “Inhibition of intestinal glucose absorption by anti-diabetic medicinal plants derived from the James Bay Cree traditional pharmacopeia,” Journal of Ethnopharmacology, vol. 132, no. 2, pp. 473–482, 2010.View at: Publisher Site | Google Scholar
N. Shehzadi, K. Hussain, N. I. Bukhari et al., “Hypoglycemic, hepatoprotective and molecular docking studies of 5-[(4-chlorophenoxy) methyl]-1, 3, 4- oxadiazole-2-thiol,” Bangladesh Journal of Pharmacology, vol. 13, no. 2, pp. 149–156, 2018.View at: Publisher Site | Google Scholar
D. Seeliger, B. L. de Groot, and V. De Pymol, “Ligand docking and binding site analysis with PyMOL and Autodock/Vina,” Journal of Computer-Aided Molecular Design, vol. 24, pp. 417–422, 2010.View at: Publisher Site | Google Scholar
W. Benalla, S. Bellahcen, and M. Bnouham, “Antidiabetic medicinal plants as a source of alpha glucosidase inhibitors,” Current Diabetes Reviews, vol. 6, no. 4, pp. 247–254, 2010.View at: Publisher Site | Google Scholar
R. Andleeb, M. U. Ijaz, A. Rafique et al., “Biological activities of methanolic extract of aegle marmelos against HN protein of newcastle disease virus,” Agronomy, vol. 11, no. 9, p. 1784, 2021.View at: Google Scholar