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 Table of Contents  
Year : 2022  |  Volume : 10  |  Issue : 4  |  Page : 105-115

In vitro analysis and molecular docking of gas chromatography-mass spectroscopy fingerprints of polyherbal mixture reveals significant antidiabetic miture

1 Department of Biochemistry, Toxicology and Therapeutics, Faculty of Basic Medical Sciences, College of Medicine, University of Lagos, Lagos, Nigeria
2 Department of Chemical Sciences, Biochemistry Unit, College of Natural and Applied Sciences, Fountain University, Osogbo, Osun State, Nigeria
3 Department of Biochemistry, Computational Biology/Drug Discovery Laboratory, Ladoke Akintola University of Technology; Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
4 Department of Biochemistry, Computational Biology/Drug Discovery Laboratory, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
5 Department of Human Physiology, Baze University, Abuja, Nigeria
6 Department of Pharmacology, Toxicology and Therapeutics, Faculty of Basic Medical Sciences, College of Medicine, University of Lagos, Lagos, Nigeria

Date of Submission22-Oct-2022
Date of Decision14-Dec-2022
Date of Acceptance08-Jan-2023
Date of Web Publication22-Feb-2023

Correspondence Address:
Dr. Musa Oladayo Babalola
Department of Biochemistry, Faculty of Basic Medical Sciences, College of Medicine, University of Lagos, Lagos
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/njecp.njecp_15_22

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Background: One of the treatment goals for type II diabetes is to keep blood sugar to normal and inhibition of carbohydrate metabolizing enzymes represents a therapeutic strategy to achieve this aim. While medicinal plants possess a useful resource for therapeutics, combining plants of different species is believed to have a better pharmacological effect. Aim and Objectives: This study reported the antidiabetic potential, in-vitro and in-silico, of a polyherbal mixture which is a combined ethanol extract of Vernonia amygdalina, Allium sativum, and Ocimum gratissimum (which are plants native to tropical Africa). Materials and Methods: The study identified and quantified the phytochemicals present in the extract, its antioxidant and antidiabetic potentials were investigated. Also, the bioactive compounds present in the mixture were profiled with gas chromatography-mass spectroscopy (GC-MS). The resulting compounds were screened for their binding potential into the active site of alpha-glucosidase using consensus scoring molecular docking strategy. Results: The polyherbal mixture was abundant in phenols flavonoids and sterols. Apart from scavenging DPPH radicals, the extract also inhibited alpha-amylase and alpha-glucosidase with better IC50 values of 106.22μg/ml and 128.60μg/ml respectively than the reference drug, acarbose. Out of the bioactive compounds present in the mixture, stigmasterol, gamma-sitosterol, and tocopherol ranked top and are good binders of alpha-glucosidase. It was observed that these compounds possessed better ADMET and drug-like properties than standard acarbose. Conclusion: These features are indicative that the polyherbal mixture of Vernonia amygdalina, Allium sativum, and Ocimum gratissimum contain in part bioactive compounds that can be used for the management/treatment of type II diabetes.

Keywords: Allium sativum, consensus scoring, molecular docking, Ocimum gratissimum, sterols, Type II diabetes, Vernonia amygdalina

How to cite this article:
Babalola MO, Ashiru MA, Boyenle ID, Atanda EO, Oyedele AQK, Dimeji IY, Awodele O, Imaga NA. In vitro analysis and molecular docking of gas chromatography-mass spectroscopy fingerprints of polyherbal mixture reveals significant antidiabetic miture. Niger J Exp Clin Biosci 2022;10:105-15

How to cite this URL:
Babalola MO, Ashiru MA, Boyenle ID, Atanda EO, Oyedele AQK, Dimeji IY, Awodele O, Imaga NA. In vitro analysis and molecular docking of gas chromatography-mass spectroscopy fingerprints of polyherbal mixture reveals significant antidiabetic miture. Niger J Exp Clin Biosci [serial online] 2022 [cited 2023 May 29];10:105-15. Available from: https://www.njecbonline.org/text.asp?2022/10/4/105/370246

  Introduction Top

Recently, diabetes mellitus (DM) made it to the top 10 causes of death worldwide; it is now ranked 9th by the World Health Organization (WHO) with ischemic heart disease taking the lead. Although diabetes mellitus is of different classifications, Type I and Type II are the most common forms of this disease.[1],[2] While Type I is caused by autoimmune attack, Type II diabetes occurs due to failure of the pancreatic beta-cells to respond to fuel leaving the body with persistent hyperglycemia.[3],[4] Of these two forms, Type II is highly prevalent and it is associated with several microvascular and macrovascular complications.[5],[6] Diabetes itself cannot kill, its complications such as atherosclerosis, neuropathy and nephropathy are life-threatening and can cause death[7],[8],[9]. It is important to state that DM is not only associated with derangement in carbohydrate metabolism, lipid and protein metabolism are also affected.[10] One way by which persistent hyperglycemia causes the progression of diabetic complications is by disrupting the balance between oxidative stress and the antioxidant defense system of the body; this event leads to the activation of signaling cascade such as the advanced glycated end product (AGE/RAGE) pathway and the protein kinase C which further aggravate the situation.[11],[12],[13] A major campaign in diabetes drug discovery is lowering blood glucose and glycated hemoglobin. In principle, achieving this aim is believed to delay the progression of diabetes complications and increase the life span of the diabetics.[14]

Several glucose-lowering therapies exist and most of them owe their mechanism of action to protein targets such as peroxisome proliferator-activated receptor-γ, adenosine monophosphate protein kinase, sodium-glucose co-transporter-2, glucagon-like peptide, and others.[3],[15] Most of the drugs that mediate blood glucose through these targets tend to clear postprandial glucose accumulation; however, they have side effects on cardiac function. A strategic way to control the amount of glucose entering the bloodstream is by inhibiting alpha-glucosidase. The inhibition of alpha-glucosidase has long been a pursuit in diabetic therapeutics, drugs such as acarbose and miglitol depend on this protein. The problem that is widely associated with conventional drugs after the high price is side effects,[16],[17] hence suggesting a need for alternative therapies that is affordable with little or no side effects.

The WHO has recommended the use of herbal products for the treatment of human maladies.[18] Medicinal plants and their extracts have recently shown better therapeutic option toward lowering blood glucose in diabetic patients, which can be credited to the bioactive compounds they possess.[19] Combining plants of different species to form a polyherbal mixture or a formulation is intended to yield more therapeutic response through a synergistic mechanism of the arrays of active ingredients present.[20],[21] Furthermore, plant formulations formed from different plant parts have been proven to have better antidiabetic potential.[22] A recent clinical trial study on Iranian diabetic patients revealed a formulation formed from Silybum marianum seeds, Urtica dioica leaves, and Boswellia serrata leaves to have profound antihyperglycemic potential.[23] A polyherbal formulation that has Allium sativum (AS) as its constituent was found to lower blood glucose and serum patients in an open-label Phase I trial.[24]

We evaluated the antidiabetic potentials of the leaf part of Ocimum gratissimum (OG), Vernonia amygdalina (VA), and AS bulb. These medicinal plants have been reported to have glucose-lowering effects by different authors. VA leaves stimulated glucose uptake ex vivo;[25] other properties such as hypoglycemic, hypolipidemic, and antioxidant potential have been attributed to this plant.[10] OG, which belongs to the Lamiaceae family, reduced lipid profile and regulated blood glucose in streptozotocin-induced diabetic rats.[26] Allium sativum, popularly known as garlic has a hypoglycemic effect on its own, it's hypoglycemic effect is felt better when it is combined with an antidiabetic drug.[27],[28],[29] There is, however, no information on the possible synergistic antidiabetic effect of the combination of these three plants. We, therefore, seek to investigate the antidiabetic potentials of the polyherbal combination of these three plants in vitro and in silico which include inhibition of α-amylase, α-glucosidase, and molecular docking of its gas chromatography–mass spectroscopy (GC-MS) fingerprints for consensus scoring, pharmacokinetics, and drug-likeness.

  Materials and Methods Top

Experimental methodologies

Plant source

Fresh plant materials VA (bitter leaf), OG (scent leaf), and AS (garlic bulbs) were obtained from the traditional medicine materials market situated in Oyingbo Market, Lagos, Nigeria. The leaves and garlic bulbs were identified and authenticated by Dr. Nodza George at the Department of Botany, Faculty of Science of the University of Lagos. Samples of the plants (bulb and leaves) were deposited in the herbarium of the Institution with the voucher numbers LUH/8101, LUH/8102, and LUH/8103, respectively.


The bitter leaf, garlic bulbs, and scent leaf obtained were air-dried at room temperature in the laboratory for 2–4 weeks. The dried plant materials were individually milled into powder. An equal proportion (350 g) of the grounded plant materials were weighed and mixed. The resulting mixture was macerated in 5 L of 96% ethanol (with mixtures vigorously stirred every 24 h). After 72 h, the mixture was decanted and the supernatant was filtered using Whatman filter paper No. 1 and concentrated using a rotary evaporator. The residual solvent in the extract was dried in an oven (Gallenkamp, England) at 40°C. The extract was placed in sterile sample bottles and stored in a refrigerator for future use.

Phytochemical analysis

Phytochemicals present in the extract were identified and quantified using the modified method of Asuquo and Udobi.[30]

DPPH (1,1-diphenyl-2-picrylhydrazyl) scavenging activity

The free radical scavenging capacity of the extracts was determined using a modified method of Hassan et al.,[31] Freshly prepared DPPH methanol solution (0.004 % w/v) was taken in test tubes and the extract (0.1 mL) was added. The absorbance was read at 517 nm using a spectrophotometer (HACH 4000 DU UV – visible spectrophotometer) after 30 min. Ascorbic acid was used as a reference. Serial dilutions (25, 50, 75 and 100 μg/ml) were done to obtain an inhibition curve. Control (same volume without extract or standard) was also prepared. Ninety five percent methanol served as blank. Ability of DPPH to scavenge free radical was measured by using the following equation:

where A0 was the absorbance of the control and A1 was the absorbance in the presence of the standard sample or extract. The IC50 value represented the concentration of the compounds that caused 50% inhibition of DPPH radical formation.

Reducing power activity

The reducing power of the extract was determined according to the methods of Oyaizu.[32] Different concentrations of the extract (25 – 100 μg/ml in 1 ml of distilled water) were mixed with phosphate buffer (2.5 ml, 0.2 M, pH 6.6) and potassium ferricyanide [K3Fe (CN)6] (2.5 ml, 1%). The mixture was incubated at 50 °C for 20 min. A portion (2.5 ml) of trichloroacetic acid (10%) was added to the mixture, which was then centrifuged at 3000 rpm for 10 min. The upper layer of the solution (2.5 ml) was mixed with distilled water (2.5 ml) and FeCl3 (0.5 ml. 0.1%) and the absorbance was measured at 700 nm. Increased absorbance of the reaction mixture indicated increased reducing power. Ascorbic acid was used as the standard. Phosphate buffer (pH 6.6) was used as blank solution. The absorbance of the final reaction mixture of two parallel experiments was taken and is expressed as mean ± standard deviation.

Alpha amylase inhibition assay

The starch solution (0.5% w/v) was obtained by stirring and boiling, 0.25 g of soluble potato starch in 50 ml of deionized water for 15 min. The enzyme solution (0.5 units/ml) was prepared by mixing 0.001 g of α-amylase (EC in 100 ml of 20 mM sodium phosphate buffer (pH 6.9) containing 6.7 mM sodium chloride. The extracts and/or fractions were dissolved in DMSO to give suitable concentrations for the assay. The color reagent was a solution containing 96 mM 3,5-dinitrosalicylic acid (20 ml), 5.31 M sodium potassium tartrate in 2 M sodium hydroxide (8 ml), and deionized water (12 ml). One milliliter of the mixture and 1 ml of the enzyme solution were mixed in a test tube and incubated at 25°C for 30 min. An aliquot of 1 ml was taken, then, 1 ml of starch solution was added to it and it was further incubated for 3 min. Then, 1 ml of the color reagent was added and the stoppered tube was placed into an 85°C water bath. After 15 min, the reaction mixture was removed from the water bath and cooled thereafter, diluted with 9 ml distilled water, and the absorbance value was determined at 540 nm using Shimadzu MultiSpec-1501 spectrophotometer.

Individual blanks were prepared for correcting the background absorbance, in this case, the color reagent solution was added before the addition of starch solution, and then, the tube was placed into the water bath. Then, the method was followed as described above. Controls were conducted identically, replacing extracts and/or fractions with 1 ml DMSO. Acarbose solution with a concentration ranging from 50 to 500 μg/mL was used as the positive control. The inhibition percentage of alpha-amylase was calculated with the formula.

Alpha-glucosidase inhibition

Alpha-glucosidase inhibition assay was used as one of the methods to evaluate the antidiabetic potential of this polyherbal mixture, the methodology was in tandem with the one prescribed by Dahlqvist[33] but with slight modification. Briefly, 1 g of rat intestinal acetone powder was mixed with 10 mL sodium phosphate buffer (pH 7, 0.1 M) and was sonicated for 30 s (12 times) with an interval of 15 s to prevent the accumulation of heat. After which the mixture was subjected to centrifugation at 10,000 g at 4°C for 10 min, the resulting supernatant obtained was labeled as rat intestinal alpha-glucosidase. The enzyme inhibition was determined by incubating the solution of the labeled enzyme (20 μL), phosphate buffer (100 μL, 0.1 M) at pH 7.0, maltase solution (37 nM), and the solutions of the extract of the plant mixture at varying concentrations of 50–500 μg/mL at 37°C for 30 min. Acarbose was used at various concentrations as the extract and was used as a reference standard for the study because of its well-documented alpha-glucosidase inhibitor. The mixture was placed in boiling water for 5 min to terminate the reaction. The amount of glucose released was determined using the glucose-oxidase method of Meites et al.[34] Alpha-glucosidase inhibition (A) was calculated using equation II below.

Gas chromatography–mass spectroscopy analysis

The GC-MS analysis of the polyherbal mixture was done using the method described by Hadi et al. and Mohammed et al.[35],[36] with slight modification. About 1 μl of the ethanol extract was injected into the GC-MS using a micro syringe and the scanning was done for 45 min. As the compounds were separated, they eluted from the column and entered a detector which was capable of creating an electronic signal whenever a compound was detected. The greater the concentration in the sample, the bigger the signal obtained which was then processed by a computer. The time from when the injection was made (initial time) to when elution occurred is referred to as the retention time (RT). While the instrument was run, the computer generated a graph from the signal called chromatogram. Each of the peaks in the chromatogram represented the signal created when a compound was eluted from the GC column into the detector. The X-axis showed the RT and the Y- axis measured the intensity of the signal to quantify the component in the sample injected. As individual compounds were eluted from the gas chromatographic column, they entered the electron ionization (MS) detector, where they were bombarded with a stream of electrons causing them to break apart into fragments. The fragments obtained were actually charged ions with a certain mass. The mass/charge (M/Z) ratio obtained is the fingerprint of a molecule. Before analyzing the extract using GC-MS, the temperature of the oven, the flow rate of the gas used, and the electron gun were programmed initially. The temperature of the oven was maintained at 100°C. Helium gas was used as a carrier as well as an eluent. The flow rate of helium was set at 1 ml/min. The electron gun of mass detector liberated electrons having energy of about 70 eV. The column employed here for the separation of components was Elite 1 (100% dimethyl polysiloxane). The identity of the components in the extracts was assigned by the comparison of their retention indices and mass spectral fragmentation patterns with those in the device library and also with published literatures. Compounds were identified by comparing their spectra to those of the Wiley and NIST/EPA/NIH mass spectral libraries.

Computational methodologies

Preparation and active site identification of α-glucosidase and molecular docking protocol

Alpha-glucosidase protein three-dimensional (3D) information obtained from the PDB (ID: 2QMJ) was used as the target protein for this study. The structure was treated accordingly using BIOVIA discovery studio software version 19.1 (http://www.accelrys.com) to prevent unbidden molecular interactions during virtual screening. The active site of the protein was detected using Computed  Atlas More Details for Surface Topology of Proteins webserver platform.[37] We docked into the active site of this protein with IGEMDOCK, PyRx, and Easydock Vina[38],[39],[40] using the methodology used in our previous studies.[41],[42]

Preparation of ligands

Bioactive compounds of the extract detected using GCMS were recruited from a public database: their SMILES format was obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/), an open chemistry database of compounds, substances, and biological assays.[43] This two-dimensional information was subsequently converted using the cactus online smile translator webserver https://cactus.nci.nih.gov/translate/to derive their 3D coordinates in PDB format.

Pharmacokinetics and drug-likeness prediction

The pharmacokinetic behavior, toxicological endpoint, and drug-likeness characters of these compounds were evaluated using the Molinspiration platform (https://www.molinspiration.com) and admetSAR web server (http://lmmd.ecust.edu.cn/admetsar2/), respectively.

Consensus scoring

The 15 compounds obtained from GC-MS result of the polyherbal mixture were subjected to molecular docking studies using three software with different algorithmic profile. The software include SAMSON, PyRx, and iGEM DOCK. The results obtained from these different softwares were compared and normalized and their values are ranked. The compounds that ranked high in the three softwares were termed hits. These hits were subjected to further computational analyses.

  Result and Discussion Top

Phytochemical analyses

Identification and quantification of the phytochemicals present in plant extract have a long record in phytomedicine. It is believed that the knowledge of the group of the phytochemical present in a plant will help identify plants that are rich in a particular phytochemical of interest and would also aid the discovery of new pharmacological agents and materials for medicine and industry, respectively.[44] [Table 1] shows that the extract of the polyherbal mixture of AS, OG, and VA to be rich in flavonoids, phenol, sterols, alkaloids, tannins, saponins, terpenoids, and phlobatannins. Meanwhile, the most abundant of all is phenol (178.45 ± 0.66 mg/dg) and flavonoid (162.21 ± 0.63 mg/dg) followed by sterols. The phytochemical screening investigation conducted on AS in the past depicted it to be rich in phenolics.[45],[46] While OG is rich in phenols, alkaloids, and saponins,[47] VA was quantitatively found to contain alkaloids, tannins, flavonoids, and saponins.[48],[49] Put together, the identified phytochemicals found in the polyherbal mixture of these plants must have been amassed from the individual plant phytochemical constituents. Interestingly, antidiabetic potential has been acclaimed to these constituents.[50]
Table 1: Qualitative and quantitative phytochemical screening of the polyherbal mixture

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In vitro inhibition of carbohydrate-metabolizing enzymes

The action of the polyherbal mixture on alpha-amylase and alpha-glucosidase is shown in [Figure 1]. It could be drawn from the graph that the inhibition of these enzymes by the extract is dose dependent. More specifically, the polyherbal mixture inhibited alpha-amylase activity with IC50 value of 106.22 ug/ml; the 50% inhibition obtained for its standard was 106.43 ug/ml. This implies that the extract is as potent as acarbose considering the relative activity of these values. On the other hand, the alpha-glucosidase activity for the extract to that of standard acarbose is 128.16 and 212.75 μg/ml, respectively, which suggests that the extract is powerful against the enzyme than standard acarbose. An interpretation for these results is that the ethanol extract of this polyherbal mixture is potent against carbohydrate-metabolizing enzymes which is an indication that this extract could be alternative glucose-lowering therapy for Type II DM. The inhibition of carbohydrate-metabolizing enzymes is believed to lower postprandial blood glucose.
Figure 1: Inhibition of carbohydrate-metabolizing enzymes

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In vitro antioxidant assay

DPPH radical scavenging activity

Medicinal plants have in addition to their properties, the ability to scavenge free radicals.[51] Screening for the antidiabetic potential of an extract should also proceed pari passu with antioxidant evaluation because oxidative stress is a major arsonist that contributes to the progression of diabetes and its downstream complications.[52] The ability of an extract to possess both antidiabetic and antioxidant properties will have a long-term effect in preventing the progression of DM. Thus, we investigated to what extent our extract can scavenge the DPPH radicals, and interestingly, we found the polyherbal mixture to scavenge free radicals in a dose-dependent manner [Figure 2]. The result of the extract shows maximum scavenging activity at 100 μg/ml (71.70) which is comparable to that of ascorbic acid (87.81) and IC50 values were found to be 0.072 and 0.087 mg/ml, respectively [Table 2]. DPPH radical scavenging activity assay is used to determine the reductive ability of an extract or compound as a free radical scavenger and to evaluate the antioxidant activities of plant extracts and foods.[53] While this antioxidant property is critical to the medicinal effect of this extract, it is logical to conclude that the antioxidant property possessed by this extract must have been due to the high phenolic content as reported above in the phytochemical screening section. Phenols can mop off radicals via different mechanisms but mostly through the hydroxyl group present in their ring structural scaffold.[54]
Figure 2: DPPH free radical scavenging activity of the ethanol extract of the polyherbal mixture

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Table 2: IC50 values of DPPH scavenging activity of the ethanol extract of the polyherbal mixture

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Reducing power activity

In principle, compounds that have reducing potential react with potassium ferricyanide (Fe3+) to form potassium ferrocyanide (Fe2+), which subsequently reacts with ferric chloride to form a ferric–ferrous complex that has an absorption maximum at 700 nm. The polyherbal mixture scavenged ferric ions with clear concentration dependencies [Figure 3]. This property could easily be linked to the abundance of phenolics observed in the extract and therefore falls in perspective with the work of Ali et al.[55] who studied the in vitro antioxidant activities of extracts of VA and OG leaves. It was found that OG had higher reducing power than VA at the concentrations studied, while Narendhirakannan and Rajeswari, 2010, studied the in vitro antioxidant properties of three varieties of AS extracts, and it was concluded that the higher content of polyphenol and flavonoids may be attributed to the antioxidant potential of garlic.[56] Their result is in agreement with the current study, and the antioxidant activity of phenolic compounds is mainly due to their redox properties, which can play an important role in absorbing and neutralizing free radicals, quenching singlet and triplet oxygen, or decomposing peroxides.[56]
Figure 3: Reducing power of the ethanol extract of the polyherbal mixture

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Gas chromatography–mass spectroscopy result analysis

GC in combination with MS has become an ideal technique for qualitative analysis of volatile and semi-volatile compounds.[57] The GC-MS analysis of combined ethanol extract of the polyherbal mixture revealed the presence of fourteen compounds (phytochemical constituents) which may be responsible for the bioactive property of this plant. The time-evolving spectrum is shown in [Figure 4], while other properties are shown in [Table 3]. The compounds were arranged based on the area peak percentage with the lowest at the top of the table Vitamin E (1.0659%) to the highest at the bottom of the table thymol (10.312). The compounds identified and their concentrations are similar to the findings of Igwe et al.[58] whose study revealed the presence of eleven compounds from ethanol leaf extract of VA.
Table 3: Major phytochemical compounds identified in the ethanol extract of the polyherbal mixture

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Figure 4: GC-MS chromatogram of the ethanol extract of the polyherbal mixture. GC-MS: Gas chromatography–mass spectroscopy

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Molecular modeling study

Bioactive compounds from the GC-MS fingerprint of the combined formulation were docked into the active site of alpha-glucosidase to predict the active ingredient responsible for its antidiabetic activity. Normally, a molecular docking platform offers the opportunity to interact a small molecule probe with a target and the corresponding algorithm computes a binding energy value.[59] However, false positive is one of the backlashes this computational model is facing in computational drug discovery mainstreaming.[60] Moreover, combining results from software of different algorithm have been proven to overcome this shortcoming.[61] Thus, in our study, iGEMDOCK, PyRx, and EASYDOCK VINA were used, and the result obtained from the three software were placed side by side and ranked based on the average ranked position such that relative rank is used as an absolute decision instead of binding affinity value.[62] This metric led to the selection of γ-sitosterol, tocopherol, and stigmasterol as possible hits of the polyherbal mixture responsible for the antidiabetic activity. More specifically, γ-sitosterol was ranked second in IGEMDOCK and EASYDOCK but was ranked first with PyRx making it emerge as the top hit for this study. On the other hand, tocopherol was ranked third in both iGEMDOCK and EASYDOCK but was ranked sec in PyRx, also, stigmasterol was ranked fourth in iGEMDOCK and PyRx but was ranked first in EASYDOCK [Figure 5]. Tocopherol and stigmasterol ranked next to γ-sitosterol. More surprisingly, acarbose which happens to be a standard inhibitor of alpha-glucosidase ranked fourth following the earlier listed hits, suggesting that γ-sitosterol, tocopherol, and stigmasterol could be better binders of alpha-glucosidase than acarbose. The interactions made by these compounds at the active site of the enzyme were mediated by hydrogen bond, Vander Waals force, and Pi interactions [Figure 6]. More interestingly, these hits had interaction with amino acid residues that are key to co-crystallized ligand binding, because Boyenle et al. recently highlighted a need for consideration of relevant amino acid during virtual screening events.[63] The amino acid residues these hits made interactions with include Asp203, Tyr299, Asp327, Trp441, Asp443, Asp542, Arg526, Phe575, Phe450, Trp406, and His600. One interpretation of this is that these prospective drug candidates can specifically bind to the active site of alpha-glucosidase and thus could prevent the hydrolysis of disaccharides. It should not go unmentioned that these three prospective drug candidates belong to the phytosterol group of phytochemicals and thus suggests a potential role of this family in reducing blood sugar level.
Figure 5: The Bar CHART showing the scored 14 ligands in iGEMDOCK, PyRx, and the correlating intersecting ligands in EASYDOCK Vina

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Figure 6: Molecular interaction between the three selected hits, the standard at the active site of alpha-glucosidase (a) Acarbose (b) γ-sitosterol (c) Stigmasterol (d) Tocopherol. The structures were rendered using discovery studio 2019

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ADMETox profiling and drug likeness

A successful clinical candidate must balance well on the knife edge of drug likeness and pharmacokinetics. The failure of most drugs in the clinical trial was recently ascribed to these properties.[64] Thus, we subjected the potential hits of this study to Lipinski's for drug-likeness evaluation and admetSAR for the determination of pharmacokinetic and some toxicological endpoints. It is believed that an orally bioavailable drug should not violate more than one of the rules of five (molecular weight ≤500, LogP ≤5, HBD ≤5, and HBA ≤10).[65] All i.e., stigmasterol, tocopherol, and gamma-sitosterol conform to this assumption [Table 4], none of them violated more than one and they show a better efficiency for drug development than the standard acarbose which defy three of the postulations. Pharmacokinetic endpoint prediction revealed the three compounds to have excellent ADME properties [Table 5]. More specifically, none of them were substrate and inhibitors of the cytochrome P450 families which is an important factor to take into consideration in long-term drug discovery pursuit. Inhibitors of the cytochrome P450 family enzymes portend a drug candidate to cause drug toxicity through drug-drug interaction.[66] An important consideration for targeting alpha-glucosidase is that its prospective drug must not have human intestinal absorption (HIA) property, because of its localization. Alpha-glucosidase is an intestinal enzyme, the HIA property the candidate possesses may cause it to bypass its target. The result shows stigmasterol and tocopherol didn't have HIA potential, however, gamma-sitosterol shows intestinal absorption propensity. In contrast to acarbose which could induce liver injury, none of these candidates also have the potential to cause hepatotoxicity. In drug discovery pursuit, positive ames result may work against the entire discovery project of a drug,[67] a positive ames result indicate a chemotype to be capable of causing cancer. Herein, stigmasterol, tocopherol, and gamma sitosterol are ames negative. A critical campaign in therapeutics is that potential drug candidates that are being considered for drug development should not inhibit the Human either-a-go-go (hERG).[68] hERG is a potassium ion channel that is responsible for cardiac cell repolarization, inhibition of this channel could cause heart dysfunction in form of QT syndrome.[69] The result here depicts none of the candidates have the affinity for this channel which is in contrast with standard acarbose. These parameters depict stigmasterol, tocopherol, and gamma sitosterol to be good candidates for pharmacological consideration than standard acarbose.
Table 4: Drug-likeness evaluation of the selected hits and standard Acarbose

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Table 5: ADMETox profiling of selected hits in comparison with standard acarbose

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  Conclusion Top

Polyherbal mixture of VA, AS, and OG inhibited pancreatic α-amylase and intestinal α-glucosidase which are key enzymes that regulate postprandial blood glucose, this property might be attributed to their high phenolic and steroid content coupled with their free radical scavenging activity. In addition, our GC/MS analysis and computational simulating methodologies revealed stigmasterol, tocopherol, and gamma sitosterol as the key bioactive compounds with strong α-glucosidase inhibitory affinity and pharmacokinetic properties when compared with acarbose. Thus, our data confirm the polyherbal mixture as not only an antidiabetic agent but also a remedy for oxidative stress-orchestrated diseases and also confers an important attribute to the family of sterols as an active ingredient with therapeutic efficiency for DM. Stigmasterol, tocopherol, and gamma sitosterol could also be developed as nutraceuticals for the management/treatment of Type-2 diabetes after advanced testing.

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Conflicts of interest

There are no conflicts of interest.

  References Top

American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2011;34 Suppl 1:S62-9. Available form: https://doi.org/10.2337/dc11-S062. [Last accessed on 2022 Oct 10].  Back to cited text no. 1
Kerner W, Brückel J. Definition, classification and diagnosis of diabetes mellitus. Exp Clin Endocrinol Diabetes 2014;122:384-6.  Back to cited text no. 2
Padhi S, Nayak AK, Behera A. Type II diabetes mellitus: A review on recent drug based therapeutics. Biomed Pharmacother 2020;131:110708.  Back to cited text no. 3
Schatz DA, Haller MJ, Atkinson MA. Type I diabetes. Preface. Endocrinol Metab Clin North Am 2010;39:xvii-xviii.  Back to cited text no. 4
Tariq R, Khan KI, Masood RA, Wain ZN. Natural remedies for diabetes mellitus. Int Curr Pharm J 2016;5:97-102.  Back to cited text no. 5
Roglic G. WHO Global report on diabetes: A summary. Int J Noncommun Dis 2016;1:3.  Back to cited text no. 6
Adelusi TI, Du L, Hao M, Zhou X, Xuan Q, Apu C, et al. Keap1/Nrf2/ARE signaling unfolds therapeutic targets for redox imbalanced-mediated diseases and diabetic nephropathy. Biomed Pharmacother 2020;123:109732.  Back to cited text no. 7
Forbes JM, Cooper ME. Mechanisms of diabetic complications. Physiol Rev 2013;93:137-88.  Back to cited text no. 8
Vinik AI, Nevoret ML, Casellini C, Parson H. Diabetic neuropathy. Endocrinol Metab Clin North Am 2013;42:747-87.  Back to cited text no. 9
Foss MC, Vlachokosta FV, Aoki TT. Carbohydrate, lipid and amino acid metabolism of insulin-dependent diabetic patients regulated by an artificial beta-cell unit. Diabetes Res 1989;11:1-8.  Back to cited text no. 10
Ighodaro OM. Molecular pathways associated with oxidative stress in diabetes mellitus. Biomed Pharmacother 2018;108:656-62.  Back to cited text no. 11
Kay AM, Simpson CL, Stewart JA Jr. The role of AGE/RAGE signaling in diabetes-mediated vascular calcification. J Diabetes Res 2016;2016:6809703.  Back to cited text no. 12
Kizub IV, Klymenko KI, Soloviev AI. Protein kinase C in enhanced vascular tone in diabetes mellitus. Int J Cardiol 2014;174:230-42.  Back to cited text no. 13
Melmer A, Laimer M. Treatment goals in diabetes. Endocr Dev 2016;31:1-27.  Back to cited text no. 14
Ayinde KS, Olaoba OT, Ibrahim B, Lei D, Lu Q, Yin X, et al. AMPK allostery: A therapeutic target for the management/treatment of diabetic nephropathy. Life Sci 2020;261:118455.  Back to cited text no. 15
Beran D, Hirsch IB, Yudkin JS. Why are we failing to address the issue of access to insulin? A national and global perspective. Diabetes Care 2018;41:1125-31.  Back to cited text no. 16
Gong S, Cai H, Ding Y, Li W, Juan X, Peng J, et al. The availability, price and affordability of antidiabetic drugs in Hubei province, China. Health Policy Plan 2018;33:937-47.  Back to cited text no. 17
Palhares RM, Gonçalves Drummond M, Dos Santos Alves Figueiredo Brasil B, Pereira Cosenza G, das Graças Lins Brandão M, Oliveira G. Medicinal plants recommended by the World Health Organization: DNA barcode identification associated with chemical analyses guarantees their quality. PLoS One 2015;10:e0127866.  Back to cited text no. 18
Salehi B, Ata A, V Anil Kumar N, Sharopov F, Ramírez-Alarcón K, Ruiz-Ortega A, et al. Antidiabetic potential of medicinal plants and their active components. Biomolecules 2019;9:551.  Back to cited text no. 19
Viswanathan V, Rajsekar S, Selvaraj B, Kumpatla S. Effect of a polyherbal formulation cream on diabetic neuropathic pain among patients with type 2 diabetes – A pilot study. Indian J Med Res 2016;144:215-9.  Back to cited text no. 20
[PUBMED]  [Full text]  
Feinberg T, Wieland LS, Miller LE, Munir K, Pollin TI, Shuldiner AR, et al. Polyherbal dietary supplementation for prediabetic adults: Study protocol for a randomized controlled trial. Trials 2019;20:24.  Back to cited text no. 21
Suvarna R, Shenoy RP, Hadapad BS, Nayak AV. Effectiveness of polyherbal formulations for the treatment of type 2 Diabetes mellitus – A systematic review and meta-analysis. J Ayurveda Integr Med 2021;12:213-22.  Back to cited text no. 22
Khalili N, Fereydoonzadeh R, Mohtashami R, Mehrzadi S, Heydari M, Huseini HF. Silymarin, olibanum, and nettle, a mixed herbal formulation in the treatment of type II diabetes: A randomized, double-blind, placebo-controlled, clinical trial. J Evid Based Complementary Altern Med 2017;22:603-8.  Back to cited text no. 23
Zarvandi M, Rakhshandeh H, Abazari M, Shafiee-Nick R, Ghorbani A. Safety and efficacy of a polyherbal formulation for the management of dyslipidemia and hyperglycemia in patients with advanced-stage of type-2 diabetes. Biomed Pharmacother 2017;89:69-75.  Back to cited text no. 24
Erukainure OL, Oyebode OA, Ibeji CU, Koorbanally NA, Islam MS. Vernonia Amygdalina Del. stimulated glucose uptake in brain tissues enhances antioxidative activities; and modulates functional chemistry and dysregulated metabolic pathways. Metab Brain Dis 2019;34:721-32.  Back to cited text no. 25
Shittu S, Shittu SA, Olatunji AA, Oyeyemi WA. Ocimum gratissimum leaf extract may precipitate infertility in male diabetic Wistar rats. JBRA Assist Reprod 2019;23:34-44.  Back to cited text no. 26
Patel DK, Prasad SK, Kumar R, Hemalatha S. An overview on antidiabetic medicinal plants having insulin mimetic property. Asian Pac J Trop Biomed 2012;2:320-30.  Back to cited text no. 27
Rahmani G, Farajdokht F, Mohaddes G, Babri S, Ebrahimi V, Ebrahimi H. Garlic (Allium sativum) improves anxiety- and depressive-related behaviors and brain oxidative stress in diabetic rats. Arch Physiol Biochem 2020;126:95-100.  Back to cited text no. 28
Ashraf R, Khan RA, Ashraf I. Garlic (Allium sativum) supplementation with standard antidiabetic agent provides better diabetic control in type 2 diabetes patients. Pak J Pharm Sci 2011;24:565-70.  Back to cited text no. 29
Asuquo EG, Udobi CE. Antibacterial and toxicity studies of the ethanol extract of Musa paradisiaca leaf. Cogent Biol 2016;2:1219248.  Back to cited text no. 30
Braca A, De Tommasi N, Di Bari L, Pizza C, Politi M, Morelli I. Antioxidant principles from bauhinia t arapotensis. J Nat Prod 2001;64:892-5.  Back to cited text no. 31
Oyaizu M. Studies on products of browning reaction antioxidative activities of products of browning reaction prepared from glucosamine. Japanese J Nutr Diet 1986;44:307-15.  Back to cited text no. 32
Dahlqvist A. Method for assay of intestinal disaccharidases. Anal Biochem 1964;7:18-25.  Back to cited text no. 33
Meites S, Saniel-Banrey K. Modified glucose oxidase method for determination of glucose in whole blood. Clin Chem 1973;19:308-11.  Back to cited text no. 34
Hadi MY, Mohammed GJ, Hameed IH. Analysis of bioactive chemical compounds of Nigella sativa using gas chromatography-mass spectrometry. J Pharmacogn Phyther 2016;8:8-24.  Back to cited text no. 35
Mohammed YH, Ghaidaa JM, Imad HH. Analysis of bioactive chemical compounds of Nigella sativa using gas chromatography-mass spectrometry. J Pharmacogn Phyther 2016;8:8-24.  Back to cited text no. 36
Binkowski TA, Naghibzadeh S, Liang J. CASTp: Computed Atlas of Surface Topography of proteins. Nucleic Acids Res 2003;31:3352-5.  Back to cited text no. 37
Hsu KC, Chen YF, Lin SR, Yang JM. iGEMDOCK: A graphical environment of enhancing GEMDOCK using pharmacological interactions and post-screening analysis. BMC Bioinformatics 2011;12 Suppl 1:S33.  Back to cited text no. 38
Trott O, Olson AJ. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 2010;31:455-61.  Back to cited text no. 39
Dallakyan S, Olson AJ. Small-molecule library screening by docking with PyRx. Methods Mol Biol 2015;1263:243-50.  Back to cited text no. 40
Adelusi TI, Abdul-Hammed M, Ojo EM, Oyedele QK, Boyenle ID, Adedotun IO, et al. Molecular docking assessment of clinically approved antiviral drugs against Mpro, Spike glycoprotein and angiotensin converting Enzyme-2 revealed probable anti-SARS-CoV-2 potential. Trop J Nat Prod Res 2021;5:778-91.  Back to cited text no. 41
Adelusi TI, Abdul-Hammed M, Idris MO, Kehinde OQ, Boyenle ID, Divine UC, et al. Exploring the inhibitory potentials of Momordica charantia bioactive compounds against Keap1-Kelch protein using computational approaches. In Silico Pharmacol 2021;9:39.  Back to cited text no. 42
Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, et al. PubChem substance and compound databases. Nucleic Acids Res 2016;44:D1202-13.  Back to cited text no. 43
Farnsworth NR. Biological and phytochemical screening of plants. J Pharm Sci 1966;55:225-76.  Back to cited text no. 44
Martins N, Petropoulos S, Ferreira IC. Chemical composition and bioactive compounds of garlic (Allium sativum L.) as affected by pre- and post-harvest conditions: A review. Food Chem 2016;211:41-50.  Back to cited text no. 45
El-Saber Batiha G, Magdy Beshbishy A, G Wasef L, Elewa YH, A Al-Sagan A, Abd El-Hack ME, et al. Chemical constituents and pharmacological activities of garlic (Allium sativum L.): A review. Nutrients 2020;12:872.  Back to cited text no. 46
Talabi JY, Makanjuola SA. Proximate, phytochemical, and in vitro antimicrobial properties of dried leaves from Ocimum gratissimum. Prev Nutr Food Sci 2017;22:191-4.  Back to cited text no. 47
Usunomena U, Ngozi OP. Phytochemical analysis and proximate composition of Vernonia amygdalina. International Journal of Scientific World 2016;4:11-4.  Back to cited text no. 48
Ekam VS, Ebong PE, Umoh IB. Phytochemical screening of activity directed extracts of Vernonia amygdalina leaves. Global Journal of Pure and Applied Sciences 2010;16:151-4.  Back to cited text no. 49
Andriyani R, Budiati TA, Pudjiraharti S. Effect of extraction method on total flavonoid, total phenolic content, antioxidant and anti-bacterial activity of Zingiberis officinale rhizome. Procedia Chem 2015;16:149-54.  Back to cited text no. 50
Kasote DM, Katyare SS, Hegde MV, Bae H. Significance of antioxidant potential of plants and its relevance to therapeutic applications. Int J Biol Sci 2015;11:982-91.  Back to cited text no. 51
Giacco F, Brownlee M. Oxidative stress and diabetic complications. Circ Res 2010;107:1058-70.  Back to cited text no. 52
Manian R, Anusuya N, Siddhuraju P, Manian S. The antioxidant activity and free radical scavenging potential of two different solvent extracts of Camellia sinensis (L.) O. Kuntz, Ficus bengalensis L. and Ficus racemosa L. Food Chem 2008;107:1000-7.  Back to cited text no. 53
Akinmoladun AC, Obuotor EM, Farombi EO. Evaluation of antioxidant and free radical scavenging capacities of some Nigerian indigenous medicinal plants. J Med Food 2010;13:444-51.  Back to cited text no. 54
Ali AM, El-Nour ME, Yagi SM. Total phenolic and flavonoid contents and antioxidant activity of ginger (Zingiber officinale Rosc.) rhizome, callus and callus treated with some elicitors. J Genet Eng Biotechnol 2018;16:677-82.  Back to cited text no. 55
Narendhirakannan RT, Rajeswari K. In vitro antioxidant properties of three varieties of Allium sativum L. extracts. E J Chem 2010;7:S573-9.  Back to cited text no. 56
Neha B, Ganesh B, Preeti K. Drug delivery to the brain using polymeric nanoparticles: A review. Int J Pharm Life Sci 2013;2:107-32.  Back to cited text no. 57
Igwe KK, Okafor PN, Ijeh II. GC–MS analysis of phytocomponents in Vernonia amygdalina del leaves and its contractile potential in mammary tissue in female albino Wistar rats. IOSR J Agric Vet Sci 2015;8:2319-72.  Back to cited text no. 58
Pinzi L, Rastelli G. Molecular docking: Shifting paradigms in drug discovery. Int J Mol Sci 2019;20:4331.  Back to cited text no. 59
Khanjiwala Z, Khale A, Prabhu A. Docking structurally similar analogues: Dealing with the false-positive. J Mol Graph Model 2019;93:107451.  Back to cited text no. 60
Dos Santos Maia M, Soares Rodrigues GC, Silva Cavalcanti AB, Scotti L, Scotti MT. Consensus analyses in molecular docking studies applied to medicinal chemistry. Mini Rev Med Chem 2020;20:1322-40.  Back to cited text no. 61
Feher M. Consensus scoring for protein-ligand interactions. Drug Discov Today 2006;11:421-8.  Back to cited text no. 62
Boyenle ID, Divine UC, Adeyemi R, Ayinde KS, Olaoba OT, Apu C, et al. Direct Keap1-kelch inhibitors as potential drug candidates for oxidative stress-orchestrated diseases: A review on in silico perspective. Pharmacol Res 2021;167:105577.  Back to cited text no. 63
Ferreira LL, Andricopulo AD. ADMET modeling approaches in drug discovery. Drug Discov Today 2019;24:1157-65.  Back to cited text no. 64
Lipinski CA. Lead- and drug-like compounds: The rule-of-five revolution. Drug Discov Today Technol 2004;1:337-41.  Back to cited text no. 65
Di L, Kerns EH. Profiling drug-like properties in discovery research. Curr Opin Chem Biol 2003;7:402-8.  Back to cited text no. 66
McCarren P, Springer C, Whitehead L. An investigation into pharmaceutically relevant mutagenicity data and the influence on Ames predictive potential. J Cheminform 2011;3:51.  Back to cited text no. 67
Walker BD, Singleton CB, Bursill JA, Wyse KR, Valenzuela SM, Qiu MR, et al. Inhibition of the human ether-a-go-go-related gene (HERG) potassium channel by cisapride: Affinity for open and inactivated states. Br J Pharmacol 1999;128:444-50.  Back to cited text no. 68
Lamothe SM, Guo J, Li W, Yang T, Zhang S. The human ether-a-go-go-related gene (hERG) potassium channel represents an unusual target for protease-mediated damage. J Biol Chem 2016;291:20387-401.  Back to cited text no. 69


  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


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