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Journal of Food Science and Technology logoLink to Journal of Food Science and Technology
. 2023 Jul 23;60(10):2649–2658. doi: 10.1007/s13197-023-05789-x

Phytoconstituents from Urtica dioica (stinging nettle) of Sikkim Himalaya and their molecular docking interactions revealed their nutraceutical potential as α-amylase and α-glucosidase inhibitors

Swati Sharma 1,2, Srichandan Padhi 1, Rounak Chourasia 1, Sourav Dey 3, Srinivas Patnaik 2, Dinabandhu Sahoo 1,4,✉
PMCID: PMC10439086  PMID: 37599855

Abstract

In this study, antioxidative methanolic leaf extract (MeOH-SIS) of Urtica dioica was characterized for anti-diabetic activity. The extract was purified on a column to yield seven homogenous fractions (F1–F7) which were further determined for DPPH radical scavenging activity. MeOH-SIS and the fraction F1 (selected based on % yield and activity) were evaluated for their in vitro α-amylase and α-glucosidase inhibitory activity. The results showed inhibition of both enzymes in a dose dependent manner and F1 exhibited relatively higher inhibition than its mother extract MeOH-SIS. GC–MS analyses of both the extracts identified 24 major compounds among which 10 were previously described as bioactive compounds. Among all, 5 compounds demonstrated to have quality pharmacokinetics profiles and were examined for possible binding affinity against the active sites of α-amylase and α-glucosidase using molecular docking. The binding interaction of 2R-acetoxymethyl-1,3,3-trimethyl-4 T-(3-methyl-2-buten-1-yl)-1 T-cyclohexanol within the active sites of the target receptors was found to be significant among others, and can be developed as a potential inhibitor of α-amylase and α-glucosidase. The leaf extract can be utilized to develop food additive for the control and management of oxidative stress induced diabetes.

Keywords: Green leafy vegetable, Urtica dioica, Sikkim Himalayan region, Anti-diabetic activity, Antioxidants

Introduction

Green leafy vegetables have been contributing a very significant role in human health since ancient times. Being considered as one of the important sources of carbohydrates, fats, vitamins, essential amino acids and proteins, dietary fibers and minerals, some of them are equally important as nutraceuticals. Due to the gaining popularity of nutraceuticals and functional foods, researchers are characterizing the bioactive metabolites associated with lesser studied green leafy vegetables and fruits. Several plant derived bioactive compounds have been characterized and assessed for biological activity to explore their applications as functional food additives (Kalai et al. 2022; Khalid et al. 2023; Ibrahim et al. 2022). Their secondary metabolites exhibit a wide range of biological functions including antioxidative property, and are proven to be useful in overcoming oxidative stress and other associated disorders (Bhat and Al-Daihan 2014; Sharma et al. 2022). Beyond antioxidant potential leafy vegetables have been reported for other health benefits for their application as functional food additive includes anti-diabetic, anti-inflammatory, immunomodulatory, antibacterial, and anti-cancer properties (Khalid et al. 2023). Nonetheless, the pharmacological significance and phyto-constituents of most such leafy vegetables is still unknown.

Leafy vegetables are an integral part of the usual diet in Sikkim, a small Himalayan state in the north eastern region of India, where most of the vegetables are considered to be medicinally relevant. Urtica dioica (or stinging nettle), a perennial herb and a member of the family Urticaceae is used as an important leafy vegetable in this region. Locally it is known as “Sisnu” and is consumed as sour soup, curry, and as a vegetable complement (Sharma et al. 2022). U. dioica, since long years, has been used as diuretic and to treat joint pain, gout, arthritis and other rheumatic aliments (Hall and Bravo-Clouzet 2013). In modern clinical treatments, leaves of this plant are applied in the management of cardiovascular and diabetic symptoms (Chrubasik et al. 2007; Kianbakht et al. 2013). However, most of its pharmacological properties remain speculative and await scientific and clinical validation.

In this investigation, the methanolic extract of U. dioica leaves, which was found to have significant antioxidant activity in our earlier study was further purified into its sub fractions and evaluated for DPPH radical scavenging and in vitro antidiabetic (α-amylase and α-glucosidase inhibiting activity) activity. Gas Chromatography–mass spectrometry (GC–MS) methodology has been applied for identification of bioactive compounds in medicinal plants having numerous health promoting potentials (Malheiro et al. 2016; Ralte et al. 2022). GC–MS has been applied as a reliable technique for identifying phytochemicals including flavonoids, alkaloids, organic acids, lipid-based nutraceuticals, amino acids, etc. (Babatunde et al. 2019; Ralte et al. 2022; Ramya 2022). The most active fraction of U. dioica leaves extract was characterized using GC–MS, in silico pharmacokinetics and molecular docking. The characterization of bioactive constituents associated with U. dioica leaves along with its functional properties can lead to its popularization as functional food in the Himalayan region. Further, their active extracts can be applied as functional food additive for enhancing specific health benefits in other foods.

Materials and methods

Chemicals

Methanol (MeOH), hexane (HEX), ethyl acetate (EtOAC), 2,2-diphenyl-1-picrylhydrazyl (DPPH), Starch, 3, 5-Dinitrosalicylic acid (DNS), Di-sodium hydrogen phosphate, sodium carbonate (Na2CO3), Sodium-di-hydrogen phosphate, α-amylase, α-glucosidase, p-nitrophenyl-α-D-glucoside (PNPG), Folin–Ciocalteu reagent are procured from Sigma Aldrich.

Sampling and metabolites extraction

Fresh leaves of Urtica dioica were procured from the local market (Lal Bazaar, Gangtok). The leaves were cleaned by washing by tap water followed by oven-drying (40° C). The dried leaves were powdered using a mixer grinder and the leaf powder (100 g) was extracted with methanol (500 mL). The solution was kept for 72 h in dark with shaking being done at every 12 h. The extracts were collected by filtration using filter papers (Whatman No. 1), followed by concentration in a Rota evaporator (R 100, Buchi). The methanolic extract (1.25 g) was further purified by chromatography on a silica gel column (75 × 3 cm) using approximately 2 L of hexane: ethyl acetate (7:3) as eluent and 7 homogenous fraction groups were collected.

DPPH radical scavenging activity of different fractions

DPPH Radical scavenging activities of different fractions of SIS-MeOH were carried out as per methodology described by Chourasia et al. (2022). Briefly, extracts (200 μL) having defined concentration were added to test tube containing 2 mL of 0.16 mM DPPH solution. The content was kept for incubation (30 min) followed by measuring the absorbance at 517 nm by a spectrophotometer (Shimadzu, Kyoto, Japan). The calculation of DPPH radical scavenging potential was done by the equation given below:

Scavenging potential (%) = {1 − (Sabs − Babs/Cabs)} × 100.

Where, Sabs-absorbance of the extract, Cabs-absorbance of the control (DPPH) and Babs-absorbance of extract blank.

α-Amylase inhibitory assay

α-Amylase inhibitory assay of MeOH SIS and F1 extracts was carried by following the method explained by Ibrahim et al. (2014). Plant extract was added to 250 µL α-amylase (prepared in 0.02 M sodium phosphate buffer) followed by incubation for 10 min at 25ºC. Further, 250 µL of 1% starch solution was added to the mixture and followed by the incubation at 25 ºC for 10 min. To this solution mixture, 500 µL DNS was added and kept for incubation for 5 min in boiling water followed by addition of distilled water (5 mL). For sample blank 250 µL sodium phosphate buffer (0.02 M) was added instead of α-amylase and starch. Absorbance of the content was recorded at 540 nm using a spectrophotometer.

α-Glucosidase inhibitory assay

Inhibition of α-glucosidase by sample extract was assayed following the method explained by (Ibrahim et al. 2018). Briefly, 50 μL of α-glucosidase (1 U/mL) was preincubated with 100 μL sample extract and 100 μL potassium phosphate buffer (0.1 M, pH 6.9) for 10 min at 37 °C. Further, 50 mL of 5 mM p-nitrophenyl-α-D-glucoside (PNPG) was added to the preincubated mixture, vortexed and incubated for reaction at 37 °C for 30 min. The reaction was stopped by addition of 0.1 M sodium carbonate (1 mL) and the absorbance was measured at 405 nm in a spectrophotometer. Inhibition of α-glucosidase activity was assessed using the equation given below:α- glucosidase inhibition (%) = [(A − B) − (C − D)/(A − B)] × 100

Where, A is the absorbance in the presence of α-glucosidase and absence of the sample (sample substituted by buffer), B-absorbance in the absence of the enzyme and sample (buffer only), C-absorbance of mixture of enzyme and the sample, and D-absorbance in the presence of the sample and absence of the enzyme (α-glucosidase substituted by buffer).

Gas Chromatography–Mass Spectrometry (GC–MS)

The chemical constituents of MeOH extract of U. Dioica leaves and its fraction F1 were subjected to a Perkin Elmer Model: Clarus 680/600C GC–MS equipped with an Elite 5MS column (60.0 mm × 0.25 mm ID). 1 μL of the sample was injected and run for 39 min. The analysis conditions were: 1 min at 60 °C, ramp 7° C/min to 200 °C, hold 3 min, ramp 10 °C/min to 300 °C, hold 5 min. Helium (He) was used as the carrier gas and split ratio was 10:1. The MS scan was performed with EI (+ ve mode) within the range 50–600 Da. The peaks were identified on comparing the spectra with the National Institute Standard and Technique (NIST) library.

Drug likeliness and Pharmacokinetics

The ADMET (absorption, distribution, metabolism, elimination and toxicity) properties of the identified compounds were predicted using ADMETlab 2.0 (Xiong et al. 2021). The ‘simplified molecular input line entry system’ (SMILES) codes of the compounds were used as input for the program. The important ADMET predictions include drug likeliness (Lipinski’s rule), water solubility, human intestinal absorption (HIA), blood brain barrier penetration (BBB), human ether-a-go-go related gene (hERG) blockers, hepatotoxicity (HT), drug induced liver injury (DILI), Ames mutagenicity, and toxicophore prediction. The compounds displaying desirable ADMET features were selected and used in molecular docking.

Molecular Docking

Briefly, the crystallographic 3D structures of human pancreatic alpha amylase (PAM) and human maltase glucoamylase (MGA) were retrieved from the protein data bank using PDB identifiers 3BAI and 3CTT, respectively. The structures were selected based on the best available resolution in the database. Protein structures were optimized upon removing the heteroatoms and water molecules, and adding polar hydrogens and Kollman charges using Autodock tools. Similarly, chemical structures of the selected compounds were retrieved from PubChem and minimized prior to docking which was performed using CB Dock web server that uses the popular docking program Autodock Vina (Liu et al. 2020). The docked complexes were visualized in Discovery Studio Visualizer (DSV) 2020 and receptor ligand interactions were analyzed. The docking results were also compared to a reference inhibitor and anti-diabetic drug, acarbose.

Statistical analysis

The data of all the experiments (performed in triplicates) in the present study were presented as mean ± standard deviation. The statistical analyses were accomplished by subjecting the experimental data to ANOVA (one way analysis of variance) using Minitab 19 software with a confidence of 95% (P < 0.05).

Results and discussion

The significance of ample vegetable consumption in the promotion of human health has been known since years. Studies on green leafy vegetables on the other hand deserve special attention as they have potential in development of functional foods. They have been proposed to have various antioxidant compounds and some of them have been shown to reduce the risk of oxidative stress mediated metabolic disorders such as type 2 diabetes (Brouwer-Brolsma et al. 2020). The leaf extract used in this study was one among several organic extracts which have shown promising antioxidant activity in our earlier study (Sharma et al. 2022). Characterization of active constituents and bioactivity of the extract as well as its fractions can lead to their application as functional food additives. The methanolic (MeOH-SIS) extract (1.25 g) was purified on a column to yield 7 homogenous fractions namely F1 (173 mg), F2 (94 mg), F3 (36 mg), F4 (125 mg), F5 (17 mg), F6 (41 mg) and F7 (56 mg). The percentage yields of each fraction have been presented in Fig. 1A. The fractions were evaluated for their antioxidant potential using DPPH radical scavenging activity assay, and fractions F1 and F6 demonstrated highest antioxidant activity as compared to other fractions. Overall antioxidant activity of the MeOH extract was 20.92% and the activity of the fractions ranged from 17.63 to 41.47% (Fig. 1B). Based on the % yield and DPPH radical scavenging activity, fraction F1 was selected for further study. Activity of F1 fraction was found to be 1.89-fold higher than parent extract.

Fig. 1.

Fig. 1

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Percentage yield A and DPPH scavenging activity B of obtained fractions (F1–F7) from MeOH-SIS crude organic extract. Data in the graphs not sharing common alphabets (a, b, c, d, e) in respective figure are significantly different (p < 0.05). F1–F7: Seven homogenous fraction groups eluted using hexane: ethyl acetate (7:3)

The antioxidative phytoconstituents (for example phenolic acids and flavonoids) are reported to scavenge the excess production of reactive oxygen species (ROS). In addition, they can neutralize the affects of ROS on the β-cells which secrete insulin and facilitate glucose uptake into muscle, brain, liver, adipose tissue and other glucose recipient organs, thereby preventing the oxidative stress induced diabetes (Sekhon-Loodu and Rupasinghe 2019). The carbohydrate metabolizing enzymes such as α-glucosidase and α-amylase influence an increase in postprandial blood glucose level in diabetic patients and are recognized as important markers of hyperglycemia or diabetes. Inhibition of these digestive enzymes may result in lowering of blood glucose level and reduced risk of diabetes (Poovitha and Parani 2016). Many of the phytoconstituents having antioxidant potential have been suggested to inhibit α-amylase and α-glucosidase, contributing in the treatment of diabetes (Pieczykolan et al. 2021). It is therefore pertinent to explore leafy vegetables that can be utilized in reducing blood-glucose levels and others diabetic biomarkers. The parental MeOH-SIS and fraction F1 were evaluated for in vitro α-amylase and α-glucosidase inhibition. The extracts demonstrated inhibition of both the enzymes in a concentration dependent manner. The α-glucosidase inhibitory potential of MeOH-SIS and F1 fraction was studied from an initial concentration of 0.25 mg/ml up to 1.25 mg/ml. The α-glucosidase followed the increasing trend of inhibitory effect ranging from 9.36-46.06%  and 15.76-87.74%  for MeOH-SIS and F1 fraction, respectively (Fig. 2). Similarly, α-amylase inhibition was studied at an increasing concentration from 0.375-0.625   mg/ml (Fig. 3). α-amylase inhibition was observed in the range of 4.51-27.66%  for MeOH-SIS and 8.71-43.71% for fraction F1. IC50 values of the F1 fraction exhibited 1.9-fold higher inhibitions in comparison to MeOH-SIS. The difference in enzyme inhibitory activity could be attributed to the ability of different solvents to extract specific compounds based on their physiochemical properties such as polarity, chemical nature of the extracted compounds, and the presence or absence of interfering substances (Boeing et al. 2014). The active extracts were subjected to GC–MS-based identification of major constituents. The GC–MS chromatograms demonstrated presence of several prominent peaks with considerable height and area based on which 24 major peaks (12 each from MeOH-SIS and F1) were selected and identified. Ten of the GC–MS-based identified compounds have been reported to have functional properties including antioxidant properties, and others were identified in several active extracts of many plants (Table 1). Some of the peaks were identified as common in both the extracts which include 3-methyl-2-(2-oxopropyl) furan, hentriacontane, Z,Z-6,28-heptatriactontadien-2-one and cyclotrisiloxane, hexamethyl.

Fig. 2.

Fig. 2

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α-Glucosidase inhibiting activity of the MeOH-SIS extract (SISME) and F1 fraction (SISME F1). Data in the graphs not sharing common alphabets (a, b, c, d, e) within same extract in respective figure are significantly different (p < 0.05)

Fig. 3.

Fig. 3

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α-Amylase inhibiting activity of the MeOH-SIS extract (SISME) and F1 fraction (SISME F1). Data not sharing common alphabets (a, b, c, d, e) within same extract in respective figure are significantly different (p < 0.05)

Table 1.

Major phyto-constituents identified from the U. dioica MeOH extract and its fraction F1 using GC–MS

Retention time (Rt) Area (%) Name of the compound(s) MW (g/mol) Chemical formula Bioactivity References
SISNU MeOH Extract
8.023 1.556 3-Methyl-2-(2-oxopropyl)furan 138.16 C8H10O2 Antioxidant & antimicrobial Ralte et al. 2022
8.629 5.507 Rhodoviolascin 596.9 C42H60O2 Antioxidant Black et al. 2020
10.930 1.113 2-Hexenoic acid, (E)- 114.14 C6H10O2 Flavoring agent Malherio et al. 2016
13.060 1.075 Oxalic acid, ethyl neopentyl ester 188.22 C9H16O4 Antiobesity Kalayoglu et al. 2013
17.882 0.902 1H-indene, 1-ethylidene- 142.20 C11H10 NR Joshi 2018
22.774 1.380 Hentriacontane 436.8 C31H64 anti-inflammatory, antitumor & antimicrobial Khajuria et al. 2017
27.416 2.507 Neophytadiene 278.5 C20H38 Antimicrobial & antioxidant Pratama et al. 2019
31.308 3.684 Z,Z-6,28-heptatriactontadien-2-one 530.9 C37H70O NR Ralte et al. 2022
32.878 3.047 2R-acetoxymethyl-1,3,3-trimethyl-4 T-(3-methyl-2-buten-1-yl)-1t-cyclohexanol 282.4 C17H30O3 Antimicrobial & antioxidant Naine et al. 2016
33.459 4.525 1,3,6,10-Cyclotetradecatetraene, 3,7,11-trimethyl-14-(1-methylethyl)-, (S-(E,Z,E,E))- 272.5 C20H32 NR Thimmegowda et al. 2013
38.701 4.513 Cyclotrisiloxane, hexamethyl- 222.46 C6H18O3Si3 NR Ahmed et al. 2020
38.826 2.437 Arsenous acid, tris (trimethylsilyl) ester 342.49 C9H27AsO3Si3 NR Falowo et al. 2017
SISNU F1 Fraction
8.023 0.917 3-Methyl-2-(2-oxopropyl)furan 138.16 C8H10O2 Antioxidant & antimicrobial Ralte et al. 2022
9.264 1.265 Meso-2,5-dimethyl-3,4-hexanediol 146.23 C8H18O2 NR Zhang et al. 2022
22.774 2.097 Hentriacontane 596.9 C42H60O2 anti-inflammatory, antitumor & antimicrobial Khajuria et al. 2017
27.416 1.198 Z,Z-6,28-heptatriactontadien-2-one 530.9 C37H70O NR Ralte et al. 2022
28.787 4.719 Methyl 11-methyl-dodecanoate 228.37 C14H28O2 NR Ralte et al. 2022
31.088 4.584 11,14-Octadecadienoic acid, methyl ester 294.5 C19H34O2 NR Siswadi & Saragih 2021
31.163 3.775 Methyl 8,11,14-heptadecatrienoate 278.4 C18H30O2 NR Manjari et al. 2014
31.313 6.213 Phytol 296.5 C20H40O Antioxidant, antimicrobial & immune-modulating Islam et al. 2018
36.095 2.553 Alpha-tocopheryl acetate 472.7 C31H52O3 Antioxidant Sunarić et al. 2017
38.706 2.048 Tris(tert-butyldimethylsilyloxy)arsane 468.7 C18H45AsO3Si3 NR Babatunde et al. 2019
32.998 0.954 2,4,4-Trimethyl-3-hydroxymethyl-5A-(3-methyl-but-2-enyl)-cyclohexene 222.37 C15H26O NR Anupama et al. 2014
36.800 0.945 Cyclotrisiloxane, hexamethyl- 222.46 C6H18O3Si3 NR Ahmed et al. 2020
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Assessment of the ADME features has been playing a considerable role in developing bioceutical (pharmaceutical or nutraceutical) and the same reportedly has accounted for the failure of majority of test compounds in the clinical phases. Aqueous solubility of proposed molecules is an excellent predictor of their absorption; better solubility correlates with better absorption of the compound. However, the real duodenal contents contain more detergents than water and favours drugs that are moderately or less soluble in water (Lipinski 2008). For any bioactive compounds to be used as bioceuticals they need to be absorbed in the blood stream or mucosal surface before reaching to the target tissue. Poor solubility, intestinal transit, and the inability to permeate the intestinal wall are some of the limiting factors in the absorption of active molecules. In addition, the lack of ability to infiltrate the blood brain barrier (BBB) is the reason why few treatments that demonstrate activity in other organs fail to reach the brain. The Caco-2 permeability has been considered as another important predictor of intestinal absorption of small molecules. Caco-2 cells are human colon adenocarcinoma cell lines which have been used as a model of human intestinal absorption of bioceuticals (Padhi et al. 2021; van Breemen and Li 2005).

The extent to which a candidate drug can cause harm to the living cells/organisms is referred to as drug toxicity and this remains one of the most crucial reasons for most drug failure in final stages. Early prediction and identification of toxicity parameters is therefore critical in the process of drug design and development. The voltage gated potassium channels encoded by the gene hERG are an essential component of cardiac depolarization and re-polarization, and play a central role in regulation of heart’s action and resting potential. Any blockade in this channel may result into long QT syndrome, Torsade de Pointes (TdP) that in turn may lead to cardiotoxicity with severe fatal irregularities (Witchel Witchel and Harry 2011). Therefore, well-grounded appraisal of hERG liability is indispensable in order to minimize the cardiotoxic risk of bioactive drug or nutraceutical candidates.

Many drugs carry one or more reactive moieties which are otherwise known as toxicophore(s) and can participate in a toxic response. Toxicophores have been known to precipitate drug-induced liver damage (DILI) in susceptible patients as most prescribed medications are metabolized by human liver. Therefore, DILI and hepatotoxicity of bioactive molecules are major concerns and are the main reason for drug withdrawl from the pharmaceutical market (Boelsterli and Kashimshetty 2010). Carcinogenicity remains as one of the major setbacks in the bioceutical development process (Meunier and Larrey 2019). It is important to assess the ability of the proposed compounds to cause damage to the DNA and impede host cellular metabolic process. As such, many approved drugs have been identified as carcinogens to humans and withdrawn from the market. In addition, with the vast available experimental data on the Ames mutagenicity of known chemical compounds it is now possible to identify the DNA reactive impurities from their chemical structure (Synder and Smith 2005). Among the identified compounds, ADME and T profiles of 2R-acetoxymethyl-1,3,3-trimethyl-4t-(3-methyl-2-buten-1-yl)-1 T-cyclohexanol (1), methyl 11-methyl-dodecanoate (2), 11,14-octadecadienoic acid methyl ester (3), methyl 8,11,14-heptadecatrienoate (4), and 2,4,4-trimethyl-3-hydroxymethyl-5A-(3-methyl-but-2-enyl)-cyclohexene (5) were found to be satisfactory and demonstrated the potential for application in the nutraceutical industry (Table 2). Further, the chemical structures of selected compounds were used as ligands to examine their binding affinity against the active sites of human PAM and MGA using molecular docking. Molecular docking has become a widely used computational approach to screen and predict the intermolecular affinity and interactions between a receptor protein and a set of small molecules in modern nutraceutical development (Talukdar et al. 2021). The compound (1) and (5) demonstrated notable binding free energy (− 7.0 and − 6.7 kcal/mol, respectively) against human PAM. Similarly, the binding free energy of (4) (− 7.2 kcal/mol) was found to be substantial against human MGA which was followed by compound (3) (− 6.6 kcal/mol). The binding free energies of the compounds were similar to that of acarbose. Above all, binding interaction of compound (1) against both the target sites was significant. The docking results are given in Table 3. In every case, the interactions were supported by several non-covalent forces of attraction, including hydrogen bonds, electrostatic and hydrophobic interactions. The hydrogen bonds are known to confer stability and structural integrity to the receptor-ligand complexes. The hydrophobic interactions on the other hand intercalate the binding affinity of the ligand within the binding pockets of the target receptors (Rahman et al. 2016). Overall findings of the study suggest that the leaves of U. dioica are a rich source of antioxidant compounds that could further exert significant α-amylase and α-glucosidase inhibitory activity. Owing to the drug likeliness and pharmacokinetics, compound (1) which was reported as an experimentally proven natural antioxidant that has shown significant binding affinity and interactions towards the active sites of α-amylase and α-glucosidase. The study can lead to development of dried extracts and its fraction (F1) as functional food additives having potential blood glucose lowering property provided that their efficacy and potency must be evaluated in animal models and clinical settings. In addition, the leafy vegetable from the Himalayan region can be popularised as one of the functional foods for the management of oxidative stress induced diabetes.

Table 2.

Representative ADMET profiles of selected compounds used in this study predicted using ADMETlab 2.0

Name of the compound Solubility (log S) HIA BBB Caco-2 hERG H-HT DILI Ames mutagenicity Carcinogenicity Toxicophore Drug likeliness Golden triangle
2R-ACETOXYMETHYL-1,3,3-TRIMETHYL-4 T-(3-METHYL-2-BUTEN-1-YL)-1 T-CYCLOHEXANOL − 4.407 0.012 0.942 − 4.509 0.009 0.253 0.037 0.004 0.048 0 Accepted Accepted
METHYL 11-METHYL-DODECANOATE − 5.554 0.002 0.798 − 4.501 0.062 0.044 0.292 0.006 0.103 0 Accepted Accepted
11,14-OCTADECADIENOIC ACID, METHYL ESTER − 5.925 0.041 0.145 − 4.794 0.166 0.269 0.031 0.002 0.059 0 Accepted Accepted
METHYL 8,11,14-HEPTADECATRIENOATE − 5.538 0.083 0.018 − 4.804 0.061 0.87 0.014 0.002 0.074 0 Accepted Accepted
2,4,4-TRIMETHYL-3-HYDROXYMETHYL-5A-(3-METHYL-BUT-2-ENYL)-CYCLOHEXENE − 4.998 0.007 0.937 − 4.321 0.007 0.701 0.016 0.002 0.052 0 Accepted Accepted
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Values in the range 0–0.3: excellent, 0.3–0.7: medium and 0.7–1: poor except for log S (− 4–0.5 log mol/L, proper), Caco-2 (> − 5.15, excellent) and Toxicophore (0-negative, 1-positive)

HIA human intestinal absorption, BBB blood brain barrier penetration, Caco-2 human colon adenocarcinoma cell lines permeability, hERG human ether-a-go-go related gene blockers, H-HT hepatotoxicity, DILI drug induced liver injury

Table 3.

Binding free energy and 2D representation of receptor–ligand interactions between the target enzymes and test compounds used in this study

graphic file with name 13197_2023_5789_Tab3_HTML.jpg

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Conclusion

The present study investigated the α-amylase and α-glucosidase inhibitory potentials of an antioxidative U. dioica leaf extract and a purified fraction F1. The fraction F1 exhibited higher inhibition of both the enzymes than the mother extract. Five compounds (one from MeOH-SIS-and four from fraction F1) among others were identified using GC–MS and demonstrated quality drug likeliness and pharmacokinetics features, and molecular docking of the compounds predicted 2R-acetoxymethyl-1,3,3-trimethyl-4 T-(3-methyl-2-buten-1-yl)-1 T-cyclohexanol as having substantial binding affinity and interaction against α-amylase and α-glucosidase. Further investigations to prove its efficacy and potency need to be done in animal models. The plant extract as well as F1 fraction can have potential application as food additive for the management of oxidative stress induced diabetes.

Acknowledgements

We acknowledge Institute of Bioresource and Sustainable Development and Department of Biotechnology, Ministry of Science and Technology, Govt. of India for the funding for conducting the research work.

Author’s contribution

SS-Conducted the experiments, performed the data analyses and Writing-original draft; SP-performed the data analyses, Writing—original draft, review & editing; RC-performed the data analyses, Writing—original draft; SD-performed the data analyses; SP-Conceptualization, and Writing—review & editing. DS-Conceptualization, Project administration, review & editing. The final manuscript was read and approved by all contributors.

Funding

The research work was supported by Department of Biotechnology, Govt. of India.

Data availability

All datasets generated for this study are included in the article/supplementary material.

Code availability

Not applicable.

Declarations

Conflict of interest

The authors declare no competing interests.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

All datasets generated for this study are included in the article/supplementary material.

Not applicable.

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