Iridoid glycosides from noni (Morinda citrifolia L.) fruit pomace: A novel booster strategy for its extraction and will its α -glucosidase inhibitory be increased by acetylation?
Chao Zhang
a,1, Chunhe Gu
b,c,1, Fan Su
b,1, Mengrui Wang
a, Junxia Chen
a, Ziqing Chang
a, Junping Zhou
a, Mingzhe Yue
a, Fei Liu
a,**, Zhen Feng
b,c,*aKey Laboratory of Dairy Science, Ministry of Education, College of Food Science, Northeast Agricultural University, 600 Changjiang Road, Harbin, 150030, Heilongjiang, China
bSpice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, 571533, Hainan, China
cKey Laboratory of Processing Suitability and Quality Control of the Special Tropical Crops, Wanning, 571533, Hainan, China
A R T I C L E I N F O Keywords:
Noni (Morinda citrifolia L.) fruit pomace Iridoid glycosides
Natural deep eutectic solvents α-Glucosidase
Interaction mechanism
A B S T R A C T
Iridoid glycosides (IGs) are secondary metabolites found in plants such as the noni plant (Morinda citrifolia L.), known for their diverse biological activities and potential health benefits. Herein, we screened fifteen natural deep eutectic solvents (NADES) and two conventional solvents (CS, 70% (V/V) methanol and 70% (V/V) ethanol) for extraction of IGs from noni fruit pomace. Our findings indicate that non-acidic NADES promote IG extraction. Glycerol/glycine combined with β-cyclodextrin was selected, and a molecular simulation was per- formed to elucidate the interaction between NADES components and IGs. Further, the structure-activity rela- tionship and interaction mechanisms of IGs with α-glucosidase were investigated using multispectral and molecular docking tools. The results demonstrated that deacetylation of the B-ring’s C-10 improved the inhib- itory potential of IGs. Deacetylation produces hydrophobic contacts, which enhance the inhibitory effect of deacetylasperulosidic acid on α-glucosides. Additionally, hydrogen bonds and van der Waals forces drive the formation of non-covalent complexes between IGs and enzymes.
1. Introduction
Noni (Morinda citrifolia L.), is a perennial plant belonging to the Rubiaceae family, Rubiacea Juss. Genus. This plant is primarily found and cultivated in equatorial regions with high rainfall, such as southern China, Southeast Asia, and the South Pacific islands. Noni fruit pro- duction results in substantial amounts of processing waste, such as pomace, which is often overlooked and underutilised, but can be a valuable source of bioactive compounds, including iridoid glycosides (IGs) (Barraza-Elenes et al., 2019). Only a few fruits contain these compounds. In addition to Morinda species (Nerurkar et al., 2015), IGs are also found in certain berries (Przybylska et al., 2023).
Growing environmental concerns have spurred interest in green and sustainable extraction techniques, with natural deep eutectic solvents (NADES) emerging as a new generation of eco-friendly, biodegradable
solvents derived from natural source. NADES contains amino acids, sugars, sugar alcohols, organic acids, and amines, which can either donate or accept hydrogen bonds (Liu et al., 2018). NADES has been utilised to extract bioactive chemicals such as phenolic acids and fla- vonoids (Miˇsan et al., 2020). A class of polymers known as cyclodextrins can enhance the dissolution, stability, and bioavailability of compounds by forming inclusion complexes with NADES (Hai et al., 2023). A novel method to improve the extraction of functional compounds involves the simultaneous use of NADES and cage macromolecules such as cyclo- dextrins. Extraction of secoiridoids was shown to improve by the addi- tion of cyclodextrins are added as a co-solvents in an aqueous solution (Yang et al., 2023b). However, IG extractions combining β-cyclodextrin and NADES, from noni fruit processing by-products have not yet been investigated.
IGs are a very efficient group of compounds that can block the
* Corresponding author. Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, 571533, Hainan, China.
** Corresponding author.
E-mail addresses: [email protected](F. Liu), [email protected](Z. Feng).
1These authors contributed to the work equally and should be regarded as co-first authors.
Contents lists available at ScienceDirect
LWT
journal homepage: www.elsevier.com/locate/lwt
https://doi.org/10.1016/j.lwt.2024.116626
Received 26 May 2024; Received in revised form 8 August 2024; Accepted 13 August 2024
LWT - Food Science and Technology 207 (2024) 116626
Available online 14 August 2024
0023-6438/© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by- nc-nd/4.0/ ).
activity of α-glucosidase (Blagojevi´c et al., 2021; Kılınc et al., 2023; Liu et al., 2015). Our previous studies showed that noni fruits are rich in deacetylasperulosidic and asperulosidic acids. Asperulosidic acid is a potent inhibitor of α-glucosidase (Milella et al., 2016). Deacetylasper- ulosidic and asperulosidic acids have very similar chemical structure, differing only in terms of acetylation (the structure shown in Fig. S1).
Acetylation is a significant chemical modification in the study of structure-activity relationships. Previous studies have shown that some natural α-glucosidase inhibitors are involved in acetylation (Dewi et al., 2014; Ren et al., 2020). However, the inhibition mechanism of deace- tylasperulosidic and asperulosidic acids as inhibitors of α-glucosidase remains unclear. The structure-activity relationship of deacetylasper- ulosidic and asperulosidic acids, particularly in relation to their inhibi- tion of α-glucosidase, remains unexplored; specifically, whether its α-glucosidase inhibitory activity is enhanced by acetylation of the C-10 hydroxyl group of the B ring.
This study hypothesised that NADES coupled with β-cyclodextrin could be successfully applied to extract IGs from noni pomace. To the best of our knowledge, this is the first report of IG extraction using NADES with incorporated β-cyclodextrin as cage molecules. The objec- tive of this study was to investigate the possible hypoglycemic effects of IGs (deacetylasperulosidic and asperulosidic acids) and analyse their structure-activity relationships. Assessing the inhibitory mechanisms of IGs on α-glucosidase is anticipated to provide a theoretical basis for the use of IGs in functional foods for the treatment of hyperglycemia.
2. Materials and methods 2.1. Materials
Noni fruit pomace was obtained from a local manufacture (Hainan Xinke Co., Ltd.). Seeds were removed from the pomace manually fol- lowed by freeze-drying and thorough milling, and the product was stored at − 20 ◦C until further analysis.
α-Glucosidase from Saccharomyces cerevisiae (≥50 U/mg, solid), deacetylasperulosidic acid, asperulosidic acid, acarbose, and p-nitro- phenyl-α-d-glucopyranoside (pNPG) were purchased from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). α-Glucosidase, acarbose, pNPG, deacetylasperulosidic acid, and asperulosidic acid were prepared in phosphate-buffered saline (PBS; 0.2 mol/L, pH 6.9). Other analytical grade chemicals were procured from Aladdin Chemical Co., Ltd. (Shanghai, China). Ultrapure water was used for the experiments.
2.2. NADES preparation
Multiple NADES were synthesised using the method described by
Rashid et al. (2023). The two components were combined in a sealed glass bottle according to the molar ratios listed in Table 1. Thickness of the mixtures were reduced by diluting with water to 30% concentration.
The entire mixture was incubated at 80 ◦C for 3 h in a shaking water bath until a transparent solution was obtained. The resulting solvents were stored at ambient temperature.
2.3. Evaluation of NADES extraction efficiency
The laboratory-scale ultrasonic probe sonicator (Cole, palmer, IL, USA). The process settings for the sonicator were set at a frequency of 20 kHz, power of 400 W, and duration of 30 min. A solid/liquid ratio of 1:30 g/ml was maintained throughout all experiments. The samples, along with the extraction medium, were placed in a glass beaker in an ice bath. The probe tip was submerged to a depth of 2 cm in the solution, and sonication was initiated. The ice bath counteracted the heat pro- duced during sonication to preserve the extraction temperature. The extracted samples were centrifuged using a refrigerated centrifuge (Eppendorf Centrifuge 5810 R) at 20,000×g for 10 min. The resultant mixture was filtered through Whatman No. 4 filter paper. The liquid portion was collected and placed in amber containers at a cold tem- perature. The extraction was carried out three times, whether using NADES or conventional organic solvents.
2.4. Extraction assisted by β-cyclodextrin incorporated into NADES This extraction procedure was carried out using extraction settings of 30 min and 30 g/100 g water in the chosen NDES, based on the results of the effect analysis reported in Section 2.3. The impact of including β-cyclodextrin on the extraction capacity of the NDES was examined utilising a single-factor approach. The effects of β-cyclodextrin were examined at doses ranging from 0 to 6 g/100 g. All experiments were performed in triplicate.
2.5. Identification and quantification of IGs by UPLC–DAD–ESI-MS The IGs in all the samples were determined using the method described by Barraza-Elenes et al. (2019). Briefly, an Accela UPLC–DAD system (Thermo Fisher Scientific Inc., Waltham, MA, USA) coupled to an LTQ XL mass spectrometer (Thermo Fisher Scientific) was used. The iridoid compounds were separated using on a C18 column (3 μm, 50 × 2.1 mm) (Fortis Technologies Ltd., Neston, UK). Quantitative analysis involved monitoring the photodiode array detector at a wavelength of 254 nm for IGs by comparing their retention times, and mass spectra to those obtained from standard solutions. The results are expressed as mg per g of sample on a dry weight basis (mg/g DW).
2.6. Molecular dynamics (MD) simulations for the extraction system Under optimized conditions, we performed simulations to prelimi- narily evaluate the interaction profile between the studied IGs and glycerol/glycine/β-cyclodextrin using Jovanovi´c et al.’s (2023)proto- col. The systems, containing each molecule (deacetylasperulosidic acid and asperulosidic acid) incorporated into a box (60 ×60 ×60 Å) of 200 molecules of glycerol and glycine, as well as 600 molecules of water, were generated using Packmol with a minimum distance of 2.4 Å be- tween the molecules. Simulations were performed using the Nanoscale MD program employing the CHARMM36 force fields. Topology files were generated using the CGenFF (CHARMM General Force Field) web platform. As in previous studies, a minimised and equilibrated system was used for a production run of 30 ns. The temperature was kept at 315.15 K, and the pressure 101 kPa.
2.7. Inhibition assays of α-glucosidase with IGs
The α-glucosidase inhibition assay was conducted following the Table 1
Prepared extraction solvents and their molar ratio (diluted with 30 % water).
No. Composition (A) Composition (B) Molar ratio
NADESa Choline chloride Lactic acid 1:3
NADESb Choline chloride Glucose 3:2
NADESc Choline chloride Glycerol 1:2
NADESd Choline chloride Fructose 3:2
NADESe Choline chloride Urea 1:2
NADESf Choline chloride Citric acid 1:1
NADESg Betaine Lactic acid 1:3
NADESh Betaine Glucose 3:2
NADESi Betaine Glycerol 1:2
NADESj Betaine Fructose 3:2
NADESk Betaine Urea 1:2
NADESl Betaine Citric acid 1:1
NADESm Urea Glycerol 1:2
NADESn Glycine Glycerol 1:3
NADESo Glycine Lactic acid 1:3
CSa 70% ethanol 1:1
CSb 70% methanol 1:1
method of Liu et al., 2021with minor modifications. Samples (50 μL), PBS (50 μL), and α-glucosidase (0.33 U/mL, 50 μL) were incubated together at 37 ◦C for 10 min. Following incubation, a solution of pNPG (100 μL, 3 mmol/L) was added and allowed to react for 30 min. Sub- sequently, a solution of Na2CO3 (750 μL, 0.2 mol/L) was added to terminate the reaction. Absorbance was measured at 405 nm using a 96-well ELISA (SynergyH1, Bio Tek, USA). Acarbose was used as a positive control. The inhibitory effects were calculated using the following equation:
α− glucosidase residual activity(%) = (A− B)/(C− D) ×100% (1) where A, B, C, and D represent the absorbance of the sample, sample, control, and control blank, respectively. IC50 values (concentration of IGs with 50% inhibition of α-glucosidase activity) were determined by GraphPad Prism 9.
2.8. Inhibition kinetics analysis for interaction between IGs and α-glucosidase
The α-glucosidase inhibition assay was used to evaluate the inhibi- tion of α-glucosidase by IGs. The pNPG concentration varied from 0.25 to 8.0 mmol/L. The inhibitory kinetics of IGs on α-glucosidases were analysed using the Michaelis‒Menten, Lineweaver‒Burk, Dixon model (Dixon, 1953), and Eisenthal‒Cornish‒Bowden model (Eisenthal &
Cornish-Bowden, 1974) as follows:
Michaelis‒Menten:
V=Vmax[S]/(Km+ [S]) (2)
Lineweaver‒Burk equation:
1/
V= Km/Vmax[S]+1/Vmax (3)
Dixon equation:
1/
V= (Km+ [S])/Vmax[S] + [I](Km/Kic+ [S]/Kiu)/Vmax[S] (4) Eisenthal‒Cornish‒Bowden equation:
[S]/V= (Km/Vmax)(1+ [I]/Kic) + ([I]/Vmax)(1+ [I]/Kiu) (5) where V is the initial reaction rate at different substrate concentrations, and Vmax is the maximum velocity; Km, Kic, and Kiu are the Michaelis, competitive inhibition, and uncompetitive inhibition constants, respectively; and [S] and [I] denote the concentrations of substrate and inhibitor, respectively.
2.9. Multi-spectroscopic analyses of interaction mechanism between IGs and α-glucosidase
2.9.1. Fluorescence spectra measurement
The fluorescence quenching spectroscopy of IGs in the presence of α-glucosidase was performed using a fluorescence spectrophotometer (F-4600, Hitachi Ltd., Tokyo, Japan) according to the reported method of Liu et al. (2021)with slight modifications. IGs solutions (0.2 mL) of different concentrations were combined with α-glucosidase solution (3 mL) and allowed to react at 298, 304, and 310 K for 20 min. PBS was substituted for IGs in the control group. The excitation wavelength was set to 230 nm and the emission wavelength ranged from 290 to 500 nm.
The emission and excitation wavelengths intervals were set to 5 nm. The quenching type was examined using the Stern‒Volmer equation.
F0
/F=1+Ksv× [Q] =1+kq×τ0× [Q] (6) where F0 and F represent the fluorescence intensities with or without IGs, respectively; τ0 represents the lifetime of the fluorophore (τ0 =10−8 s); Ksv represents the Stern‒Volmer quenching constant; kq represents the bimolecular quenching constant; and [Q] represents the concentra- tion of the quencher.
To remove the inner-filter effect, all fluorescence data were revised according to the following equation (Yang et al., 2021).
FCor=Fobse(Aex+Aem)/2 (7)
where Fcor is the corrected fluorescence intensity; Fobs is the recorrected fluorescence intensity; and Aex and Aem are the absorption values of the sample at the excitation and emission wavelengths, respectively.
Three-dimensional fluorescence spectroscopy of α-glucosidase (0.2 μmol/L) was also measured in the absence and presence of IGs. The excitation wavelength was set to 200–250 nm, and the emission wave- length was set to 200–500 nm.
2.9.2. Isothermal titration calorimetry (ITC)
Thermodynamic properties of IGs and α-glucosidase were deter- mined using an ITC calorimeter (MicroCal PEAQ-ITC, Malvern, UK) for which 300 μL of α-glucosidase solution (20 μmol/L) was injected into the sample cell, followed by the loading of the IG solution (200 μmol/L, 60 μL) into the injection syringe. The IG solution was added to the sample cell by titration, with 19 injections of 2.0 μL each. A blank experiment was performed by adding the IG solution to deionised water with a similar titration process.
2.9.3. Circular dichroism (CD) measurements
The effect of IGs on the secondary structure of α-glucosidase was assessed using a CD spectrometer (MOS-500, Bio-Logic Company, France). The three IGs (0.5 mL) were combined with α-glucosidase so- lution (0.5 mL) and incubated at 37 ◦C for 20 min. The control group comprised PBS instead of IGs. The path length was 0.1 cm, size of each step was 1 nm, and the range of wavelengths is from 190 to 260 nm. The test data were analysed using the DichroWeb online platform (http s://dichroweb.cryst.bbk.ac.uk).
2.10. Statistical analyses
The experimental data are presented as the means ±standard de- viations. One-way analysis of variance and Duncan’s test were per- formed using SPSS 19.0 software. Orthogonal Partial Least Squares- Discriminant Analysis (OPLS‒DA) was performed to visualise the discrimination among samples using SIMCA 14.1. Statistical significance was defined as p <0.05. All experiments were repeated at least three times.
3. Results
3.1. Property of IGs extracted with different solvents
Same profile was observed for IGs extracted using NADES and con- ventional solvents, with the dominant presence of deacetylasperulosidic and asperulosidic acids. As expected, the quantities of all individual and total IGs were varied significantly (p <0.05) depending on the solvent used (Fig. 1A). The extraction yields of total IGs obtained using NADES ranged from 5.59 ±0.23 mg/g DW for NADESa to 19.76 ±0.20 mg/g DW for NADESn. Methanol and ethanol showed low extraction effi- ciencies for individual and total IGs. Almost all the NADES were better at IG extraction, except for NADESa. OPLS‒DA was performed to sharpen the separation among all the extraction solvents and analyse the prop- erties of the extraction solvents. Different extraction solvents were used, as shown in Fig. 1B. NADESf, NADESj, NADESl, and NADESh were present in low amounts in asperulosidic acid. NADESn and NADESe were present in highest amounts in deacetylasperulosidic and asper- ulosidic acids, respectively, followed by NADESb, NADESc, NDESd, NADESi, NADESk, and NADESm. NADESb, NADESc, NADESd, NADESi, NADESk, and NADESm were present in similar amounts in deacetylas- perulosidic and asperulosidic acids. NADESa was low in deacetylasper- ulosidic and asperulosidic acids. CSa, Csb, NADESo, and NADESg level
were low in deacetylasperulosidic acid. To determine which IGs cause segregation, variable importance for the projection of >1.0 was used (Fig. 1C). Deacetylasperulosidic acid and total IGs were strongly corre- lated in the NADES group (Fig. 1D).
3.2. Effect of β-cyclodextrin incorporation with NADES
Extraction yield was consistently dependent on β-cyclodextrin con- centration for all the monitored compounds including IGs (Fig. 2A).
Using β-cyclodextrin at concentrations up to 3% (w/w) greatly enhanced extraction efficiency; however, further increasing the concentration to 6% (w/w) suppressed this effect.
The most significant improvement in extraction yield (approximately 19.04 %) was observed with asperulosidic acid. The β-cyclodextrin in the medium and discharged target molecule combine to create an in- clusion complex. The yields of deacetylasperulosidic acid and total IGs were increased by 18.28 and 18.56%, respectively, in the presence of 3%
(w/v) β-cyclodextrin.
3.3. MD simulation of incorporation of NADES with β-cyclodextrin In the current study, MD methodology was employed to reveal the most favourable interactions between selected NADESn combined with β-cyclodextrin and dominant iridoid compounds, deacetylasperulosidic acid, and asperulosidic acid, which influenced their extraction from noni fruits. Water formed hydrogen bonds with both constituents of the NADES (Fig. 2B). Analysis of the obtained results showed that deace- tylasperulosidic and asperulosidic acids exhibited hydrogen bond and carbon-hydrogen bond interactions with the constituents of the NADES, glycerol and glycine (Fig. 2C and D). β-Cyclodextrin also exhibited hydrogen and carbon-hydrogen bond interactions with
deacetylasperulosidic and asperulosidic acids (Fig. 2E and F). However, β-cyclodextrin showed hydrogen bond interactions with components of NADES (Fig. 2G).
3.4. Effect of IGs on α-glucosidase: Inhibition types
This study investigated the inhibitory effect of IGs on α-glucosidase by determining the initial reaction rate of different concentrations of α-glucosidases on pNPG at certain reaction times (Fig. S2 A-E). The degradation of various concentrations of IGs exhibited a consistent pattern, with the slope of the linear fit increasing as the substrate con- centration increased. The rate whereby α-glucosidases degrade pNPG diminished progressively as the concentration of the inhibitor increased.
The α-glucosidase activity steadily decreased as acarbose and IGs increased (Figs. S2 and F). The IC50 values of deacetylasperulosidic and asperulosidic acids were 4.569 ±0.237, and 6.692 ±0.162 mmol/L, respectively. Furthermore, the IC50 value of acarbose was found to be 0.012 ±0.001 μmol/L. It is essential to mention that a lower inhibitor IC50 value signifies a higher inhibitory activity towards the enzyme. As shown in Table 2, the inhibitory effects were ordered as follows:
deacetylasperulosidic acid >asperulosidic acid. In addition, the slopes of all linear fits were plotted as the initial reaction rates in Fig. 3A and E.
The initial reaction rate exhibited a rapid increase, estimated from 0 to 0.05 OD/min, followed by a slower and relatively constant rise. The data shows a consistent pattern at each IG concentration. The first-order re- action kinetics equation was transformed into a zero-order reaction, which confirmed the efficacy of the IGs in α-glucosidase inhibition.
Fig. 3B and F illustrate the relationship between the reaction velocity of the enzyme and concentration of pNPG in the presence of deacety- lasperulosidic and asperulosidic acids. The Michaelis‒Menten model was employed to estimate the values of Km and Vmax using nonlinear Fig. 1. Iridoid glycosides extraction efficiency of eleven different natural deep eutectic solvents (NADES) and two conventional solvents (CS), the different su- perscripts mean significant differences (p <0.05) (A); The score plots of OPLS-DA of iridoid glycosides in samples under different extraction solvents (B); The load plot from OPLS-DA (C); The VIP scores from OPLS-DA (D). DAA (deacetylasperulosidic acid), AA (asperulosidic acid), and TI (total iridoid glycosides).
regression analysis. The results are summarised in Table 2. The Km
values of the two IGs remained constant, whereas the Vmax values decreased with increasing inhibitor concentration. Specifically, for asperulosidic acid, the Vmax values decreased from 0.209 ±0.020 to 0.130 ±0.005 OD/min. For deacetylasperulosidic acid, the Vmax values decreased from 0.209 ±0.020 to 0.103 ±0.008 OD/min. This indicated that the two inhibitors exhibited a non-competitive inhibition mode. In addition, the types of inhibition were analysed using Lineweaver‒Burk plots (Fig. 3B–and F), which showed that all lines crossed at the opposing end of the x-axis, and the slope exhibits a positive correlation with the concentration of the inhibitors. This suggested that
deacetylasperulosidic and asperulosidic acids act as non-competitive inhibitors. The relationship between the concentration of the in- hibitors and values of Km and Vmax followed the same pattern as shown in Table 2, thereby supporting the non-competitive inhibition paradigm.
The inhibitory behaviours of the three IGs against α-glucosidase were further examined using Dixon and Cornish-Bowden plots. As shown in Fig. 3C, D, G, and H, the regression lines in each plot converged at a distinct location. The competitive inhibition (Kic) and uncompetitive inhibition constants (Kiu) values (Table 2) exhibited a high degree of similarity for each α-glucosidase-IG system, thereby indicating that these compounds effectively inhibited α-glucosidase in a non- Fig. 2. Effect of β-cyclodextrin incorporated into NADESn (glycerol/glycine) on extraction efficiency (A). Three-dimensional docking models binding interactions between NADESn (glycerol/glycine) and water (B), DAA (C), AA (D). Three-dimensional docking models binding interactions between β-cyclodextrin and DAA (E), AA (F). Three-dimensional docking models binding interactions between β-cyclodextrin and NADESn (glycerol/glycine) (including water) (G). Conventional H-bond interactions are depicted in green, non-conventional H-bond interactions are grey, for interpretation of the references to color in this figure legend; β-C (β-cyclo- dextrin), DAA (deacetylasperulosidic acid), AA (asperulosidic acid), TI (total iridoid glycosides), Gll (glycerol); Gle (glycine), and W (water). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
competitive manner. 3.5. Spectroscopic analyses of IGs’ interaction with α-glucosidase 3.5.1. Fluorescence quenching spectra
The study employed fluorescence excitation spectroscopy to examine the interactions between IGs and α-glucosidase. The amino acid Table 2
Kinetic parameters of α-glucosidase with the increasing concentration of deacetylasperulosidic and asperulosidic acids.
Reaction systems Concentration
(mmol/L) Inhibition type Vmax (OD/
min) Km (mmol/L) Kiu (mmol/L) Kic (mmol/L) Kiu/ Kic
IC50 (mmol/
L)
α-Glucosidase 0 – 0.209 ±
0.020a 2.007 ±
0.222a – – – –
α-Glucosidase-deacetylasperulosidic
acid 2.5 Non-
competitive 0.134 ±
0.013c 1.888 ±
0.216a 5.286 ±
0.146a 5.274 ±
0.128a 1.006 4.569 ±
0.237a
5.0 0.103 ±
0.008d 1.865 ±
0.166a
α-Glucosidase-asperulosidic acid 2.5 Non-
competitive 0.182 ±
0.011b 1.958 ±
0.143a 8.486 ±
0.397b 8.409 ±
0.272b 1.023 6.692 ±
0.162b
5.0 0.130 ±
0.005c 1.884 ±
0.176a The different superscripts in the same column mean significant differences (p <0.05).
Fig. 3. Michaelis-Menten, Lineweaver-Burk, Dixon and Eisenthal-Cornish-Bowden plots for α-glucosidase in the absence and presence DAA (A–D), and AA (E–H), respectively. The inset is the structure of iridoid glycosides. Axis labels demonstrate the concentration of substrate (S), reaction velocity (v), and the concentration of inhibitor (I). DAA (deacetylasperulosidic acid), AA (asperulosidic acid).
sequence (PDB: 3A4A, https://doi.org/10.2210/pdb3A4A/pdb) of S. cerevisiae α-glucosidase from the RCSB PDB (https://www.rcsb.org/) reveals that α-glucosidase is composed of 589 amino acids, including 20 Trp, 26 Tyr, and 35 Phe residues that exhibit intrinsic fluorescence. Two prominent excitation peaks of α-glucosidase were detected at 280 and 230 nm, respectively, attributable to the fluorescence emission of Trp residues (Figs. S3A and B). The excitation spectra of IGs and α-glucosi- dase overlapped in the region around the excitation wavelength (280 nm) during three-dimensional fluorescence spectral scanning. To pre- vent any disruption, the 230 nm excitation wavelength for tryptophan was chosen to assess the inherent fluorescence of α-glucosidase. Minimal light absorption was observed at the excitation (230 nm) and emission (200–600 nm) wavelengths, even when the highest concentration of IGs (7.5 mmol/L) was used (Figs. S3C, D, E, F).
The fluorescence spectra of α-glucosidase were recorded at 298 K in the presence of various concentrations of IGs (Fig. 4A and B). The addition of IGs resulted in a gradual decrease in the fluorescence in- tensity of α-glucosidase. The observed decrease in fluorescence can be
explained by the interaction between α-glucosidase and IGs, which leads to intrinsic fluorescence quenching. Furthermore, including IG resulted in a blueshift in the maximum emission, indicating a structural modi- fication and surroundings of the α-glucosidase. The order of the fluo- rescence quenching spectra was as follows: deacetylasperulosidic acid >
asperulosidic acid (Fig. 4C). The results were consistent with the inhibitory effect on α-glucosidase activity.
The Stern‒Volmer plots for the systems involving α-glucosidase and IGs are shown in the insets of Fig. 4A and B. The Figures exhibit a robust linear correlation at all temperatures, suggesting that the quenching mechanism is either dynamic or static, with no other modes involved.
The values of Ksv and bimolecular quenching constant (kq) are listed in Table 3. The values of Ksv significantly decreased as the temperature increased for the α-glucosidase-deacetylasperulosidic acid system, ranging from (1.766 ±0.029) ×103 to (1.216 ±0.016) ×103 L/mol.
Similarly, for the α-glucosidase-asperulosidic acid system, the values decreased from (0.957 ±0.011) ×103 to (0.589 ±0.012) ×103 L/mol.
The three-dimensional fluorescence spectra and characteristic
Fig. 4. The fluorescence emission spectra of α-glucosidase (0.25 μmol/L) at different concentration of DAA (A), and AA (B) at 298 K; The inset is the Stern-Volmer plots for α-glucosidase in the presence of different concentrations of DAA (A), and AA (B) at three different temperatures (T =298, 304, and 310 K). Stern-Volmer plots for α-glucosidase in the presence of different concentrations of DAA, and AA at 298 K (C). The three-dimensional fluorescence spectra: α-glucosidase without iridoid glycosides (D); α-glucosidase with 1.25 mmol/L DAA (E); α-glucosidase with 2.5 mmol/L DAA (F); α-glucosidase with 1.25 mmol/L AA (G); α-glucosidase with 2.5 mmol/L AA (H). DAA (deacetylasperulosidic acid), AA (asperulosidic acid).
fluorescence parameters of α-glucosidase with and without IGs are shown in Fig. 4D–H. Prominent primary peaks were observed in the three-dimensional fluorescence spectra of α-glucosidase. The peak (λex
=230 nm) mainly reflects the fluorescence characteristics of Trp resi- dues. The fluorescence intensity of the peak decreased markedly after adding IGs. The fluorescence intensity of Peak 1 showed a significant decrease after reacting with the IGs at 0–2.50 mmol/L; it decreased from 1581.0 to 671.2 for deacetylasperulosidic acid and from 1581.0 to 111.70 for asperulosidic acid. In addition, the position of the fluores- cence peak showed a slight blue-shift (Table 4).
3.5.2. Thermodynamic analysis
Fig. 5A, B, C, D, E, and F displays the ITC curves depicting the interaction between IGs and α-glucosidase at 25 ◦C. As depicted in Fig. 5A and D, each peak in the isotherm corresponded to a single IG injection into the α-glucosidase solution. The heat emitted per injection is shown in Fig. 5B and E, as a function of the molar ratio of IGs to α-glucosidase. The data in Fig. 5C were fitted to a sequence binding sites’
binding model using nonlinear least-squares regression. The solid lines represent the fits, which revealed the presence of three binding sites for α-glucosidase-deacetylasperulosidic acid. The binding constants were 1.83 ×10−6, 3.63 ×10−2, and 2.73 ×10−8 mol/L, and the enthalpy change (ΔH) of the reaction system was − 6.61, − 64.10, and − 79.20 kcal/mol, respectively. The (− TΔS) for α-glucosidase-deacetylasper- ulosidic acid was determined to be 1.22, − 66.00, and 68.90. The interaction between deacetylasperulosidic acid and α-glucosidase resulted in free energy (ΔG) values of − 5.39, − 1.90, and − 10.30 kcal/
mol. In Fig. 5F, the solid lines show nonlinear least-squares fits of data to a sequential binding sites’ binding model. These fits identify two binding sites, specifically the α-glucosidase-asperulosidic acid binding sites. The binding constants were 2.05 ×10−4 and 4.83 ×10−4 mol/L, and the ΔH values of the reaction system were − 85.00 and − 341.00 kcal/mol. The change in (-TΔS) for the reaction involving α-glucosidase and asper- ulosidic acid was determined to be 80.00 and 336.00 kcal/(mol•K), respectively. The interaction between asperulosidic acid and α-glucosi- dase resulted in ΔG of − 5.00 and − 5.00 kcal/mol for the two binding sites.
3.5.3. Effects of IGs on the secondary structure of α-glucosidase
Fig. 5G, H, I, and J displays the CD spectra of α-glucosidase in the presence and absence of IGs, measured within the wavelength range of 200–260 nm. The alterations in the content of the secondary structure are presented in Fig. 5G and I. CD spectra of α-glucosidase had two prominent negative peaks at approximately 211 and 225 nm. Adding IGs resulted in a considerable drop in the intensities of the two negative peaks, suggesting an alteration in the secondary structure of α-glucosi- dase. The inclusion of deacetylasperulosidic acid resulted in a decrease in the levels of α-helices and β-turns, while the levels of β-sheets increased (Fig. 5H). The content of α-helix increased, and the content of β-sheet decreased when asperulosidic acid was added (Fig. 5J).
4. Discussion
The poor extraction efficiencies of NADESa, NADESf, NADESg, NADESi, and NADESo is explained by IGs degrading into glucose mol- ecules under acidic condition. When IGs interact with acids, the initial reaction is the hydrolysis of the acetal link connecting the sugar unit and monoterpenoid aglycone (Pankoke et al., 2013) after the removal of glucose molecules by the opening of the hemiacetal ring and conversion of keto-enol. The iridoid aglycones are transformed into a dialdehyde.
This dialdehyde resembles glutaraldehyde when dissolved in water.
Solvent viscosity reduces extraction efficiency (Da Silva et al., 2020), such as sugar-based NADES (NADESb, NADESd, NADESh, and NADESj).
There were statistically significant differences in the extraction effi- ciencies with NADESc, NADESe, NADESi, and NADESk. Recently, choline chloride and betaine have been the most frequently employed hydrogen bond acceptors (HBAs) in producing NADES owing to their economic viability, biocompatibility, and minimal toxicity (Miˇsan et al., 2019). Our study found that choline chloride-based NADES exhibited a higher extraction capacity for IGs than betaine-based NADES. Choline chloride-based NADES are more effective in extracting geniposide from the gardenia fruit than choline-based NADES (Gan et al., 2023). The NADESn of amino acids based on alcohol groups was significantly more effective than other the NADES with high extraction efficiency and low cost in the present study. Similarly, NADES composed of glycine and glycerol are highly efficient in the extraction of secoiridoids from Gen- tiana rigescens (Yang et al., 2023b). NADES of alcoholic bases containing hydrogen bond donors (HBDs) have been the subject of numerous studies because they offer several advantages, such as being predomi- nantly liquid, straightforward to synthesise, and possessing long-range diffusion coefficients (Rahman et al., 2021). The IGs form more stable complexes with β-cyclodextrin, enhancing solubility and more efficient extraction when the extraction system reaches equilibrium (Shukla et al., 2020). Conversely, the reduced extraction efficiency at higher concentrations of β-cyclodextrin may be linked to increased viscosity resulting from the presence of sugar compounds (Solomakou et al., 2022). However, β-cyclodextrin, as a polar and polyhydroxylated molecule, effectively competes with IGs to interact with NADES com- ponents (Chakroun et al., 2021). Recently, molecular dynamics simu- lations have been used to understand the primary reasons behind the superior extraction efficiency of NADES (Baruah & Borgohain, 2023).
The MD simulation outcomes in the present study supplied a deeper insight into the potential binding interactions patterns between the studied ligands and NADES of glycerol and glycine, therefore providing Table 3
The quenching constant (Ksv) and the quenching rate constant (kq) for the interaction of deacetylasperulosidic and asperulosidic acids with α-glucosidase at different temperatures (T =298 K, 304 K, 310 K).
Reaction systems T Ksv ( ×103
L/mol) kq ( ×1011 L/
mol•s) R
α-Glucosidase-
deacetylasperulosidic acid 298
K 1.766 ±
0.029 1.766 ±
0.029 0.9991
304 K 1.508 ±
0.026 1.508 ±
0.026 0.9991
310 K 1.216 ±
0.016 1.216 ±
0.016 0.9995
α-Glucosidase-asperulosidic
acid 298
K 0.957 ±
0.011 0.957 ±
0.011 0.9997
304 K 0.779 ±
0.012 0.779 ±
0.012 0.9996
310 K 0.589 ±
0.012 0.589 ±
0.012 0.9995
R is the correlation coefficient between the Ksv values and the Kq values.
Table 4
Characteristics of three-dimensional fluorescence spectra of free α-glucosidase and the α-glucosidase-iridoid glycosides systems.
Reaction systems Concentration (mmol/L) Peak position λex/λem (nm/nm) Stokes Δλ (nm) Intensity F Inhabitation rate (%)
α-Glucosidase 0 225/335 110 1581 –
α-Glucosidase-deacetylasperulosidic acid 1.25 225/333 108 1033 34.66%
2.50 225/332 107 671.2 57.55%
α-Glucosidase-asperulosidic acid 1.25 225/334 109 1375 13.03%
2.50 225/333 108 1117 29.35%
a greater understanding of the extraction process with NADES combined with β-cyclodextrin, laying a good foundation for further studies in this field. The results also indicated that β-cyclodextrin interacted with NADES by hydrogen bond, which may reduce the extraction efficiency beyond optimal concentration in NADES solvent systems.
Deacetylasperulosidic and asperulosidic acids are effective inhibitors of α-glucosidase. Two IGs inhibited less than acarbose, but their natural properties and ability to block enzymes suggest that at medication dosage, they are used to reduce hypoglycemia. This result was consistent with previous reports that vanillin (186.26 mmol/L), caffeic acid (60.06 mmol/L), ferulic acid (90.90 mmol/L), rutin (0.97 mmol/L), quercetin (0.83 mmol/L), and kaempferol (1.22 mmol/L), which showed lower inhibition than acarbose (Liu et al., 2021; Qin et al., 2023; Xu et al., 2018). The IC50 values showed that the inhibitory effect of asperulosidic acid was greater than deacetylasperulosidic acid. The Km values of the two IGs remained constant, whereas the Vmax decreased with increasing inhibitor concentration. This indicated that the two inhibitors exhibited a non-competitive inhibition mode. Kic and Kiu are important factors for analysing the inhibitory properties of IGs on α-glucosidase. Kic and Kiu
intersect at the same point in the horizontal coordinate, indicating potent non-competitive inhibition (Borah et al., 2019). The Kic and Kiu
for both α-glucosidase-IGs systems were nearly identical, indicating non-competitive inhibition. The α-glucosidase contains aromatic amino acid residues, such as Trp, Tyr, and Phe with intrinsic fluorescence (Bobone et al., 2014), that contribute to its fluorescence spectra. The remarkable decrease in fluorescence intensity indicated that IGs were rapidly bound to α-glucosidase. The quenching constant of Ksv indicates the intensity of the α-glucosidase-quencher interaction (Wang et al.,
2022). Deacetylasperulosidic acid had the highest Ksv values at the same temperature, indicating that the α-glucosidase-deacetylasperulosidic acid system had the most significant impact on α-glucosidase fluores- cence quenching. The fluorescence quenching mechanisms can be calculated from the Stern‒Vomer equation and kq. In a solution system, the diffusion collision of various quenching agents leads to a maximum kq rate constant of 2.0 ×1010 L/(mol•s) for biological macromolecules (Lim et al., 2022). kq exceeded the maximum value, indicating the presence of static quenching, and molecules interacting to form a com- plex without fluorescence emission. The study found that α-glucosidase fluorescence decreased due to a stable complex with IGs, known as static quenching, rather than dynamic quenching. It confirmed that the for- mation of the IG-α-glucosidase complex followed a static quenching pattern (Lin et al., 2019). Comparing the IGs, we found a negative cor- relation between IC50 and kq, confirming the inhibition of α-glucosidase by the IGs. The peak (λex =230 nm) primarily represents Trp fluores- cence (Chen et al., 2020). The peak fluorescence intensity significantly decreased after the addition of IGs. A slight blueshift in the fluorescence peak suggested that the IGs altered the microenvironment and confor- mation of α-glucosidase (Yin et al., 2023). ITC has recently been used in enzyme-inhibitor complex studies. The negative ΔG values in this study provided thermodynamic proof of the binding process’ validity and spontaneity (Gui et al., 2023). The ΔG of the two IGs’s binding energy was <100 kcal/mol, suggesting non-covalent binding between them and α-glucosidase (Jia et al., 2020). If ΔH and ΔS is positive, hydrophobic interaction is the primary force. If ΔH and ΔS are negative, hydrogen bonding and van der Waals forces are the main binding forces (Zhu et al., 2020). Hydrogen bonds and van der Waals forces were the main Fig. 5. ITC data from the titration of 200 μmol/L iridoid glycosides into 20 μmol/L α-glucosidase at 25 ◦C: The raw data from the titration process of DAA (A), and AA (B), respectively. Fitting curve of the integrated heat in each injection (square) versus the molar ratio of α-glucosidase to iridoid glycosides: DAA (C), and AA (D), respectively; Thermodynamic parameters determined by ITC: DAA (E), and AA (F), respectively. CD spectra of α-glucosidase without and with DAA (G and H), and AA (I and J) at room temperature, Cα-glucosidase =2.5 μmol/L. DAA (deacetylasperulosidic acid), AA (asperulosidic acid).
interaction forces in forming the α-glucosidase-deacetylasperulosidic acid and α-glucosidase-asperulosidic acid complex due to the negative values of ΔH and ΔS. ΔH >0 and ΔS >0 were also shown for the α-glucosidase-deacetylasperulosidic acid. This result demonstrates that the interaction between deacetylasperulosidic acid and α-glucosidase is achieved mainly through hydrophobic interactions. The docking anal- ysis supported these findings. The results from CD spectroscopy that showed deacetylasperulosidic and asperulosidic acids induced alter- ations in the secondary structure of α-glucosidase, was due to deacety- lation of the C-10 group of the B ring, decreasing the α-helical content but increasing the amount of β-sheet. ITC analysis showed that the deacetylasperulosidic acid could interact with α-glucosidase through hydrophobic interactions, van der Waals forces, and hydrogen bonds.
We further confirmed that the conjugation of π→π* transition and hy- drophobic forces promoted the interplay of deacetylasperulosidic acid with α-glucosidase, since the content of α-helix decreased. Deacetylation loosens the enzyme structure by destroying the hydrogen-bonding network, consequently perturbing the binding capacity of the enzyme to its substrate (Yang et al., 2023a). β-sheet in the secondary structure of α-glucosidase appeared to be strongly affected by the acetylation of the C-10 group of the B ring. β-sheet is formed by the association of two polypeptide chains through establishing hydrogen bonds (Micsonai et al., 2015). Consequently, the rise in β-sheet content caused by asperulosidic acid led to enhanced interactions between the inhibitor and α-glucosidase through hydrogen bonding.
5. Conclusions
A new, highly effective, and eco-friendly method for extracting IGs from noni fruit pomace was successfully developed. Among the 15 NADES investigated in this study, glycerol/glycine exhibited the highest IG extraction efficiency (19.76 mg/g DW) and combined with β-cyclo- dextrin (3 g/100 g), it proved to be most appropriate for extracting noni IGs and increased the yield by 19.04% on recovery of IGs. Deacetylas- perulosidic and asperulosidic acids exhibited concentration-dependent inhibition of α-glucosidase. The enzyme activity was reversibly inhibi- ted in a non-competitive manner by the two IGs. The inhibitory ability of IGs was improved by the deacetylation of the C-10 of the B ring. This study provides a novel theoretical explanation for how IGs inhibit α-glucosidase activity. This can potentially facilitate the utilisation and implementation of IGs in the treatment of hypoglycemia.
CRediT authorship contribution statement
Chao Zhang: Writing – original draft, Software, Resources, Investi- gation, Formal analysis, Data curation. Chunhe Gu: Writing – original draft, Software. Fan Su: Writing – original draft, Software. Mengrui Wang: Software, Methodology, Investigation. Junxia Chen: Software, Methodology, Investigation. Ziqing Chang: Software, Methodology, Investigation. Junping Zhou: Software, Methodology, Investigation.
Mingzhe Yue: Validation, Methodology, Investigation. Fei Liu: Visu- alization, Methodology, Investigation, Funding acquisition. Zhen Feng:
Writing – review & editing, Visualization, Validation, Supervision, Project administration, Methodology, Investigation, Funding acquisi- tion, Data curation, Conceptualization.
Declaration of competing interest
The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted in LWT - Food Science and Technology.
Data availability
Data will be made available on request.
Acknowledgement
This work was supported by the Key Research and Development Project of Hainan Province (ZDYF2022XDNY269) and the grants from the Central Public-interest Scientific Institution Basal Research Fund for Chinese Academy of Tropical Agricultural Sciences (NO.1630142022006) and Chinese Academy of Tropical Agricultural Sciences for Science and Technology Innovation Team of National Tropical Agricultural Science Center (NO. CATASCXTD202404).
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.lwt.2024.116626.
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