In silico and in vitro Evaluation of Microwave-Assisted Synthesized Isoxazole Chalcone Derivatives of Selected Phytoconstituents for Antidiabetic Activity

INTRODUCTION

Diabetes Mellitus (DM) is a metabolic disorder described by prominent blood glucose levels due to insulin deficiency or resistance. In most developed countries, it primarily affects middle-aged individuals and children. ¹ Diabetes can lead to severe complications, including obesity, stroke, and heart failure. According to the International Diabetes Federation, the number of people with diabetes is projected to rise from 415 million in 2015 to 640 million by 2040. Type I Diabetes (T1DM) accounts for 5-10% of cases, while Type II Diabetes (T2DM) is far more prevalent, affecting over 90% of diabetic individuals. The development of DM is influenced by complex dysfunctions in organs, proteins, and enzymes. ^2,3 Given the multifactorial nature of diabetes, no single experimental model or treatment can fully address its complexity. Effective disease management involves a combination of a balanced diet, regular exercise, and the use of synthetic or natural therapeutics. In diabetes, α-amylase and α-glucosidase enzymes play a decisive role in breaking down carbohydrates, leading to postprandial blood sugar spikes. ⁴ Various cellular and metabolic targets have been explored to expand pancreatic function, augment insulin secretion, and optimize insulin activity at target sites. Consequently, α-amylase and α-glucosidase inhibitors serve as essential therapeutic markers for diabetes treatment. ^5,6,7 However, the clinical application of many existing diabetes therapeutics is limited due to gastrointestinal side effects, metallic taste, and constipation, loss of appetite, poor bioavailability, and short circulation half-life. These challenges highlight the urgent need for the development of novel anti-diabetic agents. Heterocyclic compounds have emerged as promising candidates for managing diabetes effectively. ^8,9 Molecular docking is an in silico approach used to predict the most stable ligand-receptor interaction. It evaluates the binding affinity of specific ligands to the active site of a receptor protein. Docking efficiency is assessed based on docking scores and interaction types, such as hydrogen bonding, ionic interactions, van der Waals forces, and π-π stacking. A more negative binding energy indicates stronger ligand-receptor interactions, signifying better docking performance. ^10,11,12 Several herbs that are used as medicines have been reported to help prevent/treat diabetes at different stages. For example, curcumin may be used to treat pre-diabetes in order to prevent Type 2 (T2) diabetes from developing, while cinnamon may help treat diabetes patients with both hypertension and diabetes. Additionally, aloe vera leaf gel has been shown to increase insulin levels and restore pancreatic beta cells ¹³ in doses of 300 mg/kg. Multiple α-glucosidase inhibitors are used for the treatment of T2 diabetes (e.g., voglibose, acarbose, miglitol, etc.) and several studies are ongoing looking for potential natural products that can be effectively used to manage diabetes; some plants, such as aster, cinnamon, mistletoe fig and bitter oleander have potential inhibitory effects on α-glucosidase. In addition, several medicinal herbs including Camellia sinensis, Aloe vera, and basil also have anticlavic effects due to their ability to inhibit amylase. ¹⁴ Alpha-Glucosidase inhibitors (acarbose, miglitol, and voglibose) inhibit lysosomal withdraw α-glucosidase activity by structurally resembling saccharides (i.e., carbohydrate binding sites on α-glucosidase). Therefore, the carbohydrate binding region of α-glucosidase interacts with all of these forms of inhibitor. However, many of the common adverse effects associated with the use of prescribed anti-diabetic agents include liver disorders including lactic acidosis; gastrointestinal symptoms including abdominal cramping, flatulence, and diarrhea. Current medication's negative side effects have resulted in efforts to develop alternative forms of lysosomal α-glucosidase inhibitor technology with reduced adverse reactions. Therefore, in this study, phytochemicals from Indian plant species were selected on the basis of literature survey based on their potential to inhibit α-glucosidase. The ligand-receptor interactions were analyzed using in silico methods. Ligand structures were optimized using Chem Sketch, and the receptor-ligand interactions were visualized using Discovery Studio Visualizer. ^15,16

MATERIALS AND METHODS

Materials

Databases, including pdb, DrugBank, PubChem, as well as using PyRx and Discovery Studio Visualizer as our software tools. The PDB (Protein Data Bank) started as a single repository for storage of Structure Data for macromolecules and opened its doors at BNL in 1971 to create one central location on the planet that contained all the Structural Data on all the macromolecules found till today. All of the X-ray Crystallography determined Structural Data and six other types of Structural Data can be found in the PDB. ChemSketch is the leading all-purpose Chemical Drawing and Graphics Software Package from ACD/Labs for Chemists to Draw Molecules, Drawing and/or Writing Reactions, creating (proof Calculating) Professional Presentations and Reports. In addition to creating drawings of compounds, ChemSketch can convert structures from SMILES notation to structure and vice versa. In our research we used Discovery Studio Visualizer to visualize the interaction between receptor protein and ligand. We also used FT-IR and HNMR Spectroscopy to characterize the compounds from synthetic procedures.

Methods

In silico studies (Docking Studies)

Protein and Ligand preparation

We have conducted an analysis using molecular docking in order to determine how the molecules interact with the active site of human diabetic α-glucosidase, which is a type of lysosomal α-glucosidases (PDB ID: 5KZX) having a 2.0 Å resolution (high quality). The Three Dimensional (3D) crystal structure for α-glucosidases was downloaded from the RCSB Protein Data Bank (PDB, RCSB) (https://www.rcsb.org/). The crystallographic inhibitor, ions (Mg + , K + ) and the water molecules further than the active site were deleted and assigned bond orders, polar hydrogens were added, Checked and repaired missing atoms in the protein crystal structure, edited histidine hydrogens, assigned Radii, added Kolmann charges (-480.326), Gasteiger charges (-22.4268) using AutoDock Vina.

Phytochemicals are selected from a plant source that has enzyme inhibition properties for alpha-Glucosidase. Previously reported 100 phytochemicals possessing α-glucosidase enzyme inhibitory activity were chosen. The SDF files of respective phytochemicals were retrieved from the PubChem database. All SDF files of ligands were imported into PyRx. The ligands were then converted to PDBQT format using PyRx's open babel plugin and used for molecular docking.

Molecular docking

The purpose of molecular docking is to predict the position, contact, and conformation of a ligand molecule within a target molecule binding site, which is typically a large macromolecule. A molecular docking study was performed using Autodock vina of PyRx 0.8 to check the binding interactions with residues at the active site of the target protein (PDB:5KZX). In PyRx's Vina workspace, the grid box for PDB: 5KZX was selected to cover the binding site residues with centers X:1.3148, Y:18.1751, Z:17.7808, and dimensions X:95.7864, Y:92.5980, Z:107.2510. The level of exhaustiveness was set to default 8. BIOVIA Discovery Studio 2020 was used to visualize docking interactions as well as analyze saved poses.

Drug likeliness and pharmacokinetic prediction

The loss of drugs due to poor pharmacokinetics in drug development procedures results in higher development costs. Screening of potential drugs has been improved by the accessibility of in silico pharmacokinetic tools. A molecule's physicochemical properties, which are crucial factors that influence a molecule's effectiveness, safety, or metabolism, can be predicted using Lipinski's rule of five. A drug must have MW<500, logP<5, HBA≤ 10, HBD≤5. The features of a molecule's ADME (absorption, distribution, metabolism, and excretion) are that determine its Pharmacokinetic profile.

Synthesis of selected compounds

All of the reagents used were reagent-grade and purified as necessary. Melting points were determined with a melting point apparatus (digital), Lab India. The FTIR (Fourier Transform Infrared Spectroscopy) spectra for all test compounds were taken by Shimadzu using FTIR spectroscopy. The Nuclear Magnetic Resonance (NMR) spectra for all test compounds were obtained on a Bruker DRX-300 and used Dimethyl Sulfoxide (DMSO) as the solvent and Tetramethylsilane (TMS) as the standard for calibration. The mass spectrometric data for all test compounds were obtained by Shimadzu using LCMS 2010A. The thin-layer chromatography results were obtained using methodology.

Procedure for the microwave-assisted synthesis of isoxazole chalcone derivatives (SP1-SP6)

The synthetic scheme (Figure 1) was developed after designing the six target molecules (SP1-SP6). Following the design, we synthesized these compounds according to the proposed synthetic route. Initially, Dimethylformamide (DMF) (2.5 mol) was added to a thoroughly dried Round-Bottom Flask (RBF) at room temperature, followed by the dropwise addition of Phosphoryl Chloride (POCl₃) (7 mol) under continuous stirring for 15 min. Subsequently, N-phenylacetamide was introduced at room temperature, and the reaction mixture was heated at 75ºC for 2 hr. Upon completion, the reaction mixture was poured into ice-cold water, and the resulting precipitate was collected by filtration. In a separate round-bottom flask, six ketones (bromoacetophenone, 4-chlorobenzophenone, p-nitroacetophenone,3-methyl-1-phenylpyrazone-5-one, dichloroacetophenone, and 3-nitroacetophenone) were dissolved in 95% ethanol (20 mL) along with substituted aromatic aldehyde (0.001 mol). To this, 10 mL of 60% aqueous sodium hydroxide solution was added dropwise. The reaction mixture was stirred at 5-10ºC for 2 hr, then poured over crushed ice, and acidified with dilute Hydrochloric Acid (HCl). The resulting solid was collected, washed, and dried. Next, a mixture of chalcone (0.01 mol), hydroxylamine hydrochloride (0.01 mol), and sodium acetate in ethanol (25 mL) was subjected to microwave irradiation at 210 W for 10-5 min at 90-100ºC. The reaction mixture was then poured into ice-cold water, and the precipitate was collected by filtration, washed, and dried for further characterization.

In vitro analysis of anti-diabetic activity using α-amylase enzyme inhibition assay

In this step, 500 µL of the test compound (1 mM) was mixed with 500 µL of 0.1 M phosphate buffer (pH 6.9) containing α-amylase enzyme (fungal diastase, 0.5%). The reaction mixture was incubated at 25ºC for 10 min. Subsequently, 500 µL of a 1% starch solution in 0.1 M phosphate buffer (pH 6.8) was added, and the mixture was further incubated at 25ºC for 10 min. For the control, the same procedure was followed, except 500 µL of enzyme was replaced by an equal volume of buffer. After the incubation period, 1000 µL of di-nitrosalicylic acid reagent was added to both the test (concentration 1mg/mL) and control mixtures. The reaction mixtures were then placed in a boiling water bath for 10 min and allowed to cool. The absorbance of each sample was measured at 540 nm using a spectrophotometer. The percentage inhibition of α-amylase enzyme was calculated using the following formula:

In vitro analysis of anti-diabetic activity usingα-glucosidase inhibition activity

The α-glucosidase inhibitory potential of the compounds was evaluated using a standard method with minor modifications. Briefly, 500 μL of the test compounds, 50 μL of glutathione, and 10 μL of α-glucosidase in phosphate buffer were added to a 96-well plate and incubated at 37ºC for 15 min. After incubation, 20 μL of P-Nitrophenyl-α-D-Glucopyranoside (P-NPG) (5 mM) was introduced, and the mixture was maintained at 37ºC for an additional 15 min. The reaction was terminated by adding 50 μL of Na₂CO₃ (0.1 M) to the reaction mixture. A blank sample, which lacked α-glucosidase, was prepared similarly to the test samples (concentration 1mg/mL). To serve as a control, the experiment was conducted in triplicate (n=3) without the test compound. The absorbance of the resulting solutions was measured at 400 nm. The α-glucosidase activity was quantified by measuring the amount of p-nitrophenol produced, with acarbose used as a positive control.

RESULTS AND DISCUSSION

In silico studies

All the synthesized derivatives were docked against target proteins and compared with phytochemicals. The phytochemicals exhibited docking scores ranging from -7.2 to -9.8 kcal/mol. Similarly, the synthesized derivatives showed docking scores within the range of -8.1 to -9.2 kcal/mol. The interactions of phytochemicals with amino acid residues are detailed in Table 1. Overall, the docking scores of the synthesized derivatives with the target proteins were higher, indicating a significant affinity between the synthesized compounds and the target proteins (Tables 2 and 3).

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Drug likeliness and pharmacokinetic prediction

The drug likeliness and pharmacokinetic properties of the synthesized compounds (SP1-SP6) were predicted using the free Swiss ADME server online (http://www.swissadme.ch). As reference drugs, all of the examined compounds (SP1-SP6) do not deviate from the Lipinski rule of 5 (MW< 500, logP<5, HBA≤10, HBD≤5). Since their values lie within the normal range (Table 4). Thus, these compounds could be considered lead compounds.

Physical characteristics of synthesized compounds

SP1 (2-bromo-1-{4-[5-(quinolin-3-yl)-4,5-dihydrofuran-3-yl]phenyl}ethan-1-one)

S Yield: 86%; Yellowish white solid; mp. 98-100ºC; R_f: 0.72 (chloroform and DMSO); FTIR (KBr, ν_max, cm⁻¹): 3233 (N-H), 1666 (C=O), 1594 (C-C Stretch), 1306 (C-N), 1008 (C-O), 760 (C-Br); ¹H-NMR spectrum (400MHz, CDCl₃): δ 2.278 (s, 2H, CH₂ Br), 7.266, 7.402, 7.422, 7.510, 7.503, 7.487, and 7.481 aromatic protons in structures (Figures 2 and 3). (Figures 2 and 3).

SP2 (1-{3-nitro-5-[5-(quinolin-3-yl)-4,5-dihydrofuran-3-yl]phenyl}ethan-1-one)

Yield: 88%; Greyish solid; mp. 90-92ºC; R_f: 0.78 (chloroform and DMSO); FTIR (KBr, ν_max, cm⁻¹): 3234 (N-H), 1668 (C=O), 1523 (C-C Stretch), 1349 (C-N); ¹H-NMR spectrum (400MHz, CDCl₃): δ 2.168 (C-H alkyl), 10.345, indicative of the acid group, with aromatic protons at δ=7.729, 7.529, 7.510, and 7.489 aromatic protons in structures.

SP3 (1-{2,4-dichloro-3-[5-(quinolin-3-yl)-4,5-dihydrofuran-3-yl]phenyl}ethan-1-one)

Yield: 84%; Yellowish white; mp. 72-74ºC; R_f: 0.82 (chloroform and DMSO); FTIR (KBr, ν_max, cm⁻¹): 3210 (N-H stretch), 1596 (C=O), 1309 (C-N stretch), 1484 (C-C), 1054 (C-O), and754 (C-Cl); ¹H-NMR spectrum (400MHz, CDCl₃):δ 2.254 (C-H alkyl),9.378 (3=CH, 1-benzene, 2-substituted benzimidazole), aromatic protons at δ=7.493, 7.488, 7.472, and 7.467 (present on the phenyl ring).

SP4 (4-chlorophenyl){3-[5-(quinolin-3-yl)-4,5-dihydrofuran-3-yl]phenyl}methanone)

Yield: 78%; Greyish white; mp. 90-92ºC; R_f: 0.85 (chloroform and DMSO); FTIR (KBr, ν_max, cm⁻¹): 3295 (N-H), 1652 (C=O), 1311 (C-N), 914 (C-O), 687 (C-Cl), ¹H-NMR spectrum (400MHz, CDCl₃):δ 7.701, 7.683, 7.454, 7.466, and 7.673 (on the phenyl ring), and amide protons at δ=9.459 and 9.067 (3=CH, 1-benzene, 2-substituted benzimidazole), absence of H from alkyl C-H confirm the absence of alkyl hydrogen that can be seen in SP2 and SP3 (due to presence of alkyl CH₂ attached to C=O.

SP5 (1-{4-nitro-2-[5-(quinolin-3-yl)-4,5-dihydrofuran-3-yl]phenyl}ethan-1-one)

Yield: 72%; Greyish black; mp. 210-214ºC; R_f: 0.87 (chloroform and DMSO); FTIR (KBr, ν_max, cm⁻¹): 1297 (C-N), 3304 (N-H), 1670 (C-C), 1520 (C-NO₂). ¹H-NMR spectrum (400MHz, CDCl₃):δ2.153-2.170 (C-H alkyl), 7.123, 7.265, 7.384, 7.556, 7.683, 7.779 (aromatic protons) 8.037, corresponding to the 4=CH group (benzene of basic benzimidazole).

α-amylase enzyme inhibition assay

The % α-amylase enzyme inhibition was calculated using an α-amylase inhibitory assay, with Acarbose used as the standard, exhibiting a 93.47% inhibition. The inhibition values of the synthesized compounds were compared with acarbose. Among all the synthesized compounds, SP2 and SP4 demonstrated the highest inhibition, both showing 90.57%. SP5 and SP6 exhibited 89.13% and 89.85% inhibition, respectively. The lowest inhibition was observed with SP3, which showed an inhibition of 88.40% (Table 5).

α -glucosidase inhibition assay

The α-glucosidase inhibitory potential of synthesized compounds was determined in comparison to the standard Acarbose. In brief, the % inhibition shown by the entire compound was observed in the range of 88.4 to 90.6% Table 5. The α-glucosidase % of compound SP2 and SP4 was found to be more which was comparable to the acarbose (93.47±6.8%).

Figure 4 represents the histogram showing the significance level for the data as ***p<0.0001,*p<0.001,*p<0.01, ns p>0.05.

Chemical code	Structure	Binding affinity (Kcal/mol)	Interacting residues	Interaction type
SP1		-8.1	PRO89,LEU831,LYS697, LEU701	Pi-Pi stacked
SP2		-8.9	PHE525 PHE525,TRP481,TRP376.	H Bond Pi-Pi stacked
SP3		-8.8	ARG854 TRP746,LEU369, VAL723 HIS708	H Bond Pi-Pi stacked Pi-Alkyl
SP4		-8.7	ASP616 PHE525,TRP481,PHE649,TRP376	H Bond Pi-Pi stacked
SP5		-9.2	HIS584,ARG608,TYR360 HIS717,ARG594	H Bond Pi-Pi stacked

CONCLUSION

This study successfully used a multi-faceted approach of in silico, synthetic and in vitro methods to create and examine new isoxazole chalcone derivatives (SP1-SP6) as α-glucosidase and α-amylase anti-diabetic agents. Molecular docking studies provided evidence that the compounds synthesized during this investigation had strong binding affinity and positive interactions with the active site residues of the target protein PDB ID: 5KZX that were similar or greater in affinity to the selected phytochemicals. Overall, the predicted pharmacokinetics of the compounds indicate they pass all aspects of Lipinski's rule of five and are therefore good drug-like candidates for further oral formulation as anti-diabetic agents.

All derivatives were synthesized, the successful formation of which was confirmed through FTIR and ^1H-NMR spectroscopy, which established the compounds' structural integrity as well as existed confirmatory functional groups. In vitro enzyme assays were also in line with computational modeling and exhibited significant inhibition of both α-amylase and α-glucosidase activity of SP2 (1-{3-nitro-5-[5-(quinolin-3-yl)-4,5-dihydrofuran-3-yl] phenyl} ethan-1-one) and SP4 (4-chlorophenyl){3-[5-(quinolin-3yl)-4,5-dihydrofuran-3-yl] phenyl} methanonein a manner comparable to systematic drug acarbose. Overall, these results suggest that the new synthetic compounds, in particular SP2 and SP4, have great potential as potent inhibitors that may modulate postprandial hyperglycemia.

In summary, the use of computational modeling, rational design, and biological assessment has enabled us to identify promising lead candidates with potential use in type 2 diabetes mellitus. Further studies including detailed mechanistic investigation, in vivo efficacy, and toxicity are needed for further evaluation of their therapeutic utility. This study ultimately lays the groundwork for the generation of structurally novel and biologically active anti-diabetic agents derived from an isoxazole chalcone scaffold.

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n=3.

Compound	3D interaction diagram	2D interaction diagram
SP2
SP3
SP4
SP5

SUMMARY

This study employed a combined in silico, synthetic, and in vitro approach to develop novel isoxazole chalcone derivatives (SP1-SP6) as potential anti-diabetic agents targeting α-glucosidase and α-amylase enzymes. Molecular docking studies showed strong binding affinity of the synthesized compounds with the target protein PDB ID: 5KZX, indicating promising inhibitory potential. The predicted pharmacokinetic properties satisfied Lipinski's rule of five, suggesting good drug-likeness for oral administration. Structural confirmation of the synthesized derivatives was achieved using FTIR and ^1H-NMR spectroscopy. In vitro enzyme inhibition studies demonstrated significant activity, with SP2 and SP4 showing inhibition comparable to the standard drug acarbose. Overall, the findings suggest that these compounds, particularly SP2 and SP4, may serve as promising candidates for further development as anti-diabetic agents to control postprandial hyperglycemia.

ABBREVIATIONS

DM

Diabetes mellitus

SP

Synthesized Product

ADME

Absorption, Distribution, Metabolism, and Excretion

DMSO

Dimethylsulfoxide

NMR

Nuclear Magnetic Resonance

FTIR

Fourier Transform Infrared Spectroscopy

SAR

Structure-Activity Relationship

P-NPG

p-nitrophenyl-α-D-glucopyranoside.

Phytochemicals Binding affinity (Kcal/mol) Interacting residues Interaction type Apigenin -8.9 PRO669, ARG702 Vander Waals PHE362, THR711, TYR710, HIS708, LEU706, TYR668. Conventional H bond HIS714, MET363 Carbon H bond TRP746, PRO640, LEU641, PRO364. Pi-Pi T-shaped LEU369 Pi-alkyl VAL723 Pi-sigma Scirpusin A -8.9 SER523, PHE525, ARG600, ASP404, TRP516, ILE441, TRP613. Vander Waals ASP282, TRP481, HIS674, ASP616, LEU677, SER676, LEU678, TRP618. Conventional H Bond ASP518 Pi-anion MET519 Pi-sulfur TRP376 Pi-pi stacked PHE649, ALA284 Pi-Pi T-shaped LEU650 Pi-alkyl Scirpusin B -8.7 PHE525, ARG600, LEU405, ASP404, ILE441, TRP516, HIS674, SER523. Vander Waals TRP481, TRP613, ASP616, LEU677, SER676, LEU678, TRP618. Conventional H bond ASP282, ASP518 Pi-anion LEU650 Pi-sigma MET519 Pi-sulfur TRP376 Pi-pi stacked PHE649 Pi-Pi T-Shaped ALA284 Pi-Alkyl Isoflavone -8.6 PHE362, TYR710, HIS708. Vander Waals PRO669, LEU706, HIS714. Conventional H Bond VAL723 Pi-Sigma TRP746 Pi-Pi T-Shaped PRO364, LEU369, PRO640, LEU641. Pi-Alkyl Spergulin A -8.6 PRO595, ARG594, GLU869, LEU865, PHE362, HIS717, ARG608, TYR360, GLY359, ASP356, PRO198.

Vander Waals HIS584, LEU868, VAL867, SER864, GLU866.

ACKNOWLEDGEMENT

The author would like to express sincere gratitude to Ashokrao Mane College of Pharmacy, Peth-Vadgaon, for supporting this work.

CONFLICT OF INTEREST

The authors declare that there is no conflict of interest.