Antioxidant, anti-inflammatory, and anti-diabetic assessment of (2Z)-2(arylimino)-2Hchromene-3-carboxamides: An in vitro-in silico study by applying ANN-GA, MCDM, and RSM optimization techniques

This study investigates four novel iminocoumarin derivatives (3–6), previously synthesized and characterized, for their antioxidant, anti-inflammatory, and antidiabetic properties at different concentrations (12.5, 25, 50, 100, 200, 400, 800, and 1600 g/mL). Artificial neural network (ANN) approaches and response surface methodology (RSM) were used in a two-variable process that comprised iminocoumarins and concentrations to determine the impact of these compounds on the parameters that were monitored. The results indicated that the 2.2-diphenyl-1-picrylhydrazyl (DPPH) scavenging assay investigated the antioxidant activity of the synthesized compounds. The compounds expressed a remarkable DPPH inhibitory effect with IC₅₀ values in the range of 45.04 and 108.61 μg/ml. The anti-inflammatory activity was evaluated using an in vitro heat-induced hemolysis method. At 400 μg/ml, the percentage of erythrocyte hemolysis inhibition of these compounds ranged from 18.23 ± 0.18 % to 64.52 ± 0.13 %. The antidiabetic activity was determined in vitro by the alpha-glucosidase and alpha-amylase inhibitory effects. The synthesized compounds were found to be potent inhibitors of alpha-glucosidase with IC₅₀ values ranging between 111.25 μg/ml and 337.2 μg/ml and alpha-amylase with IC₅₀ values ranging between 101.84 μg/ml and 339.81 μg/ml. Additionally, the synthesized compounds underwent a molecular docking study against alpha-amylase. Moreover, there is a good correlation between experimental data and the ANN and RSM models. The R 2 values for the inhibition of DPPH, alpha-glucosidase, alpha-amylase, and inflammation are 99.50 %, 98.96 %, 99.69 %, and 99.84 %, respectively; it is demonstrating the artificial neural network model's notable better accuracy and excellent agreement with the experimental findings. Thereby, the prepared molecules could serve as potential agents for the development of more powerful and effective antioxidants, anti-inflammatories, and antidiabetic compounds. • Four (2Z)-2-(arylimino)-2Hchromene-3-carboxamides were synthesized. • All compounds showed potent antioxidant and anti-inflammatory activities. • All compounds exhibited good to moderate inhibitory activity of alpha-glucosidase and alpha-amylase. • Molecular docking against alpha-amylase was conducted. • Response surface and artificial neural network modeling techniques were applied to four new iminocoumarin derivatives. • ANN outperformed RSM in the prediction of iminocoumarin derivatives.

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Journal
Results in Chemistry
Published
2025-04-09
DOI
https://doi.org/10.1016/j.rechem.2025.102249
Citations
16
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
24.07
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article

Antioxidant, anti-inflammatory, and anti-diabetic assessment of (2Z)-2(arylimino)-2Hchromene-3-carboxamides: An in vitro-in silico study by applying ANN-GA, MCDM, and RSM optimization techniques

Mostefa Hani, Elhadj-Ahmed Koceir, Wassila Saiah, Ahmed Belaadi et al.
16 citations
Results in Chemistry
Computational Drug Discovery Methods
24.07
article

Antioxidant, anti-inflammatory, and anti-diabetic assessment of (2Z)-2(arylimino)-2Hchromene-3-carboxamides: An in vitro-in silico study by applying ANN-GA, MCDM, and RSM optimization techniques

Mostefa Hani, Elhadj-Ahmed Koceir, Wassila Saiah, Ahmed Belaadi, Aissa Laouissi, Amal Rabahi, Muhammad Imam Ammarullah, Hamza Saidi, Messaouda Boumaaza, Djamel Ghernaout, Yazid Chetbani
article en
16 citations

Abstract

This study investigates four novel iminocoumarin derivatives (3–6), previously synthesized and characterized, for their antioxidant, anti-inflammatory, and antidiabetic properties at different concentrations (12.5, 25, 50, 100, 200, 400, 800, and 1600 g/mL). Artificial neural network (ANN) approaches and response surface methodology (RSM) were used in a two-variable process that comprised iminocoumarins and concentrations to determine the impact of these compounds on the parameters that were monitored. The results indicated that the 2.2-diphenyl-1-picrylhydrazyl (DPPH) scavenging assay investigated the antioxidant activity of the synthesized compounds. The compounds expressed a remarkable DPPH inhibitory effect with IC₅₀ values in the range of 45.04 and 108.61 μg/ml. The anti-inflammatory activity was evaluated using an in vitro heat-induced hemolysis method. At 400 μg/ml, the percentage of erythrocyte hemolysis inhibition of these compounds ranged from 18.23 ± 0.18 % to 64.52 ± 0.13 %. The antidiabetic activity was determined in vitro by the alpha-glucosidase and alpha-amylase inhibitory effects. The synthesized compounds were found to be potent inhibitors of alpha-glucosidase with IC₅₀ values ranging between 111.25 μg/ml and 337.2 μg/ml and alpha-amylase with IC₅₀ values ranging between 101.84 μg/ml and 339.81 μg/ml. Additionally, the synthesized compounds underwent a molecular docking study against alpha-amylase. Moreover, there is a good correlation between experimental data and the ANN and RSM models. The R 2 values for the inhibition of DPPH, alpha-glucosidase, alpha-amylase, and inflammation are 99.50 %, 98.96 %, 99.69 %, and 99.84 %, respectively; it is demonstrating the artificial neural network model's notable better accuracy and excellent agreement with the experimental findings. Thereby, the prepared molecules could serve as potential agents for the development of more powerful and effective antioxidants, anti-inflammatories, and antidiabetic compounds. • Four (2Z)-2-(arylimino)-2Hchromene-3-carboxamides were synthesized. • All compounds showed potent antioxidant and anti-inflammatory activities. • All compounds exhibited good to moderate inhibitory activity of alpha-glucosidase and alpha-amylase. • Molecular docking against alpha-amylase was conducted. • Response surface and artificial neural network modeling techniques were applied to four new iminocoumarin derivatives. • ANN outperformed RSM in the prediction of iminocoumarin derivatives.

Results in ChemistryVol. 15
Diponegoro University (ID), University of Sciences and Technology Houari Boumediene (DZ), Ziane Achour University of Djelfa (DZ), University of Ha'il (SA), Eskisehir Technical University (TR), University of Guelma (DZ), University Mohamed El Bachir El Ibrahimi of Bordj Bou Arreridj (DZ), University of Blida (DZ), University of Skikda (DZ)
Clean water and sanitation
Openalex Percentile: Top 0%
Computational Drug Discovery Methods
24.07
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