Structural Modification of Aceclofenac to Design Enhanced COX-2 Inhibitors: A Medicinal and Toxicological Study

Aceclofenac (ACF) is a nonsteroidal anti-inflammatory drug (NSAID), prescribed for treating pain and inflammation. It prevents the synthesis of prostaglandin E2 by inhibiting the activity of cyclooxygenases (COX). Upon its oral administration, evidence of gastric ulcers, hypersensitivity reactions, vasculitis, nephritis, premature fetal deliveries, etc., has been reported. So, scientists feel the necessity to look for alternatives with enhanced activity along with minimized side effects. Structural modification serves as a gold standard for such discovery. We aimed to develop a superior alternative to ACF with minimal adverse effects. We altered the fundamental structure of ACF by incorporating various functional groups. Density functional theory (DFT) was implemented with the B3LYP/6-31g ([Formula: see text], [Formula: see text] basis set for geometrical optimization of the structures. Thermodynamics, molecular orbitals, electrostatic potentials, and vibrational frequencies of the structures were analyzed. We conducted molecular docking and molecular dynamics simulation (MD) studies of the derivatives on the prostaglandin synthase protein (COX-2). PASS and ADMET were investigated in order to forecast their pharmacological properties. Our derivatives exhibited improved physicochemical properties and binding affinity. For their optimal performances, ACF19, ACF10, ACF14, and ACF23 were selected, each with a docking score of −8.3 kcal/mol, −8.1 kcal/mol, −8.1 kcal/mol, and −8.1 kcal/mol, respectively. MD simulation further confirmed the stable tendencies of the selected derivative complexes. The derivatives showed decreased toxicity and enhanced pharmacological properties. Therefore, the study has identified potentially safer drug candidates that could serve as alternatives to ACF.

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Journal
Journal of Computational Biophysics and Chemistry
Published
2025-05-09
DOI
https://doi.org/10.1142/s2737416525500711
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50
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article

Structural Modification of Aceclofenac to Design Enhanced COX-2 Inhibitors: A Medicinal and Toxicological Study

Sadab Sipar Ibban, M. R. O. Khan Noyon, Jannatul Naima, Md Kamrul Hasan et al.
1 citations
Journal of Computational Biophysics and Chemistry
Computational Drug Discovery Methods
1.50
article

Structural Modification of Aceclofenac to Design Enhanced COX-2 Inhibitors: A Medicinal and Toxicological Study

Sadab Sipar Ibban, M. R. O. Khan Noyon, Jannatul Naima, Md Kamrul Hasan, Monir Uzzaman, Md. Shohel Hossain, Mustary Anjum Maria, Anika Tahcin, Mahmudul Hasan Shuvo, Sharmin Sultana Shimu
article en
1 citations

Abstract

Aceclofenac (ACF) is a nonsteroidal anti-inflammatory drug (NSAID), prescribed for treating pain and inflammation. It prevents the synthesis of prostaglandin E2 by inhibiting the activity of cyclooxygenases (COX). Upon its oral administration, evidence of gastric ulcers, hypersensitivity reactions, vasculitis, nephritis, premature fetal deliveries, etc., has been reported. So, scientists feel the necessity to look for alternatives with enhanced activity along with minimized side effects. Structural modification serves as a gold standard for such discovery. We aimed to develop a superior alternative to ACF with minimal adverse effects. We altered the fundamental structure of ACF by incorporating various functional groups. Density functional theory (DFT) was implemented with the B3LYP/6-31g ([Formula: see text], [Formula: see text] basis set for geometrical optimization of the structures. Thermodynamics, molecular orbitals, electrostatic potentials, and vibrational frequencies of the structures were analyzed. We conducted molecular docking and molecular dynamics simulation (MD) studies of the derivatives on the prostaglandin synthase protein (COX-2). PASS and ADMET were investigated in order to forecast their pharmacological properties. Our derivatives exhibited improved physicochemical properties and binding affinity. For their optimal performances, ACF19, ACF10, ACF14, and ACF23 were selected, each with a docking score of −8.3 kcal/mol, −8.1 kcal/mol, −8.1 kcal/mol, and −8.1 kcal/mol, respectively. MD simulation further confirmed the stable tendencies of the selected derivative complexes. The derivatives showed decreased toxicity and enhanced pharmacological properties. Therefore, the study has identified potentially safer drug candidates that could serve as alternatives to ACF.

Journal of Computational Biophysics and ChemistryVol. 25(06)
International Islamic University Chittagong (BD), Mie University (JP), University of Dhaka (BD), Bangladesh Agricultural University (BD), Gono University (BD), Dhaka University of Engineering & Technology (BD), University of Chittagong (BD), University of Rajshahi (BD)
Openalex Percentile: Top 17%
Computational Drug Discovery Methods
1.50
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