Computer-aided Discovery of Novel COX-2 Inhibitors for Anti-inflammatory Therapy Using Pharmacophore Modelling, Molecular Docking, ADMET, and Virtual Screening

Authors

  • Usama Yousafzai Department of Biomedical Engineering and Sciences, School of Mechanical & Manufacturing Engineering, National University of Sciences and Technology, Islamabad, Pakistan
  • Najia Javed Department of Biomedical Engineering and Sciences, School of Mechanical & Manufacturing Engineering, National University of Sciences and Technology, Islamabad, Pakistan
  • Syed Luqman Ali Department of Biochemistry, Abdul Wali Khan University, Mardan, Khyber Pakhtunkhwa, Pakistan
  • Awais Ali Department of Biochemistry, Abdul Wali Khan University, Mardan, Khyber Pakhtunkhwa, Pakistan
  • Amir Hamza Department of Microbiology, Abdul Wali Khan University, Mardan, Khyber Pakhtunkhwa, Pakistan

DOI:

https://doi.org/10.64229/md3sjz95

Keywords:

Tanshinone IA, COX-2 Inhibitors, Pharmacophore Modelling, Molecular Docking, Anti-inflammatory therapy

Abstract

Cyclooxygenase-2 (COX-2) is a central enzyme in inflammation and a validated target for anti-inflammatory drug development. However, many existing COX-2 inhibitors cause gastrointestinal and cardiovascular side effects, necessitating safer alternatives. This study employed a computer-aided drug discovery approach integrating pharmacophore modeling, molecular docking, and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis to identify natural COX-2 inhibitors from 72 sesquiterpene lactones. A validated pharmacophore model (AUC = 0.77) screened 33 potential inhibitors, and molecular docking revealed 13 compounds with strong binding affinities. Among them, Tanshinone IA showed the highest binding affinity (-10.6 kcal/mol), surpassing celecoxib (-9.5 kcal/mol). ADMET profiling indicated favorable pharmacokinetic properties, high gastrointestinal absorption, and low toxicity for most compounds. Overall, Tanshinone IA emerged as a promising, naturally derived COX-2 inhibitor with potential for safer anti-inflammatory therapy. These findings provide a computational foundation for future experimental validation and preclinical development of natural anti-inflammatory agents.

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Published

2025-12-22

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Vol. 1 No. 4 (2025)

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Copyright (c) 2025 Usama Yousafzai , Najia Javed , Syed Luqman Ali, Awais Ali , Amir Hamza (Author)

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