Identification of Novel and Selective Cyclooxygenase 2 (COX-2) Inhibitors: Comprehensive In-Silico Investigations.

INTRODUCTION

Cyclooxygenase-2 (COX-2) is a key enzyme in the inflammatory cascade and is implicated in chronic conditions, including arthritis, cancer, and cardiovascular diseases. Selective inhibition of COX-2, while sparing COX-1, is crucial to minimize gastrointestinal and renal side effects associated with non-selective NSAIDs. Computational drug discovery offers a strategic advantage for efficiently identifying novel, selective COX-2 inhibitors.

METHODS

Comprehensive in-silico studies were performed, which included ligand and structurebased screening, ML-based QSAR model, ADME/toxicity profiling, and molecular dynamics simulation. Five potent COX-2 inhibitors were used as query compounds to identify a dataset of 9213 similar molecules using the SwissSimilarity Server, which employed fingerprint-based screening of the ZINC database. Subsequently, these molecules were docked into the active sites of the COX-1 and COX-2 targets using AutoDock Vina to discover selective COX-2 inhibitors.

RESULTS

A pool of 236 compounds was selected based on docking scores (≤ -8.0 kcal/mol for COX-2 and ≥ -6.0 kcal/mol for COX-1), indicating potential selectivity. ADME/toxicity filtering narrowed the pool to 23 candidates. QSAR predictions identified 13 biologically active molecules, which were further evaluated for toxicity. Molecular dynamics simulations confirmed ten compounds with stable binding and favorable interaction profiles.

DISCUSSION: The integrated computational workflow enabled the identification of ten highly selective COX-2 inhibitors with promising pharmacokinetic and safety profiles. These candidates demonstrated strong potential for experimental validation and development into anti-inflammatory therapeutics.

CONCLUSION

The in-silico studies offer valuable insights into discovering selective COX-2 inhibitors for potential therapeutic and pharmacological applications. The findings provide a strong foundation for future experimental validation and the development of anti-inflammatory medicine.