Author

Hamid Bouseber

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Sep 2026

Interpretable Machine Learning for Structure–Activity Relationship Modeling of Cyclooxygenase-1 Inhibitors

An interpretable computational framework is developed for modeling COX-1 inhibitor activity and characterizing prioritized compounds at the molecular level by integrating QSAR modeling, explainable artificial intelligence, molecular docking, molecular dynamics, and MM/GBSA calculations to investigate COX-1 inhibitors.

Hamid Bouseber, Mustapha Cherkaoui · Chemistry Africa · 0 citations