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TNF-? (tumor necrosis factor alpha) is a pro-inflammatory cytokine that can initiate a chain inflammatory reaction and its activity has been related to the inflammatory intestinal disease. In a previously conducted MRI (Magnetic Resonance Imaging) study, the coumarin group of metabolites had noticeable antiinflammatory effects, inhibiting TNF-? action and stopping the inflammatory chain reaction. Treatments using natural compounds have existed for thousands of years, having the benefit of being cheap to obtain. For example, Statin is probably the more famous compound used to treat high cholesterol and heart disease. Coumarins are naturally occurring substances on many plants, like Tonka Beans and Vanilla Grass, and it’s used as a defense against predators, suppressing the appetite of animals that ingest it, preventing them from eating the whole plant. One of its derivatives, Warfarin, is prescribed as an anticoagulant to prevent the formation of blood clots, serving as a therapy for pulmonary embolism. In this work we used molecular docking enhanced by convolutional neural networks (CNN) and molecular dynamics (MD) simulations to investigate the interaction and the binding pocket between coumarin and its derivatives, with TNF-?. The 3D models used for this process where obtained from PDB for the TNF-? protein, and pubchem for the coumarinic ligands. The docking was performed using Gnina, a fork of Smina that uses convoluted neural networks to predict the best scoring pose and attributes a score to the poses; this process was performed multiple times until convergence. A simulation box was built to mimic physiologic conditions, solvated with water, ionized with NaCl and equilibrated, as a preparation for the dynamics simulations. The results agreed with experimental studies, such as the docking site and its stability, the predominant type of interaction of each coumarin derivative, and the energy of the interactions.
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