Competition Between Phenothiazines and BH3 Peptide for the Binding Site of the Antiapoptotic BCL-2 Protein

The study of proteins and mechanisms involved in the apoptosis and new knowledge about cancer's biology are essential for planning new drugs. Tumor cells develop several strategies to gain proliferative advantages, including molecular alterations to evade from apoptosis. Failures in apoptosis could contribute to cancer pathogenesis, since these defects can cause the accumulation of dividing cells and do not remove genetic variants that have malignant potential. The apoptosis mechanism is composed by proteins that are members of BCL-2 and cysteine-protease families. BH3-only peptides are the "natural" intracellular ligands of BCL-2 family proteins. On the other hand, studies have proved that phenothiazine compounds influence the induction of cellular death. To understand the characteristics of phenothiazines and their effects on tumoral cells and organelles involved in the apoptosis, as well as evaluating their pharmacologic potential, we have carried out computational simulation with the purpose of relating the structures of the phenothiazines with their biological activity. Since the tridimensional (3D) structure of the target protein is known, we have employed the molecular docking approach to study the interactions between compounds and the protein's active site. Hereafter, the molecular dynamics technique was used to verify the temporal evolution of the BCL-2 complexes with phenothiazinic compounds and the BH3 peptide, the stability and the mobility of these molecules in the BCL-2 binding site. From these results, the calculation of binding free energy between the compounds and the biological target was carried out. Thus, it was possible to verify that thioridazine and trifluoperazine tend to increase the stability of the BCL-2 protein and can compete for the binding site with the BH3 peptide.

Abstract licence: CC BY

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   GalaxyPepDock: a protein–peptide docking tool based on interaction similarity and energy optimization · 2015

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