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Bioinformatic Insights on Target Receptors of Amiodarone in Human and Acanthamoeba castellanii

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Background: Amiodarone is prescribed for certain cardiac arrhythmias in current medical practice. The drug targets and inhibits voltage dependent sodium (Na+v), calcium (Ca+2v), potassium (K+v) channels, enzymes like cytochrome P450 and oxidosqualene cyclase. Past studies have shown that amiodarone exerts antiparasitic effects against Trypanosoma cruzi and Acanthamoeba castellanii.

Objectives: The presence of aforementioned targets and the type of cell death induced by amiodarone in pathogenic eukaryotes like Acanthamoeba castellanii remains to be established. We inferred the presence of homologous targets of amiodarone in A. castellanii compared with humans.

Methods: This study used bioinformatics exploration for amino acid sequence homology, ligand binding attribute predictions, 3D structural model development, and experimental assays that highlight similarity between certain target proteins in Acanthamoeba as compared to humans.

Results: The sequence identity scores for amino acids and 3D models show that A. castellanii expresses similar types of targets of amiodarone like Na+v - K+1v channels, cytochrome P450 3A4, and lanosterol synthase (oxidosqualene cyclase). We show that even though human like L-type and two pore Ca+2 channels are present in A. castellanii, there was no evidence of the expression of T-type voltage dependent Ca+2 channels. Growth assays showed amoebicidal and amoebistatic effects at doses of 40-80μg/ml.

Conclusion: The existing bioinformatics tools, ligand binding attribute prediction, and model building offer a specific method to establish homology of proteins, discover drug targets, and facilitate the investigation of the evolution of several types of cardinal ion channels from unicellular eukaryotes to multicellular species as humans.
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Keywords: Acanthamoeba castellanii; Bioinformatics computational tools; Trypanosoma cruzi; amiodarone; free-living amoeba; model unicellular eukaryotes; structural homology

Document Type: Research Article

Publication date: October 1, 2017

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