Amino Acids Sequence-based Analysis of Arginine Deiminase from Different Prokaryotic Organisms: An In Silico Approach

Abstract

Background: Arginine deiminase is a bacterial enzyme, which degrades L-arginine. Some human cancers such as hepatocellular carcinoma (HCC) and melanoma are auxotrophic for arginine. Therefore, PEGylated arginine deiminase (ADI-PEG20) is a good anticancer candidate with antitumor effects. It causes local depletion of L-arginine and growth inhibition in arginineauxotrophic tumor cells. The FDA and EMA have granted orphan status to this drug. Some recently published patents have dealt with this enzyme or its PEGylated form.

Objective: Due to increasing attention to it, we aimed to evaluate and compare 30 arginine deiminase proteins from different bacterial species through in silico analysis.

Methods: The exploited analyses included the investigation of physicochemical properties, multiple sequence alignment (MSA), motif, superfamily, phylogenetic and 3D comparative analyses of arginine deiminase proteins thorough various bioinformatics tools.

Results: The most abundant amino acid in the arginine deiminase proteins is leucine (10.13%) while the least amino acid ratio is cysteine (0.98%). Multiple sequence alignment showed 47 conserved patterns between 30 arginine deiminase amino acid sequences. The results of sequence homology among 30 different groups of arginine deiminase enzymes revealed that all the studied sequences located in amidinotransferase superfamily. Based on the phylogenetic analysis, two major clusters were identified. Considering the results of various in silico studies; we selected the five best candidates for further investigations. The 3D structures of the best five arginine deiminase proteins were generated by the I-TASSER server and PyMOL. The RAMPAGE analysis revealed that 81.4%-91.4%, of the selected sequences, were located in the favored region of arginine deiminase proteins.

Conclusion: The results of this study shed light on the basic physicochemical properties of thirty major arginine deiminase sequences. The obtained data could be employed for further in vivo and clinical studies and also for developing the related therapeutic enzymes.

Keywords: Arginine deiminase; in silico; multiple sequence alignment; phylogenetic analysis; physicochemical properties; therapeutic proteins.