Computational Analysis of Arginine Deiminase Sequences to Provide a Guideline for Protein Engineering

Author(s): Mahboubeh Zarei, Mohammad Reza Rahbar, Navid Nezafat, Manica Negahdaripour, Mohammad Hossein Morowvat, Younes Ghasemi*.

Journal Name: Current Proteomics

Volume 17 , Issue 2 , 2020

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Abstract:

Background: Arginine deiminase of Mycoplasma hominis, an arginine catabolizing enzyme, is currently in clinical trial for the treatment of arginine auxotrophic cancers. However, some drawbacks such as instability and antigenicity have limited its application as a protein drug. Arginine Deiminase (ADI) belongs to the guanidino-group modifying enzyme superfamily. Despite differences in the primary amino acid sequences of various members of this superfamily, the folding and secondary structures are conserved in all members. Despite structural similarities, ADIs in various species have different levels of catalytic activity and physicochemical properties due to the differences in their primary amino acid sequences. Therefore, investigating and comparing sequences between different ADI producing bacterial strains could be helpful in the rational engineering of ADI.

Objective: In the current research, we used an in-silico approach to characterize and classify the available reviewed protein sequences of ADI.

Results: 102 ADI sequences from SwissProt database were extracted. Subsequently, based on clustering analyses, the sequence sets were divided into five distinct groups. Different physicochemical properties, solubility, and antigenicity of the enzymes were determined. Some ADI sequences were introduced as well-suited candidates for protein engineering; Lactobacillus fermentum ADI for low pI value, Mycobacterium avium ADI for high aliphatic index, Bacillus licheniformis ADI for low GRAVY index, Bradyrhizobium diazoefficiens ADI for low antigenicity and high stability index, and among Mycoplasma ADIs, Mycoplasma arthritidis ADI for high stability and aliphatic index, and Mycoplasma capricolum for low antigenicity.

Keywords: Arginine deiminase, protein engineering, in silico, antitumor activity, sequence-based classification, pH.

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Article Details

VOLUME: 17
ISSUE: 2
Year: 2020
Page: [132 - 146]
Pages: 15
DOI: 10.2174/1570164616666190619111852
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