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Current Proteomics

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ISSN (Print): 1570-1646
ISSN (Online): 1875-6247

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Research Article

Bioinformatics-Based Characterization of Proteins Related to SARS-CoV- 2 Using the Polarity Index Method® (PIM®) and Intrinsic Disorder Predisposition

Author(s): Carlos Polanco*, Vladimir N. Uversky, Guy W. Dayhoff, Alberto Huberman, Thomas Buhse, Manlio F. Márquez, Gilberto Vargas-Alarcón, Jorge Alberto Castañón-González, Leire Andrés, Juan Luciano Dı́az-González and Karina González-Bañales

Volume 19, Issue 1, 2022

Published on: 06 January, 2021

Page: [51 - 64] Pages: 14

DOI: 10.2174/1570164618666210106114606

Price: $65

Abstract

Background: : The global outbreak of the 2019 novel Coronavirus disease (COVID-19) caused by infection with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which appeared in China at the end of 2019, signifies a major public health issue at the current time.

Objective: The objective of the present study is to characterize the physicochemical properties of the SARS-CoV-2 proteins at a residues level, and to generate a “bioinformatics fingerprint” in the form of a “PIM profile” created for each sequence utilizing the Polarity Index Method (PIM), suitable for the identification of these proteins.

Methods: Two different bioinformatics approaches were used to analyze sequence characteristics of these proteins at the residues level, an in-house bioinformatics system PIM, and a set of the commonly used algorithms for the prediction of protein intrinsic disorder predisposition, such as PONDR VLXT, PONDR VL3, PONDR VSL2, PONDR FIT, IUPred_short and IUPred_long. The PIM profile was generated for four SARS-CoV-2 structural proteins and compared with the corresponding profiles of the SARS-CoV-2 non-structural proteins, SARS-CoV-2 putative proteins, SARS-- CoV proteins, MERS-CoV proteins, sets of bacterial, fungal, and viral proteins, cell-penetrating peptides, and a set of intrinsically disordered proteins. We also searched for the UniProt proteins with PIM profiles similar to those of SARS-CoV-2 structural, non-structural, and putative proteins.

Results: We show that SARS-CoV-2 structural, non-structural, and putative proteins are characterized by a unique PIM profile. A total of 1736 proteins were identified from the 562,253 “reviewed” proteins from the UniProt database, whose PIM profile was similar to that of the SARS-CoV-2 structural, non-structural, and putative proteins.

Conclusion: The PIM profile represents an important characteristic that might be useful for the identification of proteins similar to SARS-CoV-2 proteins.

Keywords: Severe acute respiratory syndrome 2 proteins, antimicrobial peptides, structural proteomics, bioinformatics, intrinsic disorder predisposition, PIM profile.

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