Bioinformatics-based Characterization of the Sequence Variability of Zika Virus Polyprotein and Envelope Protein (E)

Carlos Polanco; Vladimir N Uversky; Alberto Huberman; Gilberto Vargas-Alarcón; Jorge Alberto Castañón González; Thomas Buhse; Enrique Hernández Lemus; Martha Rios Castro; Erika Jeannette López Oliva; Sergio Enrique Solís Nájera

doi:10.1177/11769343221130730

Bioinformatics-based Characterization of the Sequence Variability of Zika Virus Polyprotein and Envelope Protein (E)

Evol Bioinform Online. 2022 Oct 27:18:11769343221130730. doi: 10.1177/11769343221130730. eCollection 2022.

Affiliations

¹ Department of Electromechanical Instrumentation, Instituto Nacional de Cardiología "Ignacio Chávez," México City, México.
² Department of Mathematics, Faculty of Sciences, Universidad Nacional Autónoma de México, México City, México.
³ Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.
⁴ Protein Research Group, Institute for Biological Instrumentation of the Russian Academy of Sciences, Federal Research Center "Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences," Pushchino, Moscow Region, Russia.
⁵ Department of Biochemistry, Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán", México City, México.
⁶ Research Center, Instituto Nacional de Cardiología "Ignacio Chávez," México City, México.
⁷ Department of Critical Care Medicine, Hospital Juárez de México, México City, México.
⁸ Chemical Research Center, Universidad Autónoma del Estado de Morelos, Cuernavaca, Morelos, México.
⁹ Department of Computational Genomics, Instituto Nacional de Medicina Genómica, México City, México.
¹⁰ Departamento de Física, Facultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City, Mexico.

Abstract

Background: Zika virus, which is widely spread and infects humans through the bites of Aedes albopictus and Aedes aegypti female mosquitoes, represents a serious global health issue.

Objective: The objective of the present study is to computationally characterize Zika virus polyproteins (UniProt Name: PRO_0000443018 [residues 1-3423], PRO_0000445659 [residues 1-3423] and PRO_0000435828 [residues 1-3419]) and their envelope proteins using their physico-chemical properties.

Methods: To achieve this, the Polarity Index Method (PIM) profile and the Protein Intrinsic Disorder Predisposition (PIDP) profile of 3 main groups of proteins were evaluated: structural proteins extracted from specific Databases, Zika virus polyproteins, and their envelope proteins (E) extracted from UniProt Database. Once the PIM profile of the Zika virus envelope proteins (E) was obtained and since the Zika virus polyproteins were also identified with this profile, the proteins defined as "reviewed proteins" extracted from the UniProt Database were searched for the similar PIM profile. Finally, the difference between the PIM profiles of the Zika virus polyproteins and their envelope proteins (E) was tested using 2 non-parametric statistical tests.

Results: It was found and tested that the PIM profile is an efficient discriminant that allows obtaining a "computational fingerprint" of each Zika virus polyprotein from its envelope protein (E).

Conclusion: PIM profile represents a computational tool, which can be used to effectively discover Zika virus polyproteins from Databases, from their envelope proteins (E) sequences.

Keywords: PIM profile; Zika virus envelope proteins (E); Zika virus polyproteins; bioinformatics; intrinsic disorder predisposition; structural proteomics.