Document Type
Article
Publication Date
2022
Digital Object Identifier (DOI)
https://doi.org/10.1177/11769343221130730
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.
Rights Information
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Evolutionary Bioinformatics, v. 18
Scholar Commons Citation
Polanco, Carlos; Uversky, Vladimir N.; Huberman, Alberto; Vargas-Alarcón, Gilberto; González, Jorge Alberto Castañón; Buhse, Thomas; Lemus, Enrique Hernández; Castro, Martha Rios; Oliva, Erika Jeannette López; and Nájera, Sergio Enrique Solís, "Bioinformatics-based Characterization of the Sequence Variability of Zika Virus Polyprotein and Envelope Protein (E)" (2022). Molecular Medicine Faculty Publications. 1049.
https://digitalcommons.usf.edu/mme_facpub/1049
