Evidence map›Paper›PMID 36330419›Full record

ArticleEvolutionary bioinformatics online2022

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

Abstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Carlos PolancoDepartment of Electromechanical Instrumentation, Instituto Nacional de Cardiología "Ignacio Chávez," México City, México.
Vladimir N UverskyDepartment of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.
Alberto HubermanDepartment of Biochemistry, Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán", México City, México.
Gilberto Vargas-AlarcónResearch Center, Instituto Nacional de Cardiología "Ignacio Chávez," México City, México.
Jorge Alberto Castañón GonzálezDepartment of Critical Care Medicine, Hospital Juárez de México, México City, México.
Thomas BuhseChemical Research Center, Universidad Autónoma del Estado de Morelos, Cuernavaca, Morelos, México.
Enrique Hernández LemusDepartment of Computational Genomics, Instituto Nacional de Medicina Genómica, México City, México.
Martha Rios CastroDepartment of Electromechanical Instrumentation, Instituto Nacional de Cardiología "Ignacio Chávez," México City, México.
Erika Jeannette López OlivaDepartment of Electromechanical Instrumentation, Instituto Nacional de Cardiología "Ignacio Chávez," México City, México.
Sergio Enrique Solís NájeraDepartamento de Física, Facultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Zika virus, which is widely spread and infects humans through the bites of 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 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.

Indexed as

bioinformaticsintrinsic disorder predispositionPIM profilestructural proteomicsZika virus envelope proteins (E)Zika virus polyproteins

Identifiers

PMID36330419
PMCPMC9623037

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.