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In Silico Analysis of Possible Interaction between Host Genomic Transcription Factors (TFs) and Zika Virus (ZikaSPH2015) Strain with Combinatorial Gene Regulation; Virus Versus Host-The Game Reloaded.
Chetta, Massimiliano; Tarsitano, Marina; Vicari, Laura; Saracino, Annalisa; Bukvic, Nenad.
  • Chetta M; U.O.C. Genetica Medica e di Laboratorio, Ospedale Antonio Cardarelli, 80131 Napoli, Italy.
  • Tarsitano M; U.O.C. Genetica Medica e di Laboratorio, Ospedale Antonio Cardarelli, 80131 Napoli, Italy.
  • Vicari L; U.O.C. Genetica Medica e di Laboratorio, Ospedale Antonio Cardarelli, 80131 Napoli, Italy.
  • Saracino A; Clinica di Malattie Infettive, Dipartimento di Scienze Biomediche ed Oncologia Umana, Università degli Studi "Aldo Moro" di Bari, 70124 Bari, Italy.
  • Bukvic N; Genetica Medica, Azienda Ospedaliero Universitaria Consorziale Policlinico di Bari, 70124 Bari, Italy.
Pathogens ; 10(1)2021 Jan 14.
Article in English | MEDLINE | ID: covidwho-1034743
ABSTRACT
In silico analysis is a promising approach for understanding biological events in complex diseases. Herein we report on the innovative computational workflow allowed to highlight new direct interactions between human transcription factors (TFs) and an entire genome of virus ZikaSPH2015 strain in order to identify the occurrence of specific motifs on a genomic Zika Virus sequence that is able to bind and, therefore, sequester host's TFs. The analysis pipeline was performed using different bioinformatics tools available online (free of charge). According to obtained results of this in silico analysis, it is possible to hypothesize that these TFs binding motifs might be able to explain the complex and heterogeneous phenotype presentation in Zika-virus-affected fetuses/newborns, as well as the less severe condition in adults. Moreover, the proposed in silico protocol identified thirty-three different TFs identical to the distribution of TFBSs (Transcription Factor Binding Sites) on ZikaSPH2015 strain, potentially able to influence genes and pathways with biological functions confirming that this approach could find potential answers on disease pathogenesis.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Year: 2021 Document Type: Article Affiliation country: Pathogens10010069

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Full text: Available Collection: International databases Database: MEDLINE Language: English Year: 2021 Document Type: Article Affiliation country: Pathogens10010069