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In Silico Analysis of Possible Interaction between Host Genomic Transcription Factors and Zika Virus (ZikaSPH2015) Strain with Combinatorial Gene Regulation; Virus Versus Host - The Game Reloaded
Chetta, M.; Tarsitano, M.; Vicari, L.; Saracino, A.; Bukvic, N. 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. Pathogens2021, 10, 69.
Chetta, M.; Tarsitano, M.; Vicari, L.; Saracino, A.; Bukvic, N. 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. Pathogens 2021, 10, 69.
Chetta, M.; Tarsitano, M.; Vicari, L.; Saracino, A.; Bukvic, N. 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. Pathogens2021, 10, 69.
Chetta, M.; Tarsitano, M.; Vicari, L.; Saracino, A.; Bukvic, N. 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. Pathogens 2021, 10, 69.
Abstract
In silico analysis is a promising approach for understanding biological events in complex diseases. Herein, we report an in silico analysis of the entire genome of virus ZikaSPH2015 strain, which was performed in order to identify the occurrence of specific motifs on genomic sequence of Zika Virus that is able to bind and therefore, sequester host’s Transcription Factors (TFs) as well as subsequently predict a possible interactions within host genome. Accordingly to obtained results of this original computational work-flow 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 fe-tus/newborns, as well as the less severe condition in adults. Moreover, the proposed in silico protocol identified thirty three different TFs same as 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.
Copyright:
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