In silico Prediction and Validations of Domains Involved in Gossypium hirsutum SnRK1 Protein Interaction With Cotton Leaf Curl Multan Betasatellite Encoded βC1
Cotton leaf curl disease (CLCuD) caused by viruses of genus is a major constraint to cotton ( ) production in many cotton-growing regions of the world. Symptoms of the disease are caused by Cotton leaf curl Multan betasatellite (CLCuMB) that encodes a pathogenicity determinant protein, βC1. Here, we...
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Veröffentlicht in: | Frontiers in plant science 2019-05, Vol.10, p.656 |
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Sprache: | eng |
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Zusammenfassung: | Cotton leaf curl disease (CLCuD) caused by viruses of genus
is a major constraint to cotton (
) production in many cotton-growing regions of the world. Symptoms of the disease are caused by Cotton leaf curl Multan betasatellite (CLCuMB) that encodes a pathogenicity determinant protein, βC1. Here, we report the identification of interacting regions in βC1 protein by using computational approaches including sequence recognition, and binding site and interface prediction methods. We show the domain-level interactions based on the structural analysis of
SnRK1 protein and its domains with CLCuMB-βC1. To verify and validate the
predictions, three different experimental approaches, yeast two hybrid, bimolecular fluorescence complementation and pull down assay were used. Our results showed that ubiquitin-associated domain (UBA) and autoinhibitory sequence (AIS) domains of
-encoded SnRK1 are involved in CLCuMB-βC1 interaction. This is the first comprehensive investigation that combined
interaction prediction followed by experimental validation of interaction between CLCuMB-βC1 and a host protein. We demonstrated that data from computational biology could provide binding site information between CLCuD-associated viruses/satellites and new hosts that lack known binding site information for protein-protein interaction studies. Implications of these findings are discussed. |
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ISSN: | 1664-462X 1664-462X |
DOI: | 10.3389/fpls.2019.00656 |