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Identification and characterization of coiled-coil motifs across Autographa californica multiple nucleopolyhedrovirus genome
Coiled coils (CCs) are protein structural motifs universally found in proteins and mediate a plethora of biological interactions, and thus their reliable annotation is crucial for studies of protein structure and function. Autographa californica multiple nucleopolyhedrovirus (AcMNPV) is a large doub...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9483598/ https://www.ncbi.nlm.nih.gov/pubmed/36132175 http://dx.doi.org/10.1016/j.heliyon.2022.e10588 |
Sumario: | Coiled coils (CCs) are protein structural motifs universally found in proteins and mediate a plethora of biological interactions, and thus their reliable annotation is crucial for studies of protein structure and function. Autographa californica multiple nucleopolyhedrovirus (AcMNPV) is a large double-stranded DNA (dsDNA) virus and encodes 154 proteins. In this study, genome-wide scans of previously uncharacterized CC motifs throughout AcMNPV was conducted using CC prediction software. In total, 24 CC motifs in 19 CC proteins with high confidence were identified. The characteristic of viral CC motifs were analyzed. The CC proteins could be divided into 12 viral structural proteins and 7 non-structural proteins, including viral membrane fusion proteins, enzymes, and transcription factors. Moreover, CC motifs are conserved in the baculoviral orthologs of 14 of the 19 proteins. It is noted that five CC proteins, including Ac51, Ac66, Exon0, Ac13, and GP16, were previously identified to function in the nuclear egress of nucleocapsids, and Ac66 contains multiple CC motifs, the longest of which comprises 252 amino acids, suggesting a role of CC motifs in this process. Taken together, the CC motifs identified in this study are valuable resource for studying protein function and protein interaction networks during virus replication. |
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