Isaac Meza-Padilla, Andrew C Doxey, Jozef I Nissimov
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引用次数: 0
Abstract
Accurate protein structure prediction followed by structural homology detection enable the functional annotation of otherwise obscure viral protein-coding genes. Here we employ AlphaFold proteomic modelling and structural homology searches on the genome of CrV-01T, a representative freshwater cyanophage, to reveal previously unknown structural homologs. One of these cryptic viral proteins is found to be a cyanobacteriochrome-like GAF fold (CGF) protein. Cyanobacteriochromes (CBCRs) are known to regulate phototaxis, cyclic nucleotide metabolism and optimization of light harvesting in cyanobacteria. Phylogenetic analyses indicate that the CGF protein of CrV-01T was probably acquired from a cyanobacterial host. We then use experimentally determined CBCR structures to query the Big Fantastic Virus Database and discover that CGFs are present among many different bacteriophages. The GAF domain sequence, which is a hallmark of CBCRs, can still be detected in some of these divergent viral proteins. Remarkably, viral CGF proteins harbor an N-terminal extension that in most cases is predicted to contain a transmembrane α-helix, indicating that they may bind the host membrane after being synthesized in the virocell. The presence of CGF protein-coding genes in cyanophage genomes suggests novel ways in which viruses may manipulate the metabolism of cyanobacteria, the most abundant oxygenic phototrophs on Earth. Overall, the findings reported here emphasize the importance of applying structural homology detection methods when annotating viral genomes and highlight the potential of AlphaFold for exploring the dark matter of the aquatic virosphere.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology