ArticleVirus genes2017
A bioinformatics pipeline to search functional motifs within whole-proteome data: a case study of poxviruses.
Article in Virus genes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Resources to Discover and Use Short Linear Motifs in Viral Proteins.Trends in biotechnology · 2020Review
- Review
- A comparative review of viral entry and attachment during large and giant dsDNA virus infections.Archives of virology · 2017Review
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1 author.
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Abstract
Proteins harbor domains or short linear motifs, which facilitate their functions and interactions. Finding functional motifs in protein sequences could predict the putative cellular roles or characteristics of hypothetical proteins. In this study, we present Shetti-Motif, which is an interactive tool to (i) map UniProt and PROSITE flat files, (ii) search for multiple pre-defined consensus patterns or experimentally validated functional motifs in large datasets protein sequences (proteome-wide), (iii) search for motifs containing repeated residues (low-complexity regions, e.g., Leu-, SR-, PEST-rich motifs, etc.). As proof of principle, using this comparative proteomics pipeline, eleven proteomes encoded by member of Poxviridae family were searched against about 100 experimentally validated functional motifs. The closely related viruses and viruses infect the same host cells (e.g. vaccinia and variola viruses) show similar motif-containing proteins profile. The motifs encoded by these viruses are correlated, which explains why poxviruses are able to interact with wide range of host cells. In conclusion, this in silico analysis is useful to establish a dataset(s) or potential proteins for further investigation or compare between species.
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