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  •   Ιδρυματικό Αποθετήριο Πανεπιστημίου Θεσσαλίας
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  •   Ιδρυματικό Αποθετήριο Πανεπιστημίου Θεσσαλίας
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
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Ιδρυματικό Αποθετήριο Πανεπιστημίου Θεσσαλίας
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Low complexity regions in the proteins of prokaryotes perform important functional roles and are highly conserved

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Συγγραφέας
Ntountoumi C., Vlastaridis P., Mossialos D., Stathopoulos C., Iliopoulos I., Promponas V., Oliver S.G., Amoutzias G.D.
Ημερομηνία
2019
Γλώσσα
en
DOI
10.1093/NAR/GKZ730
Λέξη-κλειδί
amino acid
archaeal protein
bacterial protein
chaperone
nucleic acid binding protein
ribosome protein
DNA
protein
proteome
RNA
Article
artificial neural network
bacteriophage
DNA binding
low complexity region
metal binding
Myxococcales
nonhuman
prokaryote
protein expression
protein folding
protein structure
proteomics
RNA binding
RNA processing
chemistry
eukaryotic cell
genetics
high throughput screening
metabolism
molecular evolution
procedures
prokaryotic cell
protein domain
sequence alignment
Amino Acids
DNA
Eukaryotic Cells
Evolution, Molecular
High-Throughput Screening Assays
Prokaryotic Cells
Protein Domains
Proteins
Proteome
RNA
Sequence Alignment
Oxford University Press
Εμφάνιση Μεταδεδομένων
Επιτομή
We provide the first high-throughput analysis of the properties and functional role of Low Complexity Regions (LCRs) in more than 1500 prokaryotic and phage proteomes. We observe that, contrary to a widespread belief based on older and sparse data, LCRs actually have a significant, persistent and highly conserved presence and role in many and diverse prokaryotes. Their specific amino acid content is linked to proteins with certain molecular functions, such as the binding of RNA, DNA, metal-ions and polysaccharides. In addition, LCRs have been repeatedly identified in very ancient, and usually highly expressed proteins of the translation machinery. At last, based on the amino acid content enriched in certain categories, we have developed a neural network web server to identify LCRs and accurately predict whether they can bind nucleic acids, metal-ions or are involved in chaperone functions. An evaluation of the tool showed that it is highly accurate for eukaryotic proteins as well. © The Author(s) 2019.
URI
http://hdl.handle.net/11615/77360
Collections
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19735]

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