Diversity of short linear interaction motifs in SARS-CoV-2 nucleocapsid protein.

intrinsically disordered protein domains quasispecies short linear motifs virus-host interactions

Journal

mBio
ISSN: 2150-7511
Titre abrégé: mBio
Pays: United States
ID NLM: 101519231

Informations de publication

Date de publication:
29 Nov 2023
Historique:
medline: 29 11 2023
pubmed: 29 11 2023
entrez: 29 11 2023
Statut: aheadofprint

Résumé

Short linear motifs (SLiMs) are 3-10 amino acid long binding motifs in intrinsically disordered protein regions (IDRs) that serve as ubiquitous protein-protein interaction modules in eukaryotic cells. Through molecular mimicry, viruses hijack these sequence motifs to control host cellular processes. It is thought that the small size of SLiMs and the high mutation frequencies of viral IDRs allow rapid host adaptation. However, a salient characteristic of RNA viruses, due to high replication errors, is their obligate existence as mutant swarms. Taking advantage of the uniquely large genomic database of SARS-CoV-2, here, we analyze the role of sequence diversity in the presentation of SLiMs, focusing on the highly abundant, multi-functional nucleocapsid protein. We find that motif mimicry is a highly dynamic process that produces an abundance of motifs transiently present in subsets of mutant species. This diversity allows the virus to efficiently explore eukaryotic motifs and evolve the host-virus interface.

Identifiants

pubmed: 38018991
doi: 10.1128/mbio.02388-23
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0238823

Commentaires et corrections

Type : UpdateOf

Auteurs

Peter Schuck (P)

Laboratory of Dynamics of Macromolecular Assembly, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA.

Huaying Zhao (H)

Laboratory of Dynamics of Macromolecular Assembly, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA.

Classifications MeSH