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Nucleic Acids Res ; 52(W1): W221-W232, 2024 Jul 05.
Article in English | MEDLINE | ID: mdl-38567734

ABSTRACT

E3 ubiquitin ligases recognize substrates through their short linear motifs termed degrons. While degron-signaling has been a subject of extensive study, resources for its systematic screening are limited. To bridge this gap, we developed DEGRONOPEDIA, a web server that searches for degrons and maps them to nearby residues that can undergo ubiquitination and disordered regions, which may act as protein unfolding seeds. Along with an evolutionary assessment of degron conservation, the server also reports on post-translational modifications and mutations that may modulate degron availability. Acknowledging the prevalence of degrons at protein termini, DEGRONOPEDIA incorporates machine learning to assess N-/C-terminal stability, supplemented by simulations of proteolysis to identify degrons in newly formed termini. An experimental validation of a predicted C-terminal destabilizing motif, coupled with the confirmation of a post-proteolytic degron in another case, exemplifies its practical application. DEGRONOPEDIA can be freely accessed at degronopedia.com.


Subject(s)
Internet , Protein Processing, Post-Translational , Proteolysis , Proteome , Software , Ubiquitin-Protein Ligases , Ubiquitination , Proteome/chemistry , Ubiquitin-Protein Ligases/metabolism , Ubiquitin-Protein Ligases/chemistry , Ubiquitin-Protein Ligases/genetics , Humans , Machine Learning , Amino Acid Motifs , Degrons
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