Predicting the sequence-dependent backbone dynamics of intrinsically disordered proteins.
NMR spectroscopy
NMR spin relaxation
backbone dynamics
intrinsically disordered proteins
molecular biophysics
none
phase separation
structural biology
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
30 Oct 2024
30 Oct 2024
Historique:
medline:
30
10
2024
pubmed:
30
10
2024
entrez:
30
10
2024
Statut:
epublish
Résumé
How the sequences of intrinsically disordered proteins (IDPs) code for functions is still an enigma. Dynamics, in particular residue-specific dynamics, holds crucial clues. Enormous efforts have been spent to characterize residue-specific dynamics of IDPs, mainly through NMR spin relaxation experiments. Here, we present a sequence-based method, SeqDYN, for predicting residue-specific backbone dynamics of IDPs. SeqDYN employs a mathematical model with 21 parameters: one is a correlation length and 20 are the contributions of the amino acids to slow dynamics. Training on a set of 45 IDPs reveals aromatic, Arg, and long-branched aliphatic amino acids as the most active in slow dynamics whereas Gly and short polar amino acids as the least active. SeqDYN predictions not only provide an accurate and insightful characterization of sequence-dependent IDP dynamics but may also serve as indicators in a host of biophysical processes, including the propensities of IDP sequences to undergo phase separation.
Identifiants
pubmed: 39475380
doi: 10.7554/eLife.88958
pii: 88958
doi:
pii:
Substances chimiques
Intrinsically Disordered Proteins
0
Amino Acids
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIH HHS
ID : GM118091
Pays : United States
Commentaires et corrections
Type : UpdateOf
Informations de copyright
© 2023, Qin and Zhou.
Déclaration de conflit d'intérêts
SQ, HZ No competing interests declared
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