ArticleeLife2024
Predicting the sequence-dependent backbone dynamics of intrinsically disordered proteins.
Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Autoinhibition of untimely DNA binding by structural disorder in the full-length peroxisome proliferator-activated receptors (PPARs).Nature communications · 2026Article
- Article
- Article
- Correlated Segments of Intrinsically Disordered Proteins as Drivers of Homotypic Phase Separation.JACS Au · 2025Article
- DIRseq: a method for predicting drug-interacting residues of intrinsically disordered proteins from sequences.bioRxiv : the preprint server for biology · 2025Article
- Atomistic molecular dynamics simulations of intrinsically disordered proteins.Current opinion in structural biology · 2025Review
- Amino Acid Residue-Specific Ramachandran Distributions Derived from a Simple Mean Field Potential.ACS physical chemistry Au · 2024Article
- Predicting the sequence-dependent backbone dynamics of intrinsically disordered proteins.eLife · 2024Article
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2 authors.
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Abstract
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.
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