ArticleBiomolecules2022
Compositional Bias of Intrinsically Disordered Proteins and Regions and Their Predictions.
Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Beyond the structure-function paradigm: A comprehensive review of intrinsically disordered proteins.Biochemistry and biophysics reports · 2026Review
- Rethinking bioinformatics in liquid-liquid phase separation: data resources, predictive models, and an event-centric perspective.Briefings in bioinformatics · 2026Review
- Modern resources for intrinsic disorder predictions: protein language models, deep learning, meta-servers, and databases.Cellular and molecular life sciences : CMLS · 2026Review
- Comparative assessment of binding residue predictions in intrinsically disordered regions.Protein science : a publication of the Protein Society · 2025Article
- Empirical Assessment of Sequence-Based Predictions of Intrinsically Disordered Regions Involved in Phase Separation.Biomolecules · 2025Article
- Navigating the unstructured by evaluating alphafold's efficacy in predicting missing residues and structural disorder in proteins.PloS one · 2025Article
- Taxonomy-specific assessment of intrinsic disorder predictions at residue and region levels in higher eukaryotes, protists, archaea, bacteria and viruses.Computational and structural biotechnology journal · 2024Article
- Survey of the Aβ-peptide structural diversity: molecular dynamics approaches.Biophysical reviews · 2024Review
- Twenty years of advances in prediction of nucleic acid-binding residues in protein sequences.Briefings in bioinformatics · 2024Review
- Identification of Low-Complexity Domains by Compositional Signatures Reveals Class-Specific Frequencies and Functions Across the Domains of Life.PLoS computational biology · 2024Article
- Systematic identification of 20S proteasome substrates.Molecular systems biology · 2024Article
- Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure.Protein science : a publication of the Protein Society · 2024Review
- Intrinsically Disordered Compositional Bias in Proteins: Sequence Traits, Region Clustering, and Generation of Hypothetical Functional Associations.Bioinformatics and biology insights · 2024Article
- Tutorial: a guide for the selection of fast and accurate computational tools for the prediction of intrinsic disorder in proteins.Nature protocols · 2023Review
- DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction.Nucleic acids research · 2023Article
- Per Aspera ad Chaos: Vladimir Uversky's Odyssey through the Strange World of Intrinsically Disordered Proteins.Biomolecules · 2023Article
- Computational prediction of disordered binding regions.Computational and structural biotechnology journal · 2023Review
- Comparative evaluation of AlphaFold2 and disorder predictors for prediction of intrinsic disorder, disorder content and fully disordered proteins.Computational and structural biotechnology journal · 2023Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intrinsically disordered regions (IDRs) carry out many cellular functions and vary in length and placement in protein sequences. This diversity leads to variations in the underlying compositional biases, which were demonstrated for the short vs. long IDRs. We analyze compositional biases across four classes of disorder: fully disordered proteins; short IDRs; long IDRs; and binding IDRs. We identify three distinct biases: for the fully disordered proteins, the short IDRs and the long and binding IDRs combined. We also investigate compositional bias for putative disorder produced by leading disorder predictors and find that it is similar to the bias of the native disorder. Interestingly, the accuracy of disorder predictions across different methods is correlated with the correctness of the compositional bias of their predictions highlighting the importance of the compositional bias. The predictive quality is relatively low for the disorder classes with compositional bias that is the most different from the "generic" disorder bias, while being much higher for the classes with the most similar bias. We discover that different predictors perform best across different classes of disorder. This suggests that no single predictor is universally best and motivates the development of new architectures that combine models that target specific disorder classes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.