Cited by 683Protein Structure and DynamicsEnzyme Structure and FunctionReceptor Mechanisms and Signaling

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AlphaFold and Implications for Intrinsically Disordered Proteins

Open access
Ruff, Kiersten M., Pappu, Rohit V.·2021·Journal of Molecular Biology

Abstract

Accurate predictions of the three-dimensional structures of proteins from their amino acid sequences have come of age. AlphaFold, a deep learning-based approach to protein structure prediction, shows remarkable success in independent assessments of prediction accuracy. A significant epoch in structural bioinformatics was the structural annotation of over 98% of protein sequences in the human proteome. Interestingly, many predictions feature regions of very low confidence, and these regions largely overlap with intrinsically disordered regions (IDRs). That over 30% of regions within the proteome are disordered is congruent with estimates that have been made over the past two decades, as intense efforts have been undertaken to generalize the structure-function paradigm to include the importance of conformational heterogeneity and dynamics. With structural annotations from AlphaFold in hand, there is the temptation to draw inferences regarding the "structures" of IDRs and their interactomes. Here, we offer a cautionary note regarding the misinterpretations that might ensue and highlight efforts that provide concrete understanding of sequence-ensemble-function relationships of IDRs. This perspective is intended to emphasize the importance of IDRs in sequence-function relationships (SERs) and to highlight how one might go about extracting quantitative SERs to make sense of how IDRs function.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This perspective cautions against over-interpreting AlphaFold’s low-confidence and “unstructured” annotations for intrinsically disordered regions as literal structures or as failures of prediction. It argues that quantitative sequence–ensemble descriptions, not static models, are needed to understand IDR function.

Key findings

  • AlphaFold annotated over 98% of human proteome sequences, but roughly 30% of residues have pLDDT scores below 50, consistent with estimates that about 30% of the human proteome is disordered.
  • Low-confidence regions largely overlap intrinsically disordered regions (IDRs); the authors argue most are likely genuinely disordered rather than well-folded structures that AlphaFold missed.
  • Static AlphaFold structures of IDRs often overestimate radius of gyration relative to SAXS measurements, as shown for p27 CTD and the hnRNP-A1 prion-like low-complexity domain (A1-LCD).
  • Quantitative ensembles from atomistic simulations vetted by experiments reveal sequence-specific behavior: p27 CTD behaves on average like a Flory random coil, A1-LCD uses aromatic stickers/spacers, and Httex1 prefers tadpole-like conformations with polyQ radius scaling as n^1/3.

Methods

  • Perspective/cautionary note, not primary research; it synthesizes the AlphaFold papers, human proteome annotations, and prior IDP literature.
  • Uses illustrative examples—p27 Kip1 CTD, hnRNP-A1 A1-LCD, and huntingtin exon 1 (Httex1)—comparing AlphaFold static structures with SAXS, NMR, smFRET, and atomistic simulations based on the ABSINTH implicit solvation model and forcefield.
  • Main analysis is interpretive and qualitative, focused on why static AlphaFold depictions of IDRs lack physical meaning and how sequence–ensemble relationships should instead be quantified.

Limitations

  • The paper does not state formal limitations.
  • Evident from the text: it is a perspective/opinion piece, not a systematic review, and its examples are drawn largely from the authors’ own work and close colleagues.
  • Evident from the text: no new experimental data are reported; the quantitative examples rely on previously published simulations and experiments, and the scope is limited to interpreting AlphaFold annotations for IDRs.

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Integrity signals

Registry

Crossref · 10.1016/j.jmb.2021.167208

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Metadata

Authors
Ruff, K. M., & Pappu, R. V.
Affiliations
Washington University in St. Louis (US)
Corresponding author
Pappu, Rohit V.
Venue
Journal of Molecular Biology
Publisher
Elsevier BV
Published
2021-10
Volume
433
Issue
20
Pages
167208
ISSN
0022-2836 (ISSN-L)
OpenAlex
W3195375135
Cited by
635
References
103
Citations by year
2026: 97 · 2025: 154 · 2024: 139 · 2023: 144 · 2022: 91 · 2021: 10
FWCI
10.23
Type
journal article
Language
en
Open access
Locations
  • Journal of Molecular Biology (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
National Institutes of Health
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
Keywords
AlphaFold, intrinsically disordered regions, protein structure prediction, sequence-function relationships, conformational heterogeneity, protein dynamics, protein-protein interaction network
MeSH terms
Deep Learning, Animals, Humans, Models, Molecular, Protein Conformation, Protein Folding, Computational Biology, Proteome, Intrinsically Disordered Proteins

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