Intrinsic Disorder in Cell-signaling and Cancer-associated Proteins
Abstract
The number of intrinsically disordered proteins known to be involved in cell-signaling and regulation is growing rapidly. To test for a generalized involvement of intrinsic disorder in signaling and cancer, we applied a neural network predictor of natural disordered regions (PONDR VL-XT) to four protein datasets: human cancer-associated proteins (HCAP), signaling proteins (AfCS), eukaryotic proteins from SWISS-PROT (EU_SW) and non-homologous protein segments with well-defined (ordered) 3D structure (O_PDB_S25). PONDR VL-XT predicts >or=30 consecutive disordered residues for 79(+/-5)%, 66(+/-6)%, 47(+/-4)% and 13(+/-4)% of the proteins from HCAP, AfCS, EU_SW, and O_PDB_S25, respectively, indicating significantly more intrinsic disorder in cancer-associated and signaling proteins as compared to the two control sets. The disorder analysis was extended to 11 additional functionally diverse categories of human proteins from SWISS-PROT. The proteins involved in metabolism, biosynthesis, and degradation together with kinases, inhibitors, transport, G-protein coupled receptors, and membrane proteins are predicted to have at least twofold less disorder than regulatory, cancer-associated and cytoskeletal proteins. In contrast to 44.5% of the proteins from representative non-membrane categories, just 17.3% of the cancer-associated proteins had sequence alignments with structures in the Protein Data Bank covering at least 75% of their lengths. This relative lack of structural information correlated with the greater amount of predicted disorder in the HCAP dataset. A comparison of disorder predictions with the experimental structural data for a subset of the HCAP proteins indicated good agreement between prediction and observation. Our data suggest that intrinsically unstructured proteins play key roles in cell-signaling, regulation and cancer, where coupled folding and binding is a common mechanism.
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Many IDPs/IDRs are capable of at least partial ordering upon interaction with specific partners.
“Many IDPs/IDRs are capable of at least partial ordering upon interaction with specific partners [7–18].”
From Intrinsically disordered proteins play diverse roles in cell signaling (2022) · cites this paper as [14]
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Misiura, M. M., & Kolomeisky, A. B. (2020) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.9b08793 · Cited by 10 · see citing works
- Authors
- Iakoucheva, L. M., Brown, C. J., Lawson, J. D., Obradović, Z., & Dunker, A. K.
- Affiliations
- Washington State University (US)
- Corresponding author
- Dunker, A.Keith
- Venue
- Journal of Molecular Biology
- Publisher
- Elsevier BV
- Published
- 2002-10
- Volume
- 323
- Issue
- 3
- Pages
- 573-584
- ISSN
- 0022-2836 (ISSN-L)
- OpenAlex
- W2120881407
- Cited by
- 1,214
- References
- 66
- Citations by year
- 2026: 16 · 2025: 36 · 2024: 36 · 2023: 41 · 2022: 50 · 2021: 46 · 2020: 64 · 2019: 62 · 2018: 49 · 2017: 50 · 2016: 69 · 2015: 60 · 2014: 80 · 2013: 84 · 2012: 70
- FWCI
- 8.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Molecular Biology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Washington State University
- National Institutes of Health
- U.S. National Library of Medicine (1R01-LM06916, R01LM006916)
- Pacific Northwest National Laboratory
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
- Keywords
- intrinsically disordered proteins, signal transduction, tumor-associated proteins, protein disorder prediction, protein structure, coupled folding and binding, protein function classification, cytoskeletal proteins, G protein-coupled receptors
- MeSH terms
- Amino Acid Sequence, Humans, Molecular Sequence Data, Neoplasm Proteins, Neoplasms, Protein Conformation, Proteins, Drug Design, Signal Transduction, Sequence Alignment, Protein Structure, Tertiary, Databases, Protein
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