Intrinsic protein disorder and conditional folding in AlphaFoldDB
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Abstract
Intrinsically disordered regions (IDRs) defying the traditional protein structure-function paradigm have been difficult to analyze. The availability of accurate structure predictions on a large scale in AlphaFoldDB offers a fresh perspective on IDR prediction. Here, we establish three baselines for IDR prediction from AlphaFoldDB models based on the recent CAID dataset. Surprisingly, AlphaFoldDB is highly competitive for predicting both IDRs and conditionally folded binding regions, demonstrating the plasticity of the disorder to structure continuum.
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Preliminary studies suggest most targets with very low pLDDT (<50) are likely IDPs/IDRs rather than well-folded proteins AF2 fails to predict.
“Preliminary studies suggest that the majority of targets with very low-confidence score (pLDDT < 50) assigned by AF2 are likely to be IDPs / IDRs rather than well-folded structures that AF2 fails to predict42–44”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [44]
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Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Varadi, M., Anyango, S., Deshpande, M., Nair, S., Natassia, C., Yordanova, G., Yuan, D., Stroe, O., Wood, G., Laydon, A., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1061 · Cited by 7,850 · cited 2× · see citing works
“6 AlphaFold-pLDDT uses 1 - pLDDT as output.”
BackgroundAnnouncing the worldwide Protein Data Bank
Berman, H., Henrick, K., & Nakamura, H. (2003) · Nature Structural & Molecular Biology · doi:10.1038/nsb1203-980 · Cited by 3,093 · see citing works
Highly accurate protein structure prediction for the human proteome
Tunyasuvunakool, K., Adler, J., Wu, Z., Green, T., Zielinski, M., Žídek, A., Bridgland, A., Cowie, A., Meyer, C., Laydon, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03828-1 · Cited by 3,025 · cited 2× · see citing works
“7,10 IDRs lacking a fixed tertiary structure are well-known in structural biology 11 and have been associated with a variety of biological functions.”
BackgroundA structural biology community assessment of AlphaFold2 applications
Akdel, M., Pires, D. E. V., Pardo, E. P., Jänes, J., Zalevsky, A. O., Mészáros, B., Bryant, P., Good, L. L., Laskowski, R. A., Pozzati, G., et al. (2022) · Nature Structural & Molecular Biology · doi:10.1038/s41594-022-00849-w · Cited by 675 · cited 2× · see citing works
“9 This is possible because inter/chain contacts between interaction surfaces are well encoded in multiple sequence alignments (and in the model) similarly to intra/chain contacts.”
BackgroundAlphaFold and Implications for Intrinsically Disordered Proteins
Ruff, K. M., & Pappu, R. V. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167208 · Cited by 635 · see citing works
Critical assessment of protein intrinsic disorder prediction
Necci, M., Piovesan, D., Predictors, C., Hoque, M. T., Walsh, I., Iqbal, S., Vendruscolo, M., Sormanni, P., Wang, C., Raimondi, D., et al. (2021) · Nature Methods · doi:10.1038/s41592-021-01117-3 · Cited by 343 · see citing works
High‐accuracy protein structure prediction in <scp>CASP14</scp>
Pereira, J., Simpkin, A. J., Hartmann, M. D., Rigden, D. J., Keegan, R. M., & Lupas, A. N. (2021) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26171 · Cited by 314 · cited 1× · see citing works
“2,3 This is leading to a paradigm shift for structural biology due to the sudden availability of orders of magnitude more protein structures.”
BackgroundThe structural coverage of the human proteome before and after AlphaFold
Porta-Pardo, E., Ruiz-Serra, V., Valentini, S., & Valencia, A. (2022) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1009818 · Cited by 131 · see citing works
Flagged first, then by citations
Research works printed but not linked: 13
- [1]Kryshtafovych A, Schwede T, Topf M, Fidelis K, Moult J. Critical assessment of methods of protein structure prediction (CASP)—Round XIV. Proteins Struct Funct Bioinform. 2021; 89: 1607– 1617. PMC8726744 34533838
- [4]Subramaniam S, Kleywegt GJ. A paradigm shift in structural biology. Nat Methods. 2022; 19: 20– 23. 35017736
- [5]Cramer P. AlphaFold2 and the future of structural biology. Nat Struct Mol Biol. 2021; 28: 704– 705. 34376855
- [11]Tompa P, Fersht A. Structure and Function of Intrinsically Disordered Proteins. New York: CRC Press, 2009.
- [12]Wright PE, Dyson HJ. Intrinsically disordered proteins in cellular signalling and regulation. Nat Rev Mol Cell Biol. 2015; 16: 18– 29. 25531225 PMC4405151
- [14]Quaglia F, Mészáros B, Salladini E, et al. DisProt in 2022: Improved quality and accessibility of protein intrinsic disorder annotation. Nucleic Acids Res. 2022; 50: D480– D487. 34850135 PMC8728214
- [16]Kabsch W, Sander C. Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features. Biopolymers. 1983; 22: 2577– 2637. 6667333
- [17]Rost B, Sander C. Conservation and prediction of solvent accessibility in protein families. Proteins Struct Funct Bioinforma. 1994; 20: 216– 226. 7892171
- [18]Hamelryck T, Manderick B. PDB file parser and structure class implemented in python. Bioinformatics. 2003; 19: 2308– 2310. 14630660
- [19]Mészáros B, Erdős G, Dosztányi Z. IUPred2A: Context‐dependent prediction of protein disorder as a function of redox state and protein binding. Nucleic Acids Res. 2018; 46: W329– W337. 29860432 PMC6030935
- [20]Mészáros B, Simon I, Dosztányi Z. Prediction of protein binding regions in disordered proteins. PLoS Comput Biol. 2009; 5: e1000376. 19412530 PMC2671142
- [21]Sormanni P, Piovesan D, Heller GT, et al. Simultaneous quantification of protein order and disorder. Nat Chem Biol. 2017; 13: 339– 342. 28328918
- [22]Hu G, Katuwawala A, Wang K, et al. flDPnn: Accurate intrinsic disorder prediction with putative propensities of disorder functions. Nat Commun. 2021; 12: 4438. 34290238 PMC8295265
Cited by
Sorted by citations
Systematic identification of conditionally folded intrinsically disordered regions by AlphaFold2
Alderson, T. R., Pritišanac, I., Kolarić, Đ., Moses, A. M., & Forman-Kay, J. D. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2304302120 · Cited by 240 · see citing works
AlphaFold2: A Role for Disordered Protein/Region Prediction?
Wilson, C. J., Choy, W.-Y., & Karttunen, M. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23094591 · Cited by 173 · see citing works
The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins
Agarwal, V., & McShan, A. C. (2024) · Nature Chemical Biology · doi:10.1038/s41589-024-01638-w · Cited by 155 · see citing works
“Future benchmarks should continue to evaluate AF2 against panels of IDPs and IDR-containing proteins using novel critical assessment of protein intrinsic disorder targets 44 .”
BackgroundConte, A. D., Mehdiabadi, M., Bouhraoua, A., Miguel Monzon, A., Tosatto, S. C. E., & Piovesan, D. (2023) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26582 · Cited by 86 · see citing works
Self-citationChallenges in bridging the gap between protein structure prediction and functional interpretation
Varadi, M., Tsenkov, M., & Velankar, S. (2025) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26614 · Cited by 36 · see citing works
Varadi, M., Bordin, N., Orengo, C., & Velankar, S. (2023) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2023.102543 · Cited by 29 · see citing works
Data‐driven evaluation of suitable immunogens for improved antibody selection
Waury, K., Kvartsberg, H., Zetterberg, H., Blennow, K., Teunissen, C. E., & Abeln, S. (2025) · Protein Science · doi:10.1002/pro.70100 · Cited by 1 · see citing works
- Authors
- Piovesan, D., Monzon, A. M., & Tosatto, S. C. E.
- Affiliations
- University of Padua (IT)
- Department of Biomedical Sciences University of Padova Padova Italy
- Corresponding author
- Tosatto, Silvio C. E.
- Venue
- Protein Science
- Publisher
- Wiley
- Published
- 2022-10-26
- Volume
- 31
- Issue
- 11
- Pages
- e4466-e4466
- ISSN
- 0961-8368 (ISSN-L)
- 1469-896X
- PMC
- PMC9601767
- OpenAlex
- W4303983095
- Cited by
- 160
- References
- 9
- Citations by year
- 2026: 35 · 2025: 42 · 2024: 42 · 2023: 35 · 2022: 6
- FWCI
- 10.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Protein Science (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Padua Research Archive (University of Padova) (submittedVersion, cc-by)
- Funders
- H2020 Marie Skłodowska-Curie Actions (778247)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- intrinsically disordered regions, protein structure prediction
- MeSH terms
- Protein Conformation, Protein Folding, Intrinsically Disordered Proteins
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