The DOI matches its Crossref record; 97 of the 103 references it cites were found in a registry or an index; 1 of the 58 sources its claims cite were checked for support.
AlphaFold and Implications for Intrinsically Disordered Proteins
Open accessAbstract
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.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
38 Not checked yet · 9 Own interpretation · 9 No basis given · 5 Own result · 1 Own method · accuracy not yet measured
None of the sources cited for this claim have been checked yet.
In the paper
“Conservative estimates indicate that roughly 30% of sequences, 30residues or longer, drawn at random from the human proteome, are likely to be IDRs. 3,5”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
What the sources say
- Not checked yetcites [3] source
- Could not verifycites [5] sourceExperimental — accuracy not yet measured
The Results describe DisProt annotations and note that the dataset is biased toward model organisms, including humans; they do not estimate the prevalence of IDRs in randomly sampled human-proteome sequences. Searches for a 30% estimate and a 30-residue threshold found no passage supporting those figures. (LLM, conf=0.70)
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Integrating SAXS and NMR measurements with simulations, suggests that the ensemble of conformations fluctuate among locally compact regions, globally compact conformations, and expanded conformations.88”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > The prion-like complexity domain from hnRNPA1
What the sources say
- Not checked yetcites [88] source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Interestingly, many predictions feature regions of very low confidence, and these regions largely overlap with intrinsically disordered regions (IDRs).”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“However, the efficiency of T187 phosphorylation does not change monotonically with changes to R g .”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Examples of sequence-ensemble descriptions obtained from atomistic simulations vetted by comparisons to multipronged experiments
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Roughly 30% of the residues across predicted structures in the human proteome tend to have pLDDT scores that are less than 50.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
In the paper
“Instead, there is a cryptic motif that is proxi-mal to the primary substrate motif that regulates the efficiency of T187 phosphorylation.64”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Examples of sequence-ensemble descriptions obtained from atomistic simulations vetted by comparisons to multipronged experiments
What the sources say
- Not checked yetcites [64]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The R g value we compute using the very low confidence static structure excised from the AlphaFold prediction is considerably higher than values obtained from direct measurements based on SAXS (Figure 2(C)).”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > The prion-like complexity domain from hnRNPA1
plainSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“These conformational features are driven by the distributed network of contacts formed between pairs of sequenceproximal or distal aromatic residues and influenced or diluted by the spacer regions that are interspersed between aromatic residues (stickers).88”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > The prion-like complexity domain from hnRNPA1
What the sources say
- Not checked yetcites [88] source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The C-terminal domain of p27, p27 CTD , generally shows low pLDDT scores (<70) in the AlphaFold prediction.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Examples of sequence-ensemble descriptions obtained from atomistic simulations vetted by comparisons to multipronged experiments
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“This is because, the static AlphaFold structure likely overestimates the radius of gyration of IDRs as measured using small angle X-ray scattering (SAXS) 64 (Figure 2(A)).”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
What the sources say
- Not checked yetcites [64]
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 10
- The quote only partly states this claim. 2
- Probably not a substantial claim. 9
In the paper
“Modulating the charge patterning changes the mean size of the conformational ensemble monotonically, consistent with SAXS experiments.64”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Examples of sequence-ensemble descriptions obtained from atomistic simulations vetted by comparisons to multipronged experiments
What the sources say
- Not checked yetcites [64]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“A sizable fraction of the N-terminal region is predicted to adopt a helical structure by Alpha-Fold, and this is consistent with experimental characterizations based on nuclear magnetic resonance (NMR) spectroscopy.85”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Examples of sequence-ensemble descriptions obtained from atomistic simulations vetted by comparisons to multipronged experiments
What the sources say
- Not checked yetcites [85]
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Atomistic simulations reproduce the average R g value measured using SAXS.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > DECLARATION OF COMPETING INTEREST
plaincorrelationalSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
None of the sources cited for this claim have been checked yet.
In the paper
“This ensemble is sequence-specific 30,31 and the extent of heterogeneity 36 as well as the relative preferences of conformations within the ensemble will depend on the primary sequence, solution conditions, and functional contexts.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
What the sources say
- Not checked yetcites [30]
- Not checked yetcites [31]
- Not checked yetcites [36]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Instead, disorder implies that a diverse conformational ensemble best describes the region of interest.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“The N-terminal portion (residues 1-95) folds upon binding to Cdk2/cyclin A and this leads to kinase inhibition.85,86”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Examples of sequence-ensemble descriptions obtained from atomistic simulations vetted by comparisons to multipronged experiments
What the sources say
- Not checked yetcites [85]
- Not checked yetcites [86]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“In the current dataset, long regions with pLDDT < 50 adopt a readily identifiable ribbon-like appearance, and should not be interpreted as structures but rather as a prediction of disorder.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
In the paper
“Intrinsically disordered regions often evolve more rapidly than ordered regions and thus alignments of these regions are generally poorer and involve large gaps and extensions of gaps because orthologous IDRs can span vast sequence lengths.9,23,58,60,[68][69][70]”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
What the sources say
- Not checked yetcites 9,23,58,60,[68][69][70]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Alleviation of steric clashes leads to a steep decrease in the potential energy, and often the local minimum will be situated closest to the region of the steepest drop in energy.72,73”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
What the sources say
- Not checked yetcites [72]
- Not checked yetcites [73]
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Over the past two decades, there has been growing recognition that the sequence-structurefunction paradigm must be generalized to account for the role of conformational heterogeneity and conformational dynamics in protein function.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“created quite a stir when it was deployed to predict the structures of 98.5% of proteins in the human proteome.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“leading to the postulate, tested through theory, computations, and experiments, that aromatic residues function as cohesive motifs known as stickers that drive single chain compaction as well as phase separation 88 -the latter through a network of intermolecular interactions.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > The prion-like complexity domain from hnRNPA1
What the sources say
- Not checked yetcites [88]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Under standard conditions used to study and characterize protein structures, IDPs/IDRs are defined by conformational heterogeneity, and the preference for heterogeneity is encoded in their amino acid sequences.11,[29][30][31]”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
What the sources say
- Not checked yetcites [11]
- Not checked yetcites [29]
- Not checked yetcites [30]
- Not checked yetcites [31]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The overall number of distinct conformations in the ensemble, the conformational heterogeneity, in terms of features such as the sizes and shapes sampled, and the relative importance of different conformations within the ensemble are defined by a combination of sequence-encoded short-and long-range interactions 37,38 as well as the modulation of these interactions by solution conditions.39,40”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
What the sources say
- Not checked yetcites [37]
- Not checked yetcites [38]
- Not checked yetcites [39]
- Not checked yetcites [40]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Importantly, prediction engines are also available to identify regions that undergo disorder-to-order, order-to-disorder, and disorder-to-disorder transitions upon binding.44”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
What the sources say
- Not checked yetcites [44]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The Pro-rich C-terminal region forms a semi-flexible tail.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Conformational ensembles of the exon 1 encoded region of huntingtin (Httex1)
What the sources say
- Not checked yetcites [94]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
In the paper
“IDPs/IDRs are best defined by a heterogeneous ensemble of conformations.36”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Introduction
What the sources say
- Not checked yetcites [36]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
“Taken together with complementary efforts focused on characterizing Httex1 phase behavior, the results obtained from multipronged studies of monomeric Httex1 predict that the growth of the “sticky head” with polyQ length mediates homotypic interactions and modulates heterotypic interactions in the cellular context.94”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > Conformational ensembles of the exon 1 encoded region of huntingtin (Httex1)
What the sources say
- Not checked yetcites [94]
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Evidence in favor of this point of view is the successful prediction of natively disordered protein regions by AlphaFold and the correlation between the decrease of pLDDT and propensity to be in a disordered region [25].”
From Using AlphaFold to predict the impact of single mutations on protein stability and function (2023) · cites this paper as [25]
In the citing paper
“like peptides, IDPs and IDRs are best thought of as sampling diverse conformational ensembles rather than a single static conformation42”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [42]
In the citing paper
“Ruff et al showed that radius of gyration values of IDPs / IDR containing proteins calculated using static AF2 models significantly deviates from those experimentally obtained by small-angle X-ray scattering (SAXS)42”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [42]
In the citing paper
“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 [42]
In the citing paper
“Some groups have used MD simulations to suggest that pLDDT and PAE metrics provide information on dynamics and disorder42,65”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [42]
In the citing paper
“Preliminary comparison of SAXS-derived versus AF calculated P(r) curves revealed that for many cases a static AF2 model does not adequately describe solution state structures42,72.”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [42]
In the citing paper
“It is therefore not surprising that it was recently shown [214] that data-driven approaches can hardly predict the structure of so-called intrinsically disordered proteins”
From Quantum Computing for Molecular Biology** (2023) · cites this paper as [214]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ AlphaFold and Implications for Intrinsically Disordered Proteins > References
“26. Miskei, M., Antal, C., Fuxreiter, M., (2016). FuzDB: database of fuzzy complexes, a tool to develop stochastic structure-function relationships for protein complexes and higher-order assemblies. Nucleic Acids Res., 45, D228- D235.”
§ AlphaFold and Implications for Intrinsically Disordered Proteins > References
“26. To ´th-Petro ´czy, A ´., Oldfield, C.J., Simon, I., Takagi, Y., Dunker, A.K., Uversky, V.N., et al., (2008). Malleable machines in transcription regulation: The mediator complex. PLoS Comput. Biol., 4, e1000243”
Citations
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
Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196
Comparison of multiple Amber force fields and development of improved protein backbone parameters
Horn̆ák, V., Abel, R., Okur, A., Strockbine, B., Roitberg, A. E., & Simmerling, C. L. (2006) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.21123 · Cited by 6,989
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
Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm
Wright, P. E., & Dyson, H. J. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.3110 · Cited by 2,968
Classification of Intrinsically Disordered Regions and Proteins
van der Lee, R., Buljan, M., Lang, B., Weatheritt, R. J., Daughdrill, G. W., Dunker, A. K., Fuxreiter, M., Gough, J., Gsponer, J., Jones, D. T., et al. (2014) · Chemical Reviews · doi:10.1021/cr400525m · Cited by 2,249
Self-citationPrediction and Functional Analysis of Native Disorder in Proteins from the Three Kingdoms of Life
Ward, J. J., Sodhi, J. S., McGuffin, L. J., Buxton, B. F., & Jones, D. T. (2004) · Journal of Molecular Biology · doi:10.1016/j.jmb.2004.02.002 · Cited by 2,010
Morcos, F., Pagnani, A., Lunt, B., Bertolino, A., Marks, D. S., Sander, C., Zecchina, R., Onuchic, J. N., Hwa, T., & Weigt, M. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1111471108 · Cited by 1,434
Evolutionarily Conserved Pathways of Energetic Connectivity in Protein Families
Lockless, S. W., & Ranganathan, R. (1999) · Science · doi:10.1126/science.286.5438.295 · Cited by 1,288
Valence and patterning of aromatic residues determine the phase behavior of prion-like domains
Martin, E. W., Holehouse, A. S., Peran, I., Farag, M., Incicco, J. J., Bremer, A., Grace, C. R., Soranno, A., Pappu, R. V., & Mittag, T. (2020) · Science · doi:10.1126/science.aaw8653 · Cited by 1,147
Self-citationProtein 3D Structure Computed from Evolutionary Sequence Variation
Marks, D. S., Colwell, L. J., Sheridan, R., Hopf, T. A., Pagnani, A., Zecchina, R., & Sander, C. (2011) · PLoS ONE · doi:10.1371/journal.pone.0028766 · Cited by 1,144
Wright, P. E., & Dyson, H. J. (2009) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2008.12.003 · Cited by 1,012
Speeding molecular recognition by using the folding funnel: The fly-casting mechanism
Shoemaker, B. A., Portman, J. J., & Wolynes, P. G. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.160259697 · Cited by 992
Mutation effects predicted from sequence co-variation
Hopf, T. A., Ingraham, J. B., Poelwijk, F. J., Schärfe, C. P. I., Springer, M., Sander, C., & Marks, D. S. (2017) · Nature Biotechnology · doi:10.1038/nbt.3769 · Cited by 775
Prediction of Protein Binding Regions in Disordered Proteins
Mészáros, B., Simon, I., & Dosztányi, Z. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000376 · Cited by 635
Protein structure prediction from sequence variation
Marks, D. S., Hopf, T. A., & Sander, C. (2012) · Nature Biotechnology · doi:10.1038/nbt.2419 · Cited by 622
Emerging methods in protein co-evolution
de Juan, D., Pazos, F., & Valencia, A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3414 · Cited by 607
Kriwacki, R. W., Hengst, L., Tennant, L. L., Reed, S. I., & Wright, P. E. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.21.11504 · Cited by 576
Net charge per residue modulates conformational ensembles of intrinsically disordered proteins
Mao, A. H., Crick, S. L., Vitalis, A., Chicoine, C. L., & Pappu, R. V. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0911107107 · Cited by 555
Self-citationCIDER: Resources to Analyze Sequence-Ensemble Relationships of Intrinsically Disordered Proteins
Holehouse, A. S., Das, R. K., Ahad, J., Richardson, M. O. G., & Pappu, R. V. (2017) · Biophysical Journal · doi:10.1016/j.bpj.2016.11.3200 · Cited by 551
Self-citationSequence co-evolution gives 3D contacts and structures of protein complexes
Hopf, T. A., Schärfe, C. P. I., Rodrigues, J. P. G. L. M., Green, A. G., Kohlbacher, O., Sander, C., Bonvin, A. M. J. J., & Marks, D. S. (2014) · eLife · doi:10.7554/elife.03430 · Cited by 515
Hofmann, H., Soranno, A., Borgia, A., Gast, K., Nettels, D., & Schuler, B. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1207719109 · Cited by 475
Relating sequence encoded information to form and function of intrinsically disordered proteins
Das, R. K., Ruff, K. M., & Pappu, R. V. (2015) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2015.03.008 · Cited by 410
Self-citationRelationship of sequence and phase separation in protein low-complexity regions
Martin, E. W., & Mittag, T. (2018) · Biochemistry · doi:10.1021/acs.biochem.8b00008 · Cited by 389
ABSINTH: A new continuum solvation model for simulations of polypeptides in aqueous solutions
Vitalis, A., & Pappu, R. V. (2008) · Journal of Computational Chemistry · doi:10.1002/jcc.21005 · Cited by 349
Self-citationCritical 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
Dyson, H. J., & Wright, P. E. (2016) · Journal of Biological Chemistry · doi:10.1074/jbc.r115.692020 · Cited by 327
NMR Characterization of Long-Range Order in Intrinsically Disordered Proteins
Salmon, L., Nodet, G., Ozenne, V., Yin, G., Jensen, M. R., Zweckstetter, M., & Blackledge, M. J. (2010) · Journal of the American Chemical Society · doi:10.1021/ja101645g · Cited by 318
Lacy, E. R., Filippov, I. V., Lewis, W. S., Otieno, S. B., Xiao, L., Weiß, S. B., Hengst, L., & Kriwacki, R. W. (2004) · Nature Structural & Molecular Biology · doi:10.1038/nsmb746 · Cited by 305
Bedford, D. C., Kasper, L. H., Fukuyama, T., & Brindle, P. K. (2010) · Epigenetics · doi:10.4161/epi.5.1.10449 · Cited by 300
Shindyalov, I. N., Kolchanov, N. A., & Sander, C. (1994) · "Protein Engineering, Design and Selection" · doi:10.1093/protein/7.3.349 · Cited by 297
Brown, C. J., Johnson, A. K., Dunker, A., & Daughdrill, G. (2011) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2011.02.005 · Cited by 288
Zimmerman, M. I., Porter, J. R., Ward, M. D., Singh, S., Vithani, N., Meller, A., Mallimadugula, U. L., Kuhn, C. E., Borowsky, J. H., Wiewiora, R., et al. (2021) · Nature Chemistry · doi:10.1038/s41557-021-00707-0 · Cited by 288
Bowman, G. R., & Geissler, P. L. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1209309109 · Cited by 279
Hopf, T. A., Ingraham, J., Poelwijk, F. J., Springer, M., Sander, C., & Marks, D. S. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1510.04612 · Cited by 249
Fuzzy Complexes: A More Stochastic View of Protein Function
Fuxreiter, M., & Tompa, P. (2012) · Advances in Experimental Medicine and Biology · doi:10.1007/978-1-4614-0659-4_1 · Cited by 240
MobiDB: intrinsically disordered proteins in 2021
Piovesan, D., Necci, M., Escobedo, N., Monzón, A. M., Hatos, A., Mičetić, I., Quaglia, F., Paladin, L., Ramasamy, P., Dosztányi, Z., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa1058 · Cited by 218
The Id-protein family in developmental and cancer-associated pathways
Roschger, C., & Cabrele, C. (2017) · Cell Communication and Signaling · doi:10.1186/s12964-016-0161-y · Cited by 217
Analyzing protein structure and function using ancestral gene reconstruction
Harms, M. J., & Thornton, J. W. (2010) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2010.03.005 · Cited by 214
Proteome-wide signatures of function in highly diverged intrinsically disordered regions
Zarin, T., Strome, B., Ba, A. N. N., Alberti, S., Forman-Kay, J. D., & Moses, A. M. (2019) · eLife · doi:10.7554/elife.46883 · Cited by 212
pE-DB: a database of structural ensembles of intrinsically disordered and of unfolded proteins
Váradi, M., Kosol, S., Lebrun, P., Valentini, E., Blackledge, M. J., Dunker, A. K., Felli, I. C., Forman-Kay, J. D., Kriwacki, R. W., Pierattelli, R., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt960 · Cited by 211
Intrinsic disorder in measles virus nucleocapsids
Jensen, M. R., Communie, G., Ribeiro, E. A., Martínez, N., Desfosses, A., Salmon, L., Mollica, L., Gabel, F., Jamin, M., Longhi, S., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1103270108 · Cited by 211
Electric-field-stimulated protein mechanics
Hekstra, D. R., White, K. I., Socolich, M., Henning, R. W., Šrajer, V., & Ranganathan, R. (2016) · Nature · doi:10.1038/nature20571 · Cited by 208
Liu, Y., Wang, X., & Liu, B. (2017) · Briefings in Bioinformatics · doi:10.1093/bib/bbx126 · Cited by 163
Interactions by disorder – A matter of context
Bugge, K., Brakti, I., Fernandes, C. B., Dreier, J. E., Lundsgaard, J. E., Olsen, J. G., Skriver, K., & Kragelund, B. B. (2020) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2020.00110 · Cited by 155
A simple model for polyproline II structure in unfolded states of alanine‐based peptides
Pappu, R. V., & Rose, G. D. (2002) · Protein Science · doi:10.1110/ps.0217402 · Cited by 154
Self-citationMalleable Machines in Transcription Regulation: The Mediator Complex
Tóth-Petróczy, Á., Oldfield, C. J., Simon, I., Takagi, Y., Dunker, A. K., Uversky, V. N., & Fuxreiter, M. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000243 · Cited by 145
Physics-based computational and theoretical approaches to intrinsically disordered proteins
Shea, J., Best, R. B., & Mittal, J. (2021) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2020.12.012 · Cited by 144
Schneider, R. C., Maurin, D., Communie, G., Kragelj, J., Hansen, D. F., Ruigrok, R. W. H., Jensen, M. R., & Blackledge, M. J. (2014) · Journal of the American Chemical Society · doi:10.1021/ja511066q · Cited by 143
PED in 2021: a major update of the protein ensemble database for intrinsically disordered proteins
Lazar, T., Martínez-Pérez, E., Quaglia, F., Hatos, A., Chemes, L. B., Iserte, J. A., Méndez, N. A., Garrone, N. A., Saldaño, T. E., Marchetti, J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1021 · Cited by 142
Self-citationDescribing sequence–ensemble relationships for intrinsically disordered proteins
Mao, A. H., Lyle, N., & Pappu, R. V. (2013) · Biochemical Journal · doi:10.1042/bj20121346 · Cited by 135
Self-citationProteome-Wide Discovery of Evolutionary Conserved Sequences in Disordered Regions
Ba, A. N. N., Yeh, B. J., van Dyk, D., Davidson, A. R., Andrews, B., Weiss, E. L., & Moses, A. M. (2012) · Science Signaling · doi:10.1126/scisignal.2002515 · Cited by 134
Sherry, K. P., Das, R. K., Pappu, R. V., & Barrick, D. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1706083114 · Cited by 127
Self-citationYing, J., Roche, J., & Bax, A. (2013) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2013.11.006 · Cited by 124
Cryptic sequence features within the disordered protein p27 Kip1 regulate cell cycle signaling
Das, R. K., Huang, Y., Phillips, A. H., Kriwacki, R. W., & Pappu, R. V. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1516277113 · Cited by 119
Self-citationMiskei, M., Antal, C., & Fuxreiter, M. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1019 · Cited by 119
Uversky, V. N. (2021) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-062920-063704 · Cited by 118
Functional Advantages of Conserved Intrinsic Disorder in RNA-Binding Proteins
Váradi, M., Zsolyomi, F., Guharoy, M., & Tompa, P. (2015) · PLoS ONE · doi:10.1371/journal.pone.0139731 · Cited by 114
Sequence-Based Prediction of Fuzzy Protein Interactions
Miskei, M., Horváth, A., Vendruscolo, M., & Fuxreiter, M. (2020) · Journal of Molecular Biology · doi:10.1016/j.jmb.2020.02.017 · Cited by 113
Genome-scale prediction of proteins with long intrinsically disordered regions
Peng, Z., Mizianty, M. J., & Kurgan, L. (2013) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24348 · Cited by 112
Disordered p27Kip1 Exhibits Intrinsic Structure Resembling the Cdk2/Cyclin A-bound Conformation
Sivakolundu, S. G., Bashford, D., & Kriwacki, R. W. (2005) · Journal of Molecular Biology · doi:10.1016/j.jmb.2005.08.074 · Cited by 108
Making the Case for Disordered Proteins and Biomolecular Condensates in Bacteria
Cohan, M. C., & Pappu, R. V. (2020) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2020.04.011 · Cited by 104
Self-citationComputational identification of MoRFs in protein sequences
Malhis, N., & Gsponer, J. A. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv060 · Cited by 101
Efficient Ensemble Refinement by Reweighting
Köfinger, J., Stelzl, L. S., Reuter, K., Allande, C., Reichel, K., & Hummer, G. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b01231 · Cited by 94
Inherent structure theory of liquids in the hard-sphere limit
Stillinger, F. H., & Weber, T. A. (1985) · The Journal of Chemical Physics · doi:10.1063/1.449840 · Cited by 93
Selection maintains signaling function of a highly diverged intrinsically disordered region
Zarin, T., Tsai, C. N., Ba, A. N. N., & Moses, A. M. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1614787114 · Cited by 93
The Cellular Environment Affects Monomeric α-Synuclein Structure
Stephens, A. D., Zacharopoulou, M., & Schierle, G. S. K. (2018) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2018.11.005 · Cited by 91
Warner, J. B., Ruff, K. M., Tan, P. S., Lemke, E. A., Pappu, R. V., & Lashuel, H. A. (2017) · Journal of the American Chemical Society · doi:10.1021/jacs.7b06659 · Cited by 90
Self-citationA quantitative measure for protein conformational heterogeneity
Lyle, N., Das, R. K., & Pappu, R. V. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4812791 · Cited by 85
Self-citationLong-Range Correlated Dynamics in Intrinsically Disordered Proteins
Parigi, G., Rezaei‐Ghaleh, N., Giachetti, A., Becker, S., Fernández, C. O., Blackledge, M. J., Griesinger, C., Zweckstetter, M., & Luchinat, C. (2014) · Journal of the American Chemical Society · doi:10.1021/ja506820r · Cited by 83
Discovery of drugs that directly target the intrinsically disordered region of the androgen receptor
Sadar, M. D. (2020) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2020.1732920 · Cited by 83
Revealing the Hidden Sensitivity of Intrinsically Disordered Proteins to their Chemical Environment
MOSES, D. C., Yu, F., Ginell, G. M., Shamoon, N. M., Koenig, P. S., Holehouse, A. S., & Sukenik, S. (2020) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.0c02822 · Cited by 78
Milles, S., Jensen, M. R., Lazert, C., et al. (2018) · Science Advances · doi:10.1126/sciadv.aat7778 · Cited by 74
Radhakrishnan, I., Pérez-Alvarado, G. C., Parker, D., Dyson, H. J., Montminy, M., & Wright, P. E. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.2658 · Cited by 73
Sequence-to-conformation relationships of disordered regions tethered to folded domains of proteins
Mittal, A., Holehouse, A. S., Cohan, M. C., & Pappu, R. V. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.05.012 · Cited by 72
Self-citationSterckx, Y. G. ‐., Volkov, A. N., Vranken, W., Kragelj, J., Jensen, M. R., Buts, L., Garcia‐Pino, A., Jové, T., Melderen, L. V., Blackledge, M. J., et al. (2014) · Structure · doi:10.1016/j.str.2014.03.012 · Cited by 70
Newcombe, E. A., Ruff, K. M., Sethi, A., Ormsby, A. R., Ramdzan, Y. M., Fox, A., Purcell, A. W., Gooley, P. R., Pappu, R. V., & Hatters, D. M. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.03.031 · Cited by 66
Self-citationUrbanek, A., Popovic, M., Morató, A., Estaña, A., Elena-Real, C. A., Mier, P., Fournet, A., Allemand, F., Delbecq, S., Andrade-Navarro, M. A., et al. (2020) · Structure · doi:10.1016/j.str.2020.04.008 · Cited by 66
Lacy, E. R., Wang, Y., Post, J. D., Nourse, A., Webb, W., Mapelli, M., Musacchio, A., Siuzdak, G. E., & Kriwacki, R. W. (2005) · Journal of Molecular Biology · doi:10.1016/j.jmb.2005.04.019 · Cited by 60
Leung, H. T. A., Bignucolo, O., Aregger, R., et al. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5b00759 · Cited by 56
Choi, J., & Pappu, R. V. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00573 · Cited by 56
Self-citationMoesa, H. A., Wakabayashi, S., Nakai, K., & Patil, A. (2012) · Molecular BioSystems · doi:10.1039/c2mb25202c · Cited by 55
Guharoy, M., Bhowmick, P., & Tompa, P. (2016) · Journal of Biological Chemistry · doi:10.1074/jbc.r115.692665 · Cited by 54
Bertagna, A. M., Toptygin, D. D., Brand, L., & Barrick, D. (2008) · Biochemical Society Transactions · doi:10.1042/bst0360157 · Cited by 50
Local complexity of amino acid interactions in a protein core
Jain, R. K., & Ranganathan, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2534352100 · Cited by 43
Radhakrishnan, A., Vitalis, A., Mao, A. H., Steffen, A. T., & Pappu, R. V. (2012) · The Journal of Physical Chemistry B · doi:10.1021/jp212637r · Cited by 36
Self-citationIdiosyncrasies of hnRNP A1-RNA recognition: Can binding mode influence function
Levengood, J. D., & Tolbert, B. S. (2018) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2018.04.001 · Cited by 34
Controlling Structural Bias in Intrinsically Disordered Proteins Using Solution Space Scanning
Holehouse, A. S., & Sukenik, S. (2020) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b00604 · Cited by 32
Fuzziness : structural disorder in protein complexes
Fuxreiter, M., & Tompa, P. (2012) · doi:10.1007/978-1-4614-0659-4 · Cited by 28
Cohan, M. C., Ruff, K. M., & Pappu, R. V. (2019) · Protein Engineering Design and Selection · doi:10.1093/protein/gzz014 · Cited by 28
Self-citationProtein Allostery in Drug Discovery
(2019) · Advances in Experimental Medicine and Biology · doi:10.1007/978-981-13-8719-7 · Cited by 25
Choi, J., & Pappu, R. V. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00572 · Cited by 15
Self-citationPredicting Conformational Properties of Intrinsically Disordered Proteins from Sequence
Ruff, K. M. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-0524-0_18 · Cited by 13
Self-citationMorató, A., Elena-Real, C. A., Popovic, M., Fournet, A., Zhang, K., Allemand, F., Sibille, N., Urbanek, A., & Bernadó, P. (2020) · Biomolecules · doi:10.3390/biom10101458 · Cited by 12
Allosteric Modulation of Intrinsically Disordered Proteins
Rehman, A. U., Rahman, M. U., Arshad, T., & Chen, H. (2019) · Advances in experimental medicine and biology · doi:10.1007/978-981-13-8719-7_14 · Cited by 12
Affinity versus specificity in coupled binding and folding reactions
Gianni, S., & Jemth, P. (2019) · Protein Engineering Design and Selection · doi:10.1093/protein/gzz020 · Cited by 11
metapredict: a fast, accurate, and easy-to-use predictor of consensus disorder and structurePreprint
Emenecker, R. J., Griffith, D., & Holehouse, A. S. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.30.446349 · Cited by 10
Cited by
Sorted by citations
The molecular basis for cellular function of intrinsically disordered protein regions
Holehouse, A. S., & Kragelund, B. B. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-023-00673-0 · Cited by 741
Conformational ensembles of the human intrinsically disordered proteome
Tesei, G., Trolle, A. I., Jonsson, N., Betz, J., Knudsen, F. E., Pesce, F., Johansson, K. E., & Lindorff‐Larsen, K. (2024) · Nature · doi:10.1038/s41586-023-07004-5 · Cited by 331
“When methods such as AlphaFold are applied to IDRs, however, they result in a single configuration or few configurations of low confidence, which do not represent the conformational heterogeneity and functional states of IDRs 6 .”
Before and after AlphaFold2: An overview of protein structure prediction
Bertoline, L. M. F., Lima, A. N., Krieger, J. E., & Teixeira, S. K. (2023) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2023.1120370 · Cited by 330
“Ruff and Pappu (2021) demonstrated that residues and regions predicted with low accuracy by AlphaFold2 overlaps intrinsically disordered regions, while Stevens and He (2022) showed that only short loops ( 20 amino acids) are predicted with high accuracy by AlphaFold and it has the tendency to…”
BackgroundUsing AlphaFold to predict the impact of single mutations on protein stability and function
Pak, M. A., Markhieva, K. A., Novikova, M. S., Petrov, D. S., Vorobyev, I. S., Maksimova, E. S., Kondrashov, F. A., & Ivankov, D. N. (2023) · PLOS One · doi:10.1371/journal.pone.0282689 · Cited by 322
“Evidence in favor of this point of view is the successful prediction of natively disordered protein regions by AlphaFold and the correlation between the decrease of pLDDT and propensity to be in a disordered region [25].”
BackgroundThe AlphaFold Database of Protein Structures: A Biologist’s Guide
David, A., Islam, S., Tankhilevich, E., & Sternberg, M. J. E. (2022) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167336 · Cited by 268
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
- Semantic Scholar
- 960aaaa85d1de9f8e2490d872165b720e3d4b565
- 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
- hybrid
- doi.org
- Licence
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-07, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-07 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review