The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Determination of Secondary Structure Populations in Disordered States of Proteins Using Nuclear Magnetic Resonance Chemical Shifts
Abstract
One of the major open challenges in structural biology is to achieve effective descriptions of disordered states of proteins. This problem is difficult because these states are conformationally highly heterogeneous and cannot be represented as single structures, and therefore it is necessary to characterize their conformational properties in terms of probability distributions. Here we show that it is possible to obtain highly quantitative information about particularly important types of probability distributions, the populations of secondary structure elements (α-helix, β-strand, random coil, and polyproline II), by using the information provided by backbone chemical shifts. The application of this approach to mammalian prions indicates that for these proteins a key role in molecular recognition is played by disordered regions characterized by highly conserved polyproline II populations. We also determine the secondary structure populations of a range of other disordered proteins that are medically relevant, including p53, α-synuclein, and the Aβ peptide, as well as an oligomeric form of αB-crystallin. Because chemical shifts are the nuclear magnetic resonance parameters that can be measured under the widest variety of conditions, our approach can be used to obtain detailed information about secondary structure populations for a vast range of different protein states.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864
Spillantini, M. G., Schmidt, M. L., Lee, V. M.-Y., Trojanowski, J. Q., Jakes, R., & Goedert, M. (1997) · Nature · doi:10.1038/42166 · Cited by 8,382
Protein folding and misfolding
Dobson, C. M. (2003) · Nature · doi:10.1038/nature02261 · Cited by 4,791
Intrinsically unstructured proteins and their functions
Dyson, H. J., & Wright, P. E. (2005) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1589 · Cited by 3,871
STRIDE: a web server for secondary structure assignment from known atomic coordinates of proteins
Heinig, M., & Frishman, D. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh429 · Cited by 1,003
The interplay between structure and function in intrinsically unstructured proteins
Tompa, P. (2005) · FEBS Letters · doi:10.1016/j.febslet.2005.03.072 · Cited by 717
Structure of tumor suppressor p53 and its intrinsically disordered N-terminal transactivation domain
Wells, M., Tidow, H., Rutherford, T. J., Markwick, P., Jensen, M. R., Mylonas, E., Svergun, D. I., Blackledge, M., & Fersht, A. R. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0801353105 · Cited by 434
Cited by
Brady, J. P., Farber, P. J., Sekhar, A., Lin, Y.-H., Huang, R., Bah, A., Nott, T. J., Chan, H. S., Baldwin, A. J., Forman-Kay, J. D., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1706197114 · Cited by 533
Dao, T. P., Kolaitis, R.-M., Kim, H. J., O’Donovan, K., Martyniak, B., Colicino, E., Hehnly, H., Taylor, J. P., & Castañeda, C. A. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.02.004 · Cited by 341
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
Voelz, V. A., Jäger, M., Yao, S., Chen, Y., Zhu, L., Waldauer, S. A., Bowman, G. R., Friedrichs, M., Bakajin, O., Lapidus, L. J., et al. (2012) · Journal of the American Chemical Society · doi:10.1021/ja302528z · Cited by 140
Free-energy landscape of protein oligomerization from atomistic simulations
Barducci, A., Bonomi, M., Prakash, M. K., & Parrinello, M. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1320077110 · Cited by 87
Metadata
- Authors
- Camilloni, C., De Simone, A., Vranken, W. F., & Vendruscolo, M.
- Venue
- Biochemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-03-06
- Volume
- 51
- Issue
- 11
- Pages
- 2224-2231
- ISSN
- 0006-2960 (ISSN-L)
- 1520-4995
- OpenAlex
- W2316981376
- Cited by
- 376
- References
- 7
- FWCI
- 12.66
- Type
- journal article
- Language
- en
- Open access
- closed
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.
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Determination of Secondary Structure Populations in Disordered States of Proteins Using Nuclear Magnetic Resonance Chemical Shifts. https://app.cochat.ai/papers/10.1021/bi3001825
- The paper
- Camilloni, C., De Simone, A., Vranken, W. F., & Vendruscolo, M. (2012). Determination of Secondary Structure Populations in Disordered States of Proteins Using Nuclear Magnetic Resonance Chemical Shifts. Biochemistry. https://doi.org/10.1021/bi3001825
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
