How multisite phosphorylation impacts the conformations of intrinsically disordered proteins
Open accessAbstract
Phosphorylation of intrinsically disordered proteins (IDPs) can produce changes in structural and dynamical properties and thereby mediate critical biological functions. How phosphorylation effects intrinsically disordered proteins has been studied for an increasing number of IDPs, but a systematic understanding is still lacking. Here, we compare the collapse propensity of four disordered proteins, Ash1, the C-terminal domain of RNA polymerase (CTD2’), the cytosolic domain of E-Cadherin, and a fragment of the p130Cas, in unphosphorylated and phosphorylated forms using extensive all-atom molecular dynamics (MD) simulations. We find all proteins to show V-shape changes in their collapse propensity upon multi-site phosphorylation according to their initial net charge: phosphorylation expands neutral or overall negatively charged IDPs and shrinks positively charged IDPs. However, force fields including those tailored towards and commonly used for IDPs overestimate these changes. We find quantitative agreement of MD results with SAXS and NMR data for Ash1 and CTD2’ only when attenuating protein electrostatic interactions by using a higher salt concentration ( e . g . 350 mM), highlighting the overstabilization of salt bridges in current force fields. We show that phosphorylation of IDPs also has a strong impact on the solvation of the protein, a factor that in addition to the actual collapse or expansion of the IDP should be considered when analyzing SAXS data. Compared to the overall mild change in global IDP dimension, the exposure of active sites can change significantly upon phosphorylation, underlining the large susceptibility of IDP ensembles to regulation through post-translational modifications.
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
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.
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?
Disordered proteins and regions are characterized by broad and heterogeneous ensembles with small differences in relative conformational stabilities and low barriers.
“Disordered proteins (regions) are characterized by broad and heterogeneous ensembles where the differences in the relative conformational stabilities are small, or even minor and the barriers are low.”
From AlphaFold, Artificial Intelligence (AI), and Allostery (2022) · cites this paper as [130]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
GROMACS: Fast, flexible, and free
van der Spoel, D., Lindahl, E. R., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. C. (2005) · Journal of Computational Chemistry · doi:10.1002/jcc.20291 · Cited by 19,187 · see citing works
The PyMOL Molecular Graphics System
DeLano, W. L. (2002) · Medical Entomology and Zoology · Cited by 18,147 · see citing works
CHARMM36m: An Improved Force Field for Folded and Intrinsically Disordered Proteins
Huang, J., Rauscher, S., Nawrocki, G., Ran, T., Feig, M., de Groot, B. L., Grubmüller, H., & MacKerell, A. (2016) · Nature Methods · doi:10.1038/nmeth.4067 · Cited by 6,708 · see citing works
Improved side-chain torsion potentials for the Amber ff99SB protein force field
Lindorff-Larsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J., Dror, R., & Shaw, D. (2010) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.22711 · Cited by 6,037 · see citing works
P-LINCS: A Parallel Linear Constraint Solver for Molecular Simulation
Hess, B. (2007) · Journal of Chemical Theory and Computation · doi:10.1021/ct700200b · Cited by 4,020 · see citing works
Intrinsically disordered proteins in cellular signalling and regulation
Wright, P. E., & Dyson, H. J. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3920 · Cited by 2,371 · see citing works
Wang, J., Choi, J.-M., Holehouse, A., Lee, H. O., Zhang, X., Jahnel, M., Maharana, S., Lemaitre, R., Pozniakovsky, A., Drechsel, D., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.006 · Cited by 1,876 · see citing works
Natively unfolded proteins: A point where biology waits for physics
Uversky, V. N. (2002) · Protein Science · doi:10.1110/ps.4210102 · Cited by 1,815 · see citing works
Fuzzy complexes: polymorphism and structural disorder in protein–protein interactions
Tompa, P., & Fuxreiter, M. (2007) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2007.10.003 · Cited by 1,080 · see citing works
Developing a molecular dynamics force field for both folded and disordered protein states
Robustelli, P., Piana, S., & Shaw, D. E. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1800690115 · Cited by 1,047 · see citing works
Das, R. K., & Pappu, R. V. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1304749110 · Cited by 1,008 · see citing works
Force Sensing by Mechanical Extension of the Src Family Kinase Substrate p130Cas
Sawada, Y., Tamada, M., Dubin‐Thaler, B. J., Cherniavskaya, O., Sakai, R., Tanaka, S., & Sheetz, M. P. (2006) · Cell · doi:10.1016/j.cell.2006.09.044 · Cited by 945 · see citing works
Piana, S., Donchev, A., Robustelli, P., & Shaw, D. E. (2015) · The Journal of Physical Chemistry B · doi:10.1021/jp508971m · Cited by 855 · see citing works
Random-coil behavior and the dimensions of chemically unfolded proteins
Kohn, J. E., Millett, I. S., Jacob, J., Žagrović, B., Dillon, T. M., Cingel, N., Dothager, R. S., Seifert, S., Thiyagarajan, P., Sosnick, T. R., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0403643101 · Cited by 706 · see citing works
Kikhney, A., & Svergun, D. I. (2015) · FEBS Letters · doi:10.1016/j.febslet.2015.08.027 · Cited by 687 · see citing works
SHIFTX2: significantly improved protein chemical shift prediction
Han, B., Liu, Y., Ginzinger, S., & Wishart, D. S. (2011) · Journal of Biomolecular NMR · doi:10.1007/s10858-011-9478-4 · Cited by 673 · see citing works
Modulation of Intrinsically Disordered Protein Function by Post-translational Modifications
Bah, A., & Forman-Kay, J. D. (2016) · Journal of Biological Chemistry · doi:10.1074/jbc.r115.695056 · Cited by 556 · see citing works
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 554 · see citing works
Tight Regulation of Unstructured Proteins: From Transcript Synthesis to Protein Degradation
Gsponer, J., Futschik, M. E., Teichmann, S. A., & Babu, M. M. (2008) · Science · doi:10.1126/science.1163581 · Cited by 466 · see citing works
Homeyer, N., Horn, A., Lanig, H., & Sticht, H. (2006) · Journal of Molecular Modeling · doi:10.1007/s00894-005-0028-4 · Cited by 384 · see citing works
The Structure and Dynamics of Higher-Order Assemblies: Amyloids, Signalosomes, and Granules
Wu, H., & Fuxreiter, M. (2016) · Cell · doi:10.1016/j.cell.2016.05.004 · Cited by 352 · see citing works
Polarization effects in molecular mechanical force fields
Cieplak, P., Dupradeau, F., Duan, Y., & Wang, J. (2009) · Journal of Physics Condensed Matter · doi:10.1088/0953-8984/21/33/333102 · Cited by 323 · see citing works
Martin, E. W., Holehouse, A. S., Grace, C. R., Hughes, A. C., Pappu, R. V., & Mittag, T. (2016) · Journal of the American Chemical Society · doi:10.1021/jacs.6b10272 · Cited by 248 · see citing works
Darling, A., & Uversky, V. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00158 · Cited by 236 · see citing works
Fuzzy complexes: Specific binding without complete folding
Sharma, R., Ráduly, Z., Miskei, M., & Fuxreiter, M. (2015) · FEBS Letters · doi:10.1016/j.febslet.2015.07.022 · Cited by 226 · see citing works
Knight, C. J., & Hub, J. S. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv309 · Cited by 200 · see citing works
Fuertes, G., Banterle, N., Ruff, K. M., Chowdhury, A., Mercadante, D., Koehler, C., Kachala, M., Girona, G. E., Milles, S., Mishra, A., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1704692114 · Cited by 198 · see citing works
Self-citationNMR contributions to structural dynamics studies of intrinsically disordered proteins
Konrat, R. (2014) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2013.11.011 · Cited by 184 · see citing works
Validating Solution Ensembles from Molecular Dynamics Simulation by Wide-Angle X-ray Scattering Data
Chen, P., & Hub, J. S. (2014) · Biophysical Journal · doi:10.1016/j.bpj.2014.06.006 · Cited by 166 · see citing works
Brinkman, A., van der Flier, S., Kok, E. M., & Dorssers, L. C. J. (2000) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/92.2.112 · Cited by 146 · see citing works
PyTMs: a useful PyMOL plugin for modeling common post-translational modifications
Warnecke, A., Sandalova, T., Achour, A., & Harris, R. A. (2014) · BMC Bioinformatics · doi:10.1186/s12859-014-0370-6 · Cited by 120 · see citing works
Gibbs, E. B., Lu, F., Portz, B., et al. (2017) · Nature Communications · doi:10.1038/ncomms15233 · Cited by 92 · see citing works
Kulkarni, P., Jolly, M. K., Jia, D., Mooney, S. M., Bhargava, A., Kagohara, L. T., Chen, Y., Hao, P., He, Y., Veltri, R. W., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1700082114 · Cited by 85 · see citing works
An Extended Guinier Analysis for Intrinsically Disordered Proteins
Zheng, W., & Best, R. B. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.03.007 · Cited by 82 · see citing works
Mercadante, D., Milles, S., Fuertes, G., Svergun, D. I., Lemke, E. A., & Gräter, F. (2015) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.5b03440 · Cited by 77 · see citing works
Self-citationCommonly used FRET fluorophores promote collapse of an otherwise disordered protein
Riback, J. A., Bowman, M. A., Zmyslowski, A. M., Plaxco, K. W., Clark, P. L., & Sosnick, T. R. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1813038116 · Cited by 73 · see citing works
How well do force fields capture the strength of salt bridges in proteins?
Ahmed, M. C., Papaleo, E., & Lindorff‐Larsen, K. (2018) · PeerJ · doi:10.7717/peerj.4967 · Cited by 72 · see citing works
Single Molecule FRET: A Powerful Tool to Study Intrinsically Disordered Proteins
LeBlanc, S. J., Kulkarni, P., & Weninger, K. (2018) · Biomolecules · doi:10.3390/biom8040140 · Cited by 71 · see citing works
Henriques, J., Arleth, L., Lindorff‐Larsen, K., & Skepö, M. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.03.002 · Cited by 69 · see citing works
McEwen, A. E., Maher, M. T., Mo, R., et al. (2014) · Molecular Biology of the Cell · doi:10.1091/mbc.e14-01-0690 · Cited by 64 · see citing works
Chan-Yao-Chong, M., Christiane, D. D., & Ha‐Duong, T. (2019) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.8b00928 · Cited by 61 · see citing works
Phosphorylation of a Disordered Peptide─Structural Effects and Force Field Inconsistencies
Rieloff, E., & Skepö, M. (2020) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b01190 · Cited by 38 · see citing works
Src, p130Cas, and Mechanotransduction in Cancer Cells
Matsui, H., Harada, I., & Sawada, Y. (2012) · Genes & Cancer · doi:10.1177/1947601912461443 · Cited by 34 · see citing works
Dölker, N., Górna, M. W., Sutto, L., Torralba, A. S., Superti‐Furga, G., & Gervasio, F. L. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003863 · Cited by 33 · see citing works
Theoretical pKa prediction of O-phosphoserine in aqueous solution
Śmiechowski, M. (2010) · Chemical Physics Letters · doi:10.1016/j.cplett.2010.10.063 · Cited by 32 · see citing works
Effect of Phosphorylation on a Human-like Osteopontin Peptide
Lenton, S., Grimaldo, M., Roosen‐Runge, F., et al. (2017) · Biophysical Journal · doi:10.1016/j.bpj.2017.03.005 · Cited by 30 · see citing works
Mercadante, D., Wagner, J. A., Aramburu, I. V., Lemke, E. A., & Gräter, F. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00143 · Cited by 20 · see citing works
Self-citationShowalter, S. A., & Gibbs, E. B. (2017) · Biophysical Journal · doi:10.1016/j.bpj.2016.11.2755 · Cited by 4 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
AlphaFold, Artificial Intelligence (AI), and Allostery
Nussinov, R., Zhang, M., Liu, Y., & Jang, H. (2022) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.2c04346 · Cited by 190 · see citing works
Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs
Nussinov, R., Zhang, M., Maloney, R., Liu, Y., Tsai, C.-J., & Jang, H. (2022) · Journal of Molecular Biology · doi:10.1016/j.jmb.2022.167569 · Cited by 66 · see citing works
Williams, E. T., Schiefelbein, K., Schuster, M., Ahmed, I. M. M., De Vries, M., Beveridge, R., Zerbe, O., & Hartrampf, N. (2024) · Chemical Science · doi:10.1039/d4sc00481g · Cited by 13 · see citing works
- Authors
- Jin, F., & Gräter, F.
- Affiliations
- Heidelberg University (DE)
- Corresponding author
- Gräter, Frauke
- Venue
- PLOS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2021-05-04
- Volume
- 17
- Issue
- 5
- Pages
- e1008939
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC8148376
- OpenAlex
- W3157400614
- Cited by
- 77
- References
- 48
- Citations by year
- 2026: 15 · 2025: 20 · 2024: 16 · 2023: 10 · 2022: 13 · 2021: 3
- FWCI
- 3.30
- Type
- journal article
- Language
- en
- Update notices
- new_version (2021-05-25)
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Baden-Württemberg
- Deutsche Forschungsgemeinschaft (INST 35/1134-1 FUGG, SPP1782)
- Gauss Centre for Supercomputing e.V.
- Klaus Tschira Foundation
- Heidelberg University
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Keywords
- intrinsically disordered proteins, multisite phosphorylation, protein conformation, electrostatic interactions, salt bridges, protein solvation, active site exposure, post-translational modification, ASH1, p130Cas, net charge
- MeSH terms
- Amino Acid Sequence, Phosphorylation, Protein Conformation, Protein Processing, Post-Translational, Reproducibility of Results, Nuclear Magnetic Resonance, Biomolecular, Molecular Dynamics Simulation, 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.
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