Solutes unmask differences in clustering versus phase separation of FET proteins.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
23 May 2024
23 May 2024
Historique:
received:
22
08
2023
accepted:
03
05
2024
medline:
24
5
2024
pubmed:
24
5
2024
entrez:
23
5
2024
Statut:
epublish
Résumé
Phase separation and percolation contribute to phase transitions of multivalent macromolecules. Contributions of percolation are evident through the viscoelasticity of condensates and through the formation of heterogeneous distributions of nano- and mesoscale pre-percolation clusters in sub-saturated solutions. Here, we show that clusters formed in sub-saturated solutions of FET (FUS-EWSR1-TAF15) proteins are affected differently by glutamate versus chloride. These differences on the nanoscale, gleaned using a suite of methods deployed across a wide range of protein concentrations, are prevalent and can be unmasked even though the driving forces for phase separation remain unchanged in glutamate versus chloride. Strikingly, differences in anion-mediated interactions that drive clustering saturate on the micron-scale. Beyond this length scale the system separates into coexisting phases. Overall, we find that sequence-encoded interactions, mediated by solution components, make synergistic and distinct contributions to the formation of pre-percolation clusters in sub-saturated solutions, and to the driving forces for phase separation.
Identifiants
pubmed: 38782886
doi: 10.1038/s41467-024-48775-3
pii: 10.1038/s41467-024-48775-3
doi:
Substances chimiques
Glutamic Acid
3KX376GY7L
Chlorides
0
Solutions
0
RNA-Binding Proteins
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
4408Informations de copyright
© 2024. The Author(s).
Références
Brangwynne, C. P. et al. Germline P granules are liquid droplets that localize by controlled dissolution/condensation. Science 324, 1729–1732 (2009).
pubmed: 19460965
doi: 10.1126/science.1172046
Li, P. et al. Phase transitions in the assembly of multivalent signalling proteins. Nature 483, 336–340 (2012).
pubmed: 22398450
pmcid: 3343696
doi: 10.1038/nature10879
Banani, S. F., Lee, H. O., Hyman, A. A. & Rosen, M. K. Biomolecular condensates: organizers of cellular biochemistry. Nat. Rev. Mol. Cell Biol. 18, 285–298 (2017).
pubmed: 28225081
pmcid: 7434221
doi: 10.1038/nrm.2017.7
Shin, Y. & Brangwynne, C. P. Liquid phase condensation in cell physiology and disease. Science 357, eaaf4382 (2017).
pubmed: 28935776
doi: 10.1126/science.aaf4382
Pappu, R. V., Cohen, S. R., Dar, F., Farag, M. & Kar, M. Phase transitions of associative biomacromolecules. Chem. Rev. 123, 8945–8987 (2023).
pubmed: 36881934
doi: 10.1021/acs.chemrev.2c00814
Harmon, T. S., Holehouse, A. S., Rosen, M. K. & Pappu, R. V. Intrinsically disordered linkers determine the interplay between phase separation and gelation in multivalent proteins. eLife 6, 30294 (2017).
doi: 10.7554/eLife.30294
Yang, P. et al. G3BP1 is a tunable switch that triggers phase separation to assemble stress granules. Cell 181, 325–345 e328 (2020).
pubmed: 32302571
pmcid: 7448383
doi: 10.1016/j.cell.2020.03.046
Sanders, D. W. et al. Competing protein-RNA interaction networks control multiphase intracellular organization. Cell 181, 306–324 e328 (2020).
pubmed: 32302570
pmcid: 7816278
doi: 10.1016/j.cell.2020.03.050
Guillen-Boixet, J. et al. RNA-induced conformational switching and clustering of G3BP drive stress granule assembly by condensation. Cell 181, 346–361.e317 (2020).
pubmed: 32302572
pmcid: 7181197
doi: 10.1016/j.cell.2020.03.049
Overbeek, J. T. G. & Voorn, M. J. Phase separation in polyelectrolyte solutions. Theory of complex coacervation. J. Cell. Comp. Physiol. 49, 7–26 (1957).
doi: 10.1002/jcp.1030490404
Pak, ChiW. et al. Sequence determinants of intracellular phase separation by complex coacervation of a disordered protein. Mol. Cell 63, 72–85 (2016).
pubmed: 27392146
pmcid: 4973464
doi: 10.1016/j.molcel.2016.05.042
Adhikari S., Leaf M. A., & Muthukumar M. Polyelectrolyte complex coacervation by electrostatic dipolar interactions. J. Chem. Phys. 149, 163308 (2018).
Sing, C. E. & Perry, S. L. Recent progress in the science of complex coacervation. Soft Matter 16, 2885–2914 (2020).
pubmed: 32134099
doi: 10.1039/D0SM00001A
Neitzel, A. E. et al. Polyelectrolyte complex coacervation across a broad range of charge densities. Macromolecules 54, 6878–6890 (2021).
pubmed: 34334816
pmcid: 8320234
doi: 10.1021/acs.macromol.1c00703
King M. R. et al. Macromolecular condensation organizes nucleolar sub-phases to set up a pH gradient. Cell 187, 1889–1906 (2024).
Wang, J. et al. A molecular grammar governing the driving forces for phase separation of prion-like RNA binding proteins. Cell 174, 688–699.e616 (2018).
pubmed: 29961577
pmcid: 6063760
doi: 10.1016/j.cell.2018.06.006
Schwartz, J. C., Cech, T. R. & Parker, R. R. Biochemical properties and biological functions of FET proteins. Annu. Rev. Biochem. 84, 355–379 (2015).
pubmed: 25494299
doi: 10.1146/annurev-biochem-060614-034325
Krainer, G. et al. Reentrant liquid condensate phase of proteins is stabilized by hydrophobic and non-ionic interactions. Nat. Commun. 12, 1085 (2021).
pubmed: 33597515
pmcid: 7889641
doi: 10.1038/s41467-021-21181-9
Rubinstein, M. & Dobrynin, A. V. Solutions of associative polymers. Trends Polym. Sci. 5, 181–186 (1997).
Rubinstein, M. & Semenov, A. N. Thermoreversible gelation in solutions of associating polymers. 2. Linear dynamics. Macromolecules 31, 1386–1397 (1998).
doi: 10.1021/ma970617+
Choi, J.-M., Dar, F. & Pappu, R. V. LASSI: A lattice model for simulating phase transitions of multivalent proteins. PLoS Comput. Biol. 15, e1007028 (2019).
pubmed: 31634364
pmcid: 6822780
doi: 10.1371/journal.pcbi.1007028
Choi, J.-M., Holehouse, A. S. & Pappu, R. V. Physical principles underlying the complex biology of intracellular phase transitions. Annu. Rev. Biophys. 49, 107–133 (2020).
pubmed: 32004090
pmcid: 10715172
doi: 10.1146/annurev-biophys-121219-081629
Choi, J. M., Hyman, A. A. & Pappu, R. V. Generalized models for bond percolation transitions of associative polymers. Phys. Rev. E 102, 042403 (2020).
pubmed: 33212590
pmcid: 10846689
doi: 10.1103/PhysRevE.102.042403
Ruff, K. M. et al. Sequence grammar underlying the unfolding and phase separation of globular proteins. Mol. Cell 82, 3193–3208.e3198 (2022).
pubmed: 35853451
pmcid: 10846692
doi: 10.1016/j.molcel.2022.06.024
Harmon, T. S., Holehouse, A. S. & Pappu, R. V. Differential solvation of intrinsically disordered linkers drives the formation of spatially organized droplets in ternary systems of linear multivalent proteins. New J. Phys. 20, 045002 (2018).
doi: 10.1088/1367-2630/aab8d9
Martin, E. W. et al. Valence and patterning of aromatic residues determine the phase behavior of prion-like domains. Science 367, 694–699 (2020).
pubmed: 32029630
pmcid: 7297187
doi: 10.1126/science.aaw8653
Bremer, A. et al. Deciphering how naturally occurring sequence features impact the phase behaviours of disordered prion-like domains. Nat. Chem. 14, 196–207 (2022).
pubmed: 34931046
doi: 10.1038/s41557-021-00840-w
Farag, M. et al. Condensates of disordered proteins have small-world network structures and interfaces defined by expanded conformations. Nat. Commun. 13, 7722 (2022).
pubmed: 36513655
pmcid: 9748015
doi: 10.1038/s41467-022-35370-7
Mittag, T. & Pappu, R. V. A conceptual framework for understanding phase separation and addressing open questions and challenges. Mol. Cell 82, 2201–2214 (2022).
pubmed: 35675815
pmcid: 9233049
doi: 10.1016/j.molcel.2022.05.018
Semenov, A. N. & Rubinstein, M. Thermoreversible gelation in solutions of associative polymers. 1. Statics. Macromolecules 31, 1373–1385 (1998).
doi: 10.1021/ma970616h
Tanaka, F. Theory of thermoreversible gelation. Macromolecules 22, 1988–1994 (1989).
doi: 10.1021/ma00194a077
Flory, P. J. Thermodynamics of high polymer solutions. J. Chem. Phys. 10, 51–61 (1942).
doi: 10.1063/1.1723621
Huggins, M. L. Solutions of long chain compounds. J. Chem. Phys. 9, 440–440 (1941).
doi: 10.1063/1.1750930
Farag, M., Holehouse, A. S., Zeng, X. & Pappu, R. V. FIREBALL: a tool to fit protein phase diagrams based on mean-field theories for polymer solutions. Biophys. J. 122, 2396–2403 (2023).
pubmed: 37161095
doi: 10.1016/j.bpj.2023.05.007
Qian, D., Michaels, T. C. T. & Knowles, T. P. J. Analytical solution to the Flory–Huggins model. J. Phys. Chem. Lett. 13, 7853–7860 (2022).
pubmed: 35977086
pmcid: 9421911
doi: 10.1021/acs.jpclett.2c01986
Tanaka, F. Theoretical study of molecular association and thermoreversible gelation in polymers. Polym. J. 34, 479–509 (2002).
doi: 10.1295/polymj.34.479
Stockmayer, W. H. Theory of molecular size distribution and gel formation in branched‐chain polymers. J. Chem. Phys. 11, 45–55 (1943).
doi: 10.1063/1.1723803
Flory, P. J. Molecular size distribution in three dimensional polymers. I. Gelation1. J. Am. Chem. Soc. 63, 3083–3090 (1941).
doi: 10.1021/ja01856a061
Ogston, A. G. On the interaction of solute molecules with porous networks. J. Phys. Chem. 74, 668–669 (1970).
doi: 10.1021/j100698a032
Wu T., King M. R., Farag M., Pappu R. V., & Lew M. D. Single fluorogen imaging reveals distinct environmental and structural features of biomolecular condensates. bioRxiv, 2023.2001.2026.525727 (2023).
Alshareedah, I. et al. Sequence-specific interactions determine viscoelasticity and aging dynamics of protein condensates. bioRxiv, 2023.2004.2006.535902 (2023).
Rekhi, S. et al. Expanding the molecular language of protein liquid–liquid phase separation. Nat. Chem. https://doi.org/10.1038/s41557-024-01489-x (2024).
Farag, M., Borcherds, W. M., Bremer, A., Mittag, T. & Pappu, R. V. Phase separation of protein mixtures is driven by the interplay of homotypic and heterotypic interactions. Nat. Commun. 14, 5527 (2023).
pubmed: 37684240
pmcid: 10491635
doi: 10.1038/s41467-023-41274-x
Tanaka F. Polymer Physics: Applications to Molecular Association and Thermoreversible Gelation. (Cambridge University Press, 2011).
Nott, T. J. et al. Phase transition of a disordered nuage protein generates environmentally responsive membraneless organelles. Mol. Cell 57, 936–947 (2015).
pubmed: 25747659
pmcid: 4352761
doi: 10.1016/j.molcel.2015.01.013
Brady, J. P. et al. Structural and hydrodynamic properties of an intrinsically disordered region of a germ cell-specific protein on phase separation. Proc. Natl Acad. Sci. 114, E8194–E8203 (2017).
pubmed: 28894006
pmcid: 5625912
doi: 10.1073/pnas.1706197114
Wei, M. T. et al. Phase behaviour of disordered proteins underlying low density and high permeability of liquid organelles. Nat. Chem. 9, 1118–1125 (2017).
pubmed: 29064502
pmcid: 9719604
doi: 10.1038/nchem.2803
Alshareedah, I., Moosa, M. M., Pham, M., Potoyan, D. A. & Banerjee, P. R. Programmable viscoelasticity in protein-RNA condensates with disordered sticker-spacer polypeptides. Nat. Commun. 12, 6620 (2021).
pubmed: 34785657
pmcid: 8595643
doi: 10.1038/s41467-021-26733-7
Patil, A. et al. A disordered region controls cBAF activity via condensation and partner recruitment. Cell 186, 4936–4955.e4926 (2023).
pubmed: 37788668
doi: 10.1016/j.cell.2023.08.032
Yang, Y., Jones, H. B., Dao, T. P. & Castañeda, C. A. Single amino acid substitutions in stickers, but not spacers, substantially alter UBQLN2 phase transitions and dense phase material properties. J. Phys. Chem. B 123, 3618–3629 (2019).
pubmed: 30925840
doi: 10.1021/acs.jpcb.9b01024
Wadsworth, G. M. et al. RNAs undergo phase transitions with lower critical solution temperatures. Nat. Chem. 15, 1693–1704 (2023).
pubmed: 37932412
doi: 10.1038/s41557-023-01353-4
Kar, M. et al. Phase-separating RNA-binding proteins form heterogeneous distributions of clusters in subsaturated solutions. Proc. Natl Acad. Sci. 119, e2202222119 (2022).
pubmed: 35787038
pmcid: 9282234
doi: 10.1073/pnas.2202222119
He, G. et al. Phase-separating pyrenoid proteins form complexes in the dilute phase. Commun. Biol. 6, 19 (2023).
pubmed: 36611062
pmcid: 9825591
doi: 10.1038/s42003-022-04373-x
Lan, C. et al. Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation. Nat. Commun. 14, 4831 (2023).
pubmed: 37582808
pmcid: 10427612
doi: 10.1038/s41467-023-40540-2
Cheng, X. et al. Basis of protein stabilization by k glutamate: unfavorable interactions with carbon, oxygen groups. Biophys. J. 111, 1854–1865 (2016).
pubmed: 27806267
pmcid: 5103011
doi: 10.1016/j.bpj.2016.08.050
Sengupta, R. et al. Positioning the intracellular salt potassium glutamate in the Hofmeister series by chemical unfolding studies of NTL9. Biochemistry 55, 2251–2259 (2016).
pubmed: 27054379
doi: 10.1021/acs.biochem.6b00173
Goodacre, R., Vaidyanathan, S., Dunn, W. B., Harrigan, G. G. & Kell, D. B. Metabolomics by numbers: acquiring and understanding global metabolite data. Trends Biotechnol. 22, 245–252 (2004).
pubmed: 15109811
doi: 10.1016/j.tibtech.2004.03.007
Milo R., & Phillips R. Cell Biology by the Numbers. (Garland Science, 2015).
van Eunen, K. et al. Measuring enzyme activities under standardized in vivo-like conditions for systems biology. FEBS J. 277, 749–760 (2010).
pubmed: 20067525
doi: 10.1111/j.1742-4658.2009.07524.x
Greenwood, N. N., & Earnshaw, A. The halogens: fluorine, chlorine, bromine, iodine and astatine. in Chemistry of the Elements 2nd edn (eds Greenwood, N. N., Earnshaw, A.) (Butterworth-Heinemann, 1997).
Leirmo, S., Harrison, C., Cayley, D. S., Burgess, R. R. & Record, M. T. Jr Replacement of potassium chloride by potassium glutamate dramatically enhances protein-DNA interactions in vitro. Biochemistry 26, 2095–2101 (1987).
pubmed: 2887198
doi: 10.1021/bi00382a006
Vander Meulen, K. A., Saecker, R. M. & Record, M. T. Jr Formation of a wrapped DNA–protein interface: experimental characterization and analysis of the large contributions of ions and water to the thermodynamics of binding IHF to H′ DNA. J. Mol. Biol. 377, 9–27 (2008).
doi: 10.1016/j.jmb.2007.11.104
Kontur, W. S., Capp, M. W., Gries, T. J., Saecker, R. M. & Record, M. T. Jr Probing DNA binding, DNA opening, and assembly of a downstream clamp/jaw in Escherichia coli RNA polymerase− λPR promoter complexes using salt and the physiological anion glutamate. Biochemistry 49, 4361–4373 (2010).
pubmed: 20201585
doi: 10.1021/bi100092a
Record, M. T., Guinn, E., Pegram, L. & Capp, M. Introductory Lecture: Interpreting and predicting Hofmeister salt ion and solute effects on biopolymer and model processes using the solute partitioning model. Faraday Discuss. 160, 9–44 (2013).
pubmed: 23795491
pmcid: 3694758
doi: 10.1039/C2FD20128C
Kozlov, A. G. et al. How glutamate promotes liquid-liquid phase separation and DNA binding cooperativity of E. coli SSB protein. J. Mol. Biol. 434, 167562 (2022).
pubmed: 35351518
pmcid: 9400470
doi: 10.1016/j.jmb.2022.167562
Kozlov, A. G., Shinn, M. K., Weiland, E. A. & Lohman, T. M. Glutamate promotes SSB protein–protein interactions via intrinsically disordered regions. J. Mol. Biol. 429, 2790–2801 (2017).
pubmed: 28782560
pmcid: 5576569
doi: 10.1016/j.jmb.2017.07.021
Harami, G. M. et al. Phase separation by ssDNA binding protein controlled via protein−protein and protein−DNA interactions. Proc. Natl Acad. Sci. 117, 26206–26217 (2020).
pubmed: 33020264
pmcid: 7584906
doi: 10.1073/pnas.2000761117
Stetefeld, J., McKenna, S. A. & Patel, T. R. Dynamic light scattering: a practical guide and applications in biomedical sciences. Biophysical Rev. 8, 409–427 (2016).
doi: 10.1007/s12551-016-0218-6
Filipe, V., Hawe, A. & Jiskoot, W. Critical evaluation of nanoparticle tracking analysis (NTA) by nanosight for the measurement of nanoparticles and protein aggregates. Pharm. Res. 27, 796–810 (2010).
pubmed: 20204471
pmcid: 2852530
doi: 10.1007/s11095-010-0073-2
Cohan, M. C. & Pappu, R. V. Making the case for disordered proteins and biomolecular condensates in bacteria. Trends Biochem. Sci. 45, 668–680 (2020).
pubmed: 32456986
doi: 10.1016/j.tibs.2020.04.011
Brangwynne, C. P., Tompa, P. & Pappu, R. V. Polymer physics of intracellular phase transitions. Nat. Phys. 11, 899–904 (2015).
doi: 10.1038/nphys3532
Bracha, D. et al. Mapping local and global liquid phase behavior in living cells using photo-oligomerizable seeds. Cell 175, 1467–1480.e1413 (2018).
pubmed: 30500534
pmcid: 6724719
doi: 10.1016/j.cell.2018.10.048
Fritsch, A. W. et al. Local thermodynamics govern formation and dissolution of Caenorhabditis elegans P granule condensates. Proc. Natl Acad. Sci. 118, e2102772118 (2021).
pubmed: 34507991
pmcid: 8449359
doi: 10.1073/pnas.2102772118
Krainer, G. et al. Direct digital sensing of protein biomarkers in solution. Nat. Commun. 14, 653 (2023).
pubmed: 36746944
pmcid: 9902533
doi: 10.1038/s41467-023-35792-x
Barth A., et al. Unraveling multi-state molecular dynamics in single-molecule FRET experiments. I. Theory of FRET-lines. J. Chem. Phys. 156, 141501 (2022).
Erdős, G., Pajkos, M. & Dosztányi, Z. IUPred3: prediction of protein disorder enhanced with unambiguous experimental annotation and visualization of evolutionary conservation. Nucleic Acids Res. 49, W297–W303 (2021).
pubmed: 34048569
pmcid: 8262696
doi: 10.1093/nar/gkab408
Das, R. K., Ruff, K. M. & Pappu, R. V. Relating sequence encoded information to form and function of intrinsically disordered proteins. Curr. Opin. Struct. Biol. 32, 102–112 (2015).
pubmed: 25863585
pmcid: 4512920
doi: 10.1016/j.sbi.2015.03.008
Sengupta, P., Garai, K., Balaji, J., Periasamy, N. & Maiti, S. Measuring size distribution in highly heterogeneous systems with fluorescence correlation spectroscopy. Biophys. J. 84, 1977–1984 (2003).
pubmed: 12609900
pmcid: 1302767
doi: 10.1016/S0006-3495(03)75006-1
Vinogradov, S. A. & Wilson, D. F. Recursive maximum entropy algorithm and its application to the luminescence lifetime distribution recovery. Appl. Spectrosc. 54, 849–855 (2000).
doi: 10.1366/0003702001950210
Alexander, C. G. et al. Novel microscale approaches for easy, rapid determination of protein stability in academic and commercial settings. Biochim. Biophys Acta 1844, 2241–2250 (2014).
pubmed: 25262836
pmcid: 4332417
doi: 10.1016/j.bbapap.2014.09.016
Di, W. et al. Single-molecule force spectroscopy reveals cation-π interactions in aqueous media are highly affected by cation dehydration. Phys. Rev. Lett. 130, 118101 (2023).
pubmed: 37001074
doi: 10.1103/PhysRevLett.130.118101
Fossat, M. J., Zeng, X. & Pappu, R. V. Uncovering differences in hydration free energies and structures for model compound mimics of charged side chains of amino acids. J. Phys. Chem. B 125, 4148–4161 (2021).
pubmed: 33877835
pmcid: 8154595
doi: 10.1021/acs.jpcb.1c01073
Daban, J.-R., Samsó, M. & Bartolomé, S. Use of Nile red as a fluorescent probe for the study of the hydrophobic properties of protein-sodium dodecyl sulfate complexes in solution. Anal. Biochem. 199, 162–168 (1991).
pubmed: 1812781
doi: 10.1016/0003-2697(91)90084-7
Korte, T. & Herrmann, A. pH-dependent binding of the fluorophore bis-ANS to influenza virus reflects the conformational change of hemagglutinin. Eur. Biophys. J. 23, 105–113 (1994).
pubmed: 8050396
doi: 10.1007/BF00208864
Cser, A., Nagy, K. & Biczók, L. Fluorescence lifetime of Nile Red as a probe for the hydrogen bonding strength with its microenvironment. Chem. Phys. Lett. 360, 473–478 (2002).
doi: 10.1016/S0009-2614(02)00784-4
Felitsky, D. J. & Record, M. T. Application of the local-bulk partitioning and competitive binding models to interpret preferential interactions of glycine betaine and urea with protein surface. Biochemistry 43, 9276–9288 (2004).
pubmed: 15248785
doi: 10.1021/bi049862t
Chen, A. A., Marucho, M., Baker, N. A. & Pappu, R. V. Simulations of RNA interactions with monovalent ions. Methods Enzymol. 469, 411–432 (2009).
pubmed: 20946801
doi: 10.1016/S0076-6879(09)69020-0
Spruijt, E. et al. Reversible assembly of oppositely charged hairy colloids in water. Soft Matter 7, 8281–8290 (2011).
doi: 10.1039/c1sm05881a
Dar F., et al. Biomolecular condensates form spatially inhomogeneous network fluids. Nat. Commun. 15, 3413 (2024).
Wanger, M. & Wegner, A. Similar affinities of ADP and ATP for G-actin at physiological salt concentrations. FEBS Lett. 162, 112–116 (1983).
pubmed: 6617883
doi: 10.1016/0014-5793(83)81059-X
Wegner, A. & Isenberg, G. 12-fold difference between the critical monomer concentrations of the two ends of actin filaments in physiological salt conditions. Proc. Natl Acad. Sci. 80, 4922–4925 (1983).
pubmed: 6576365
pmcid: 384159
doi: 10.1073/pnas.80.16.4922
Almagor, M. & Cole, R. D. In physiological salt conditions the core proteins of the nucleosomes in large chromatin fragments denature at 3’ and the DNA unstacks at 5’. J. Biol. Chem. 264, 6515–6519 (1989).
pubmed: 2703503
doi: 10.1016/S0021-9258(18)83378-6
Arbely, E. et al. Acetylation of lysine 120 of p53 endows DNA-binding specificity at effective physiological salt concentration. Proc. Natl Acad. Sci. 108, 8251–8256 (2011).
pubmed: 21525412
pmcid: 3100949
doi: 10.1073/pnas.1105028108
Yi, J., Yeou, S. & Lee, N. K. DNA bending force facilitates Z-DNA formation under physiological salt conditions. J. Am. Chem. Soc. 144, 13137–13145 (2022).
pubmed: 35839423
pmcid: 9335521
doi: 10.1021/jacs.2c02466
Featherstone, D. E. Intercellular glutamate signaling in the nervous system and beyond. ACS Chem. Neurosci. 1, 4–12 (2010).
pubmed: 22778802
doi: 10.1021/cn900006n
Burger, P. M. et al. Synaptic vesicles immunoisolated from rat cerebral cortex contain high levels of glutamate. Neuron 3, 715–720 (1989).
pubmed: 2577130
doi: 10.1016/0896-6273(89)90240-7
Levy, R. M., Zhang, L. Y., Gallicchio, E. & Felts, A. K. On the nonpolar hydration free energy of proteins: surface area and continuum solvent models for the solute−solvent interaction energy. J. Am. Chem. Soc. 125, 9523–9530 (2003).
pubmed: 12889983
doi: 10.1021/ja029833a
Ashbaugh, H. S. & Paulaitis, M. E. Effect of solute size and solute−water attractive interactions on hydration water structure around hydrophobic solutes. J. Am. Chem. Soc. 123, 10721–10728 (2001).
pubmed: 11674005
doi: 10.1021/ja016324k
Wagoner, J. A. & Baker, N. A. Assessing implicit models for nonpolar mean solvation forces: the importance of dispersion and volume terms. Proc. Natl Acad. Sci. 103, 8331–8336 (2006).
pubmed: 16709675
pmcid: 1482494
doi: 10.1073/pnas.0600118103
Tran, H. T., Mao, A. & Pappu, R. V. Role of backbone−solvent interactions in determining conformational equilibria of intrinsically disordered proteins. J. Am. Chem. Soc. 130, 7380–7392 (2008).
pubmed: 18481860
doi: 10.1021/ja710446s
Schellman, J. A. Destabilization and stabilization of proteins. Q. Rev. Biophys. 38, 351–361 (2005).
pubmed: 16526966
doi: 10.1017/S0033583505004099
Kirkwood, J. G. & Buff, F. P. The statistical mechanical theory of solutions. I. J. Chem. Phys. 19, 774–777 (1951).
doi: 10.1063/1.1748352
Cho, W.-K. et al. Mediator and RNA polymerase II clusters associate in transcription-dependent condensates. Science 361, 412–415 (2018).
pubmed: 29930094
pmcid: 6543815
doi: 10.1126/science.aar4199
Henninger, J. E. et al. RNA-mediated feedback control of transcriptional condensates. Cell 184, 207–225.e224 (2021).
pubmed: 33333019
doi: 10.1016/j.cell.2020.11.030
Yanas A., Him S., Owens M. C., Liu K. F., & Goldman Y. E. DDX3X and DDX3Y constitutively form nano-sized RNA-protein clusters that foster enzymatic activity. bioRxiv, 2023.2011.2029.569239 (2023).
Davis, R. B., Supakar, A., Ranganath, A. K., Moosa, M. M., & Banerjee, P. R. Heterotypic interactions can drive selective co-condensation of prion-like low-complexity domains of FET proteins and mammalian SWI/SNF complex. Nat Commun 15, 1168 (2024).
Lemaitre, R. P., Bogdanova, A., Borgonovo, B., Woodruff, J. B. & Drechsel, D. N. FlexiBAC: a versatile, open-source baculovirus vector system for protein expression, secretion, and proteolytic processing. BMC Biotechnol. 19, 20 (2019).
pubmed: 30925874
pmcid: 6441187
doi: 10.1186/s12896-019-0512-z
Bradford, M. M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254 (1976).
pubmed: 942051
doi: 10.1016/0003-2697(76)90527-3
Sutherland, W. LXXV. A dynamical theory of diffusion for non-electrolytes and the molecular mass of albumin. Lond., Edinb., Dublin Philos. Mag. J. Sci. 9, 781–785 (1905).
doi: 10.1080/14786440509463331
Kask, P., Palo, K., Ullmann, D. & Gall, K. Fluorescence-intensity distribution analysis and its application in biomolecular detection technology. Proc. Natl Acad. Sci. 96, 13756–13761 (1999).
pubmed: 10570145
pmcid: 24137
doi: 10.1073/pnas.96.24.13756
Arosio, P. et al. Microfluidic diffusion analysis of the sizes and interactions of proteins under native solution conditions. ACS Nano 10, 333–341 (2016).
pubmed: 26678709
doi: 10.1021/acsnano.5b04713
Xia, Y. & Whitesides, G. M. Soft lithography. Annu. Rev. Mater. Sci. 28, 153–184 (1998).
doi: 10.1146/annurev.matsci.28.1.153
Best, R. B. et al. Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone ϕ, ψ and side-chain χ1 and χ2 dihedral angles. J. Chem. Theory Comput. 8, 3257–3273 (2012).
pubmed: 23341755
pmcid: 3549273
doi: 10.1021/ct300400x
Lindahl, E., Hess, B. & van der Spoel, D. GROMACS 3.0: a package for molecular simulation and trajectory analysis. Mol. modeling Annu. 7, 306–317 (2001).
doi: 10.1007/s008940100045
Páll, S. et al. Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS. J. Chem. Phys. 153, 134110 (2020).
pubmed: 33032406
doi: 10.1063/5.0018516
Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983).
doi: 10.1063/1.445869
Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys. 126, 014101 (2007).
pubmed: 17212484
doi: 10.1063/1.2408420
Parrinello, M. & Rahman, A. Polymorphic transitions in single crystals: a new molecular dynamics method. J. Appl. Phys. 52, 7182–7190 (1981).
doi: 10.1063/1.328693
Essmann, U. et al. A smooth particle mesh Ewald method. J. Chem. Phys. 103, 8577–8593 (1995).
doi: 10.1063/1.470117
Hess, B., Bekker, H., Berendsen, H. J. & Fraaije, J. G. LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472 (1997).
doi: 10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H
Abraham, M. J. et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1-2, 19–25 (2015).
doi: 10.1016/j.softx.2015.06.001