Abstract
Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined1. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed2,3,4. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters5,6; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.
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Data availability
All data needed to evaluate the conclusions in the paper are present in the paper and/or the supplementary materials. For reproduction purposes, the raw data used to generate the figures are available from the Dryad Digital Repository (DOI:10.6078/D1KH8R ).
Code availability
Source code and input scripts supporting this work are available at https://github.com/Shunili/AE-RHP.
References
Fulton, A. B. How crowded is the cytoplasm? Cell 30, 345–347 (1982).
Lewandowski, J. R., Halse, M. E., Blackledge, M. & Emsley, L. Direct observation of hierarchical protein dynamics. Science 348, 578–581 (2015).
Dill, K. A. Dominant forces in protein folding. Biochemistry 29, 7133–7155 (1990).
Wirth, A. J., Platkov, M. & Gruebele, M. Temporal variation of a protein folding energy landscape in the cell. J. Am. Chem. Soc. 135, 19215–19221 (2013).
Keskin, O., Gursoy, A., Ma, B. & Nussinov, R. Principles of protein–protein interactions: what are the preferred ways for proteins to interact? Chem. Rev. 108, 1225–1244 (2008).
Golumbfskie, A. J., Pande, V. S. & Chakraborty, A. K. Simulation of biomimetic recognition between polymers and surfaces. Proc. Natl Acad. Sci. USA 96, 11707–11712 (1999).
Minton, A. P. How can biochemical reactions within cells differ from those in test tubes? J. Cell Sci. 119, 2863–2869 (2006).
DePristo, M. A., Weinreich, D. M. & Hartl, D. L. Missense meanderings in sequence space: a biophysical view of protein evolution. Nat. Rev. Genet. 6, 678–687 (2005).
Rutherford, S. L. Between genotype and phenotype: protein chaperones and evolvability. Nat. Rev. Genet. 4, 263–274 (2003).
Alberti, S., Gladfelter, A. & Mittag, T. Considerations and challenges in studying liquid-liquid phase separation and biomolecular condensates. Cell 176, 419–434 (2019).
Tamasi, M. J. et al. Machine learning on a robotic platform for the design of polymer-protein hybrids. Adv. Mater. 34, e2201809 (2022).
Webb, M. A., Jackson, N. E., Gil, P. S. & de Pablo, J. J. Targeted sequence design within the coarse-grained polymer genome. Sci. Adv. 6, eabc6216 (2020).
Panganiban, B. et al. Random heteropolymers preserve protein function in foreign environments. Science 359, 1239–1243 (2018).
Jiang, T. et al. Single-chain heteropolymers transport protons selectively and rapidly. Nature 577, 216–220 (2020).
Nguyen, T. D., Qiao, B. F. & de la Cruz, M. O. Efficient encapsulation of proteins with random copolymers. Proc. Natl Acad. Sci. USA 115, 6578–6583 (2018).
Bateman, A. et al. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 49, D480–D489 (2021).
Monera, O. D., Sereda, T. J., Zhou, N. E., Kay, C. M. & Hodges, R. S. Relationship of sidechain hydrophobicity and alpha-helical propensity on the stability of the single-stranded amphipathic alpha-helix. J. Pept. Sci. 1, 319–329 (1995).
Kramer, M. A. Nonlinear principal component analysis using autoassociative neural networks. AlChE J. 37, 233–243 (1991).
Vidal, R., Ma, Y. & Sastry, S. S. Generalized Principal Component Analysis 25–62 (Springer, 2016).
Smith, A. A. A., Hall, A., Wu, V. & Xu, T. Practical prediction of heteropolymer composition and drift. ACS Macro Lett. 8, 36–40 (2019).
Bustamante, C. J., Chemla, Y. R., Liu, S. & Wang, M. D. Optical tweezers in single-molecule biophysics. Nat. Rev. Methods Primers 1, 25 (2021).
Ritchie, D. B. & Woodside, M. T. Probing the structural dynamics of proteins and nucleic acids with optical tweezers. Curr. Opin. Struct. Biol. 34, 43–51 (2015).
Suzuki, Y. & Dudko, O. K. Single molecules in an extension clamp: extracting rates and activation barriers. Phys. Rev. Lett. 110, 158105 (2013).
Zhao, Q. Nature of protein dynamics and thermodynamics. Rev. Theor. Sci. 1, 83–101 (2013).
Gstraunthaler, G., Lindl, T. & van der Valk, J. A plea to reduce or replace fetal bovine serum in cell culture media. Cytotechnology 65, 791–793 (2013).
Drew, D., Lerch, M., Kunji, E., Slotboom, D. J. & de Gier, J. W. Optimization of membrane protein overexpression and purification using GFP fusions. Nat. Methods 3, 303–313 (2006).
Shastry, M. C. R. & Roder, H. Evidence for barrier-limited protein folding kinetics on the microsecond time scale. Nat. Struct. Biol. 5, 385–392 (1998).
Milo, R. & Phillips, R. Cell Biology by the Numbers (Garland Science, Taylor & Francis Group, 2016).
Saio, T., Guan, X., Rossi, P., Economou, A. & Kalodimos, C. G. Structural basis for protein antiaggregation activity of the trigger factor chaperone. Science 344, 597–610 (2014).
Zhou, H. X., Rivas, G. N. & Minton, A. P. Macromolecular crowding and confinement: biochemical, biophysical, and potential physiological consequences. Annu. Rev. Biophys. 37, 375–397 (2008).
Street, T. O., Bolen, D. W. & Rose, G. D. A molecular mechanism for osmolyte-induced protein stability. Proc. Natl Acad. Sci. USA 103, 13997–14002 (2006).
Hilburg, S. L., Ruan, Z. Y., Xu, T. & Alexander-Katz, A. Behavior of protein-inspired synthetic random heteropolymers. Macromolecules 53, 9187–9199 (2020).
Terashima, T., Sugita, T., Fukae, K. & Sawamoto, M. Synthesis and single-chain folding of amphiphilic random copolymers in water. Macromolecules 47, 589–600 (2014).
Shu, J. Y. et al. Amphiphilic peptide-polymer conjugates based on the coiled-coil helix bundle. Biomacromolecules 11, 1443–1452 (2010).
Choi, S. H., Lodge, T. P. & Bates, F. S. Mechanism of molecular exchange in diblock copolymer micelles: hypersensitivity to core chain length. Phys. Rev. Lett. 104, 047802 (2010).
Quiroz, F. G. & Chilkoti, A. Sequence heuristics to encode phase behaviour in intrinsically disordered protein polymers. Nat. Mater. 14, 1164–1171 (2015).
Hyman, A. A., Weber, C. A. & Juelicher, F. Liquid-liquid phase separation in biology. Annu. Rev. Cell Dev. Biol. 30, 39–58 (2014).
Sing, C. E. & Perry, S. L. Recent progress in the science of complex coacervation. Soft Matter 16, 2885–2914 (2020).
Fournier, D., Hoogenboom, R., Thijs, H. M. L., Paulus, R. M. & Schubert, U. S. Tunable pH- and temperature-sensitive copolymer libraries by reversible addition-fragmentation chain transfer copolymerizations of methacrylates. Macromolecules 40, 915–920 (2007).
Wang, X. et al. LLPSDB v2.0: an updated database of proteins undergoing liquid-liquid phase separation in vitro. Bioinformatics 38, 2010–2014 (2022).
Putnam, A., Cassani, M., Smith, J. & Seydoux, G. A gel phase promotes condensation of liquid P granules in Caenorhabditis elegans embryos. Nat. Struct. Mol. Biol. 26, 220–226 (2019).
McSwiggen, D. T., Mir, M., Darzacq, X. & Tjian, R. Evaluating phase separation in live cells: diagnosis, caveats, and functional consequences. Gene Dev. 33, 1619–1634 (2019).
Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph Model 14, 33–38 (1996).
AMBER 2019 (Univ. California, San Francisco, 2019).
Xiao, L., Zhou, Z. J., Feng, M. L., Tong, A. J. & Xiang, Y. Cationic peptide conjugation enhances the activity of peroxidase-mimicking DNAzymes. Bioconjugate Chem. 27, 621–627 (2016).
Comstock, M. J., Ha, T. & Chemla, Y. R. Ultrahigh-resolution optical trap with single-fluorophore sensitivity. Nat. Methods 8, 335–382 (2011).
Biewald, L. Machine learning experiment tracking. Weights & Biases https://www.wandb.com (2020).
Acknowledgements
The work was supported by the US Department of Defense (DOD), Army Research Office, under contract no. W911NF-13-1-0232, Defense Threat Reduction Agency (DTRA) under contract no. HDTRA1-19-1-0011, the National Science Foundation under contract no. DMR-2104443, the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, under contract no. DE-AC02-05-CH11231 (KC3104) and the Alfred P. Sloan Foundation (grant no. G-2021-16757). Z.R. is supported by the Kavli Energy NanoScience Institute through the Kavli ENSI Philomathia Graduate Student Fellowship Program. Scattering studies were done at Advanced Photon Source and use of the Advanced Photon Source was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, under contract no. DE-AC02-06CH1135.
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Contributions
T.X. conceived the idea and guided the project. Z.R. and T.J. performed cell-free synthesis of membrane proteins. Z.R. and A.G. performed thermal denaturation of globular enzymes. S.L., I.J., Z.R. and H.H. performed sequence analysis. H.A. and C.B. performed optical tweezers analysis. S.H. and A.A.-K. performed all-atom simulation studies. Z.R. and Z.G. synthesized and characterized the RHPs and DHPs. H.C. performed the cell study. A.G. and H.C. performed the confocal study. All authors participated in writing the manuscript.
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T.X., H.H., Z.R. and S.L. have a pending PCT patent application. The rest of the authors declare no competing interests.
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Extended data figures and tables
Extended Data Fig. 1 Blocks and 50-mers along a polymer chain.
(a) Each monomer was reassigned to one of two pseudo-monomers (hydrophobic vs. hydrophilic) based on monomer’s hydrophobicity. A block comprises consecutive monomers of a single type. (b) A polymer chain was truncated into a set of 50-mers.
Extended Data Fig. 2 The FBS solution with different RHP ensembles after incubating at 52 °C for 2.5 h.
The FBS solution forms a thin film (like “milk skin”) at the air-water interface after thermal treatment (red circle). RHP4 exhibits the weakest tendency for formation of this thin film among three tested RHP ensembles. The solution is stirred to tear the thin film into suspended flakes for visualization.
Extended Data Fig. 3 Temperature-dependent 1H-NMR spectrum of RHP4 in D2O.
(a) 1H-NMR spectrum of RHP4 in D2O at 37 °C and its chemical structure. (b) The FWHM of proton peaks (a, p, and n) as a function of temperature (30–70 °C). (c) Part of 1H-NMR spectra of RHP4 as a function of temperature (30–70 °C) including proton peaks of the OEGMA side chain.
Extended Data Fig. 5 The distribution of DHP2 segments in PCA space.
From top to bottom, the distribution of segments from hydrophobic region, amphiphilic region, and hydrophilic region along DHP2 chains were shown.
Extended Data Fig. 6 Differential interference contrast (DIC) images of (a) RHP8 (b) RHP9 phase-separated droplets.
Each sample is 1 mg/ml in sodium phosphate buffer (50 mM, pH 7.0).
Extended Data Fig. 7 Folding status of AqpZ-eGFP in the presence of 0.2 wt% RHPs based on the eGFP fluorescence.
Error bar is 1 s.d and n = 3.
Extended Data Fig. 8 Temperature-dependent turbidimetry for RHP14 ensemble.
The polymer solution is 1mg/ml in sodium phosphate buffer (50 mM, pH 7.0).
Extended Data Fig. 9 FRAP analysis of liquid-like coacervates made from RHP10 ensemble.
The recovery trace shows the normalized recovery of a bleached region. Solid red curve fits to an exponential function (see FRAP method section).
Supplementary information
Supplementary Information
This file contains Supplementary Tables 1 and 2 and Figs. 1–21.
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Ruan, Z., Li, S., Grigoropoulos, A. et al. Population-based heteropolymer design to mimic protein mixtures. Nature 615, 251–258 (2023). https://doi.org/10.1038/s41586-022-05675-0
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DOI: https://doi.org/10.1038/s41586-022-05675-0
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