Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

A designer minimalistic model parallels the phase-separation-mediated assembly and biophysical cues of extracellular matrix

Abstract

The propensity for controlled liquid–liquid phase separation and subsequent directed phase transition are crucial for the coacervation-mediated assembly of extracellular matrix (ECM). This spatiotemporally controlled ECM assembly can be used to develop coacervate-based polymer assembly strategies to generate biomimetic materials that can emulate the complex structures and biophysical cues of the ECM. Inspired by the tropoelastin structure, here we develop a designer minimalistic model consisting of alternating hydrophobic moieties and covalent crosslinking domains. By increasing the valence and enhancing the interaction strength of the hydrophobic moieties, we can control the degree of the assembly to enhance the propensity for phase separation and thus emulate the extracellular coacervation process of tropoelastin, including droplet formation, coalescence and maturation. The subsequent covalent-bonding-triggered coacervate–hydrogel transition with enhanced assembly order stabilizes the phase-separated structure in the form of a heterogeneous hydrogel, thereby mimicking covalent crosslinking-derived elastin fibrillation. Furthermore, the heterogeneous hydrogel network establishes a biomimetic matrix that can effectively promote the mechanosensing of adherent stem cells.

This is a preview of subscription content, access via your institution

Access options

Buy this article

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: A minimalistic model with tunable assembly order emulates the spatiotemporal assembly and associated biophysical cues of ECM for cellular regulation.
Fig. 2: Hydrophobic interactions among the grafted aromatic moieties induce the formation of stable coacervate.
Fig. 3: The increased valence of grafted hydrophobic moieties promotes the formation and stability of gelatin-based coacervates.
Fig. 4: Increased interaction strength of the hydrophobic moieties grafted onto gelatin promotes the propensity for LLPS.
Fig. 5: Post-LLPS covalent crosslinking achieves an on-demand coacervate–hydrogel transition to stabilize the phase-separated structure.
Fig. 6: Coacervation-mediated fabrication of biomimetic matrix for the regulation of stem cell behaviours.

Similar content being viewed by others

Data availability

The data supporting the findings from this study can be found within the paper, supplementary materials or source data files. All final CG parameters, modelled structures and MD simulation inputs/outputs for each system investigated in this study are available on Zenodo at https://doi.org/10.5281/zenodo.15111903 (ref. 90). Source data are provided with this paper.

References

  1. Shin, Y. & Brangwynne, C. P. Liquid phase condensation in cell physiology and disease. Science 357, eaaf4382 (2017).

    Article  PubMed  Google Scholar 

  2. Mayr, C. et al. Frontiers in biomolecular condensate research. Nat. Cell Biol. 25, 512–514 (2023).

    Article  CAS  PubMed  Google Scholar 

  3. Hirose, T., Ninomiya, K., Nakagawa, S. & Yamazaki, T. A guide to membraneless organelles and their various roles in gene regulation. Nat. Rev. Mol. Cell Biol. 24, 288–304 (2023).

    Article  CAS  PubMed  Google Scholar 

  4. Lyon, A. S., Peeples, W. B. & Rosen, M. K. A framework for understanding the functions of biomolecular condensates across scales. Nat. Rev. Mol. Cell Biol. 22, 215–235 (2021).

    Article  CAS  PubMed  Google Scholar 

  5. Dzuricky, M., Rogers, B. A., Shahid, A., Cremer, P. S. & Chilkoti, A. De novo engineering of intracellular condensates using artificial disordered proteins. Nat. Chem. 12, 814–825 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Aumiller, W. M. & Keating, C. D. Phosphorylation-mediated RNA/peptide complex coacervation as a model for intracellular liquid organelles. Nat. Chem. 8, 129–137 (2016).

    Article  CAS  PubMed  Google Scholar 

  7. Abbas, M., Lipin, W. P., Wang, J. & Spruijt, E. Peptide-based coacervates as biomimetic protocells. Chem. Soc. Rev. 50, 3690–3705 (2021).

    Article  CAS  PubMed  Google Scholar 

  8. Priftis, D. et al. Self-assembly of α-helical polypeptides driven by complex coacervation. Angew. Chem. Int. Ed. 54, 11128–11132 (2015).

    Article  CAS  Google Scholar 

  9. Reichheld, S. E., Muiznieks, L. D., Keeley, F. W. & Sharpe, S. Direct observation of structure and dynamics during phase separation of an elastomeric protein. Proc. Natl Acad. Sci. USA 114, E4408–E4415 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Bini, E., Knight, D. P. & Kaplan, D. L. Mapping domain structures in silks from insects and spiders related to protein assembly. J. Mol. Biol. 335, 27–40 (2004).

    Article  CAS  PubMed  Google Scholar 

  11. Tan, Y. P. et al. Infiltration of chitin by protein coacervates defines the squid beak mechanical gradient. Nat. Chem. Biol. 11, 488–495 (2015).

    Article  CAS  PubMed  Google Scholar 

  12. Sun, Y., Hiew, S. H. & Miserez, A. Bioinspired squid peptides—a tale of curiosity-driven research leading to unforeseen biomedical applications. Acc. Chem. Res. 57, 164–174 (2023).

    Article  PubMed  Google Scholar 

  13. Chen, S. J., Guo, Q. & Yu, J. Bio-inspired functional coacervates. Aggregate 3, e293 (2022).

    Article  CAS  Google Scholar 

  14. Reichheld, S. E., Muiznieks, L. D., Lu, R., Sharpe, S. & Keeley, F. W. Sequence variants of human tropoelastin affecting assembly, structural characteristics and functional properties of polymeric elastin in health and disease. Matrix Biol. 84, 68–80 (2019).

    Article  CAS  PubMed  Google Scholar 

  15. Ceballos, A. V. et al. Liquid to solid transition of elastin condensates. Proc. Natl Acad. Sci. USA 119, e2202240119 (2022).

    Article  CAS  Google Scholar 

  16. Quiroz, F. G. et al. Intrinsically disordered proteins access a range of hysteretic phase separation behaviors. Sci. Adv. 5, eaax5177 (2019).

    Article  CAS  Google Scholar 

  17. Fawzi, N. L. Elastin phase separation—structure or disorder? Nat. Rev. Mol. Cell Biol. 21, 568–569 (2020).

    Article  CAS  PubMed  Google Scholar 

  18. Even-Ram, S., Artym, V. & Yamada, K. M. Matrix control of stem cell fate. Cell 126, 645–647 (2006).

    Article  CAS  PubMed  Google Scholar 

  19. Mosher, D. F. & Adams, J. C. Adhesion-modulating/matricellular ECM protein families: a structural, functional and evolutionary appraisal. Matrix Biol. 31, 155–161 (2012).

    Article  CAS  PubMed  Google Scholar 

  20. Barker, T. H. The role of ECM proteins and protein fragments in guiding cell behavior in regenerative medicine. Biomaterials 32, 4211–4214 (2011).

    Article  CAS  PubMed  Google Scholar 

  21. Patten, J. & Wang, K. Fibronectin in development and wound healing. Adv. Drug Deliv. Rev. 170, 353–368 (2021).

    Article  CAS  PubMed  Google Scholar 

  22. Karamanos, N. K. et al. Proteoglycan chemical diversity drives multifunctional cell regulation and therapeutics. Chem. Rev. 118, 9152–9232 (2018).

    Article  CAS  PubMed  Google Scholar 

  23. Theocharis, A. D., Skandalis, S. S., Gialeli, C. & Karamanos, N. K. Extracellular matrix structure. Adv. Drug Deliv. Rev. 97, 4–27 (2016).

    Article  CAS  PubMed  Google Scholar 

  24. Mouw, J. K., Ou, G. Q. & Weaver, V. M. Extracellular matrix assembly: a multiscale deconstruction. Nat. Rev. Mol. Cell Biol. 15, 771–785 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Hoffman, B. D., Grashoff, C. & Schwartz, M. A. Dynamic molecular processes mediate cellular mechanotransduction. Nature 475, 316–323 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Saraswathibhatla, A., Indana, D. & Chaudhuri, O. Cell–extracellular matrix mechanotransduction in 3D. Nat. Rev. Mol. Cell Biol. 24, 495–516 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Kanchanawong, P. & Calderwood, D. A. Organization, dynamics and mechanoregulation of integrin-mediated cell–ECM adhesions. Nat. Rev. Mol. Cell Biol. 24, 142–161 (2023).

    Article  CAS  PubMed  Google Scholar 

  28. Xu, Y. et al. ECM-inspired micro/nanofibers for modulating cell function and tissue generation. Sci. Adv. 6, eabc2036 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Colosi, C. et al. Microfluidic bioprinting of heterogeneous 3D tissue constructs using low-viscosity bioink. Adv. Mater. 28, 677–684 (2016).

    Article  CAS  PubMed  Google Scholar 

  30. Tseng, Q. Z. et al. Spatial organization of the extracellular matrix regulates cell–cell junction positioning. Proc. Natl Acad. Sci. USA 109, 1506–1511 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Glorevski, N. et al. Designer matrices for intestinal stem cell and organoid culture. Nature 539, 560–564 (2016).

    Article  Google Scholar 

  32. Green, J. J. & Elisseeff, J. H. Mimicking biological functionality with polymers for biomedical applications. Nature 540, 386–394 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Rosales, A. M. & Anseth, K. S. The design of reversible hydrogels to capture extracellular matrix dynamics. Nat. Rev. Mater. 1, 15012 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Strader, R. L., Shmidov, Y. & Chilkoti, A. Encoding structure in intrinsically disordered protein biomaterials. Acc. Chem. Res. 57, 302–311 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Ozsvar, J. et al. Tropoelastin and elastin assembly. Front. Bioeng. Biotechnol. 9, 643110 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Muiznieks, L. D. et al. Modulated growth, stability and interactions of liquid-like coacervate assemblies of elastin. Matrix Biol. 36, 39–50 (2014).

    Article  CAS  PubMed  Google Scholar 

  37. Vrhovski, B., Jensen, S. & Weiss, A. S. Coacervation characteristics of recombinant human tropoelastin. Eur. J. Biochem. 250, 92–98 (1997).

    Article  CAS  PubMed  Google Scholar 

  38. Varanko, A. K., Su, J. C. & Chilkoti, A. Elastin-like polypeptides for biomedical applications. Annu. Rev. Biomed. Eng. 22, 343–369 (2020).

    Article  CAS  PubMed  Google Scholar 

  39. Roberts, S. et al. Injectable tissue integrating networks from recombinant polypeptides with tunable order. Nat. Mater. 17, 1154–1163 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Despanie, J., Dhandhukia, J. P., Hamm-Alvarez, S. F. & MacKay, J. A. Elastin-like polypeptides: therapeutic applications for an emerging class of nanomedicines. J. Control. Release 240, 93–108 (2016).

    Article  CAS  PubMed  Google Scholar 

  41. van Strien, J., Escalona-Rayo, O., Jiskoot, W., Slütter, B. & Kros, A. Elastin-like polypeptide-based micelles as a promising platform in nanomedicine. J. Control. Release 353, 713–726 (2023).

    Article  PubMed  Google Scholar 

  42. Garanger, E. & Lecommandoux, S. Emerging opportunities in bioconjugates of elastin-like polypeptides with synthetic or natural polymers. Adv. Drug Deliv. Rev. 191, 114589 (2022).

    Article  CAS  PubMed  Google Scholar 

  43. Tian, X. et al. In situ formed depot of elastin-like polypeptide–hirudin fusion protein for long-acting antithrombotic therapy. Proc. Natl Acad. Sci. USA 121, e2314349121 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Feng, Z., Chen, X. D., Wu, X. D. & Zhang, M. J. Formation of biological condensates via phase separation: characteristics, analytical methods, and physiological implications. J. Biol. Chem. 294, 14823–14835 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Alberti, S., Gladfelter, A. & Mittag, T. Considerations and challenges in studying liquid–liquid phase separation and biomolecular condensates. Cell 176, 419–434 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Liu, J. H., Zhorabek, F., Dai, X., Huang, J. Q. & Chau, Y. Minimalist design of an intrinsically disordered protein-mimicking scaffold for an artificial membraneless organelle. ACS Cent. Sci. 8, 493–500 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Abbas, M., Lipinski, W. P., Nakashima, K. K., Huck, W. T. S. & Spruijt, E. A short peptide synthon for liquid–liquid phase separation. Nat. Chem. 13, 1046–1054 (2021).

    Article  CAS  PubMed  Google Scholar 

  48. Scott, W. A. et al. Active controlled and tunable coacervation using side-chain functional α-helical homopolypeptides. J. Am. Chem. Soc. 143, 18196–18203 (2021).

    Article  CAS  PubMed  Google Scholar 

  49. Liu, D. S., Nikoo, M., Boran, G., Zhou, P. & Regenstein, J. M. Collagen and gelatin. Annu. Rev. Food Sci. Technol. 6, 527–557 (2015).

    Article  CAS  PubMed  Google Scholar 

  50. Akahoshi, Y. et al. Phase-separation propensity of non-ionic amino acids in peptide-based complex coacervation systems. Biomacromolecules 24, 704–713 (2023).

    Article  CAS  PubMed  Google Scholar 

  51. Doshi, N. et al. Simple and complex coacervation in systems involving plant proteins. Soft Matter 20, 1966–1977 (2024).

    Article  CAS  PubMed  Google Scholar 

  52. Ito, S. et al. Improved hydration property of tissue adhesive/hemostatic microparticle based on hydrophobically-modified Alaska pollock gelatin. Biomater. Adv. 159, 213834 (2024).

    Article  CAS  PubMed  Google Scholar 

  53. Mohanty, B. & Bohidar, H. B. Systematic of alcohol-induced simple coacervation in aqueous gelatin solutions. Biomacromolecules 4, 1080–1086 (2003).

    Article  CAS  PubMed  Google Scholar 

  54. McTigue, W. C. B. & Perry, S. L. Protein encapsulation using complex coacervates: what nature has to teach us. Small 16, e1907671 (2020).

    Article  Google Scholar 

  55. Cook, A. B., Novosedlik, S. & van Hest, J. C. M. Complex coacervate materials as artificial cells. Acc. Mater. Res. 4, 287–298 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Martin, E. W. et al. Valence and patterning of aromatic residues determine the phase behavior of prion-like domains. Science 367, 694–699 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. 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).

    Article  CAS  PubMed  Google Scholar 

  58. Hong, Y. et al. Hydrophobicity of arginine leads to reentrant liquid–liquid phase separation behaviors of arginine-rich proteins. Nat. Commun. 13, 7326 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  59. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Malay, A. D. et al. Spider silk self-assembly via modular liquid–liquid phase separation and nanofibrillation. Sci. Adv. 6, eabb6030 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Stewart, R. J., Wang, C. S., Song, I. T. & Jones, J. P. The role of coacervation and phase transitions in the sandcastle worm adhesive system. Adv. Colloid Interface Sci. 239, 88–96 (2017).

    Article  CAS  PubMed  Google Scholar 

  62. Balu, R., Dutta, N. K., Dutta, A. K. & Choudhury, N. R. Resilin-mimetics as a smart biomaterial platform for biomedical applications. Nat. Commun. 12, 149 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Xie, X. et al. Biomimetic nanofibrillar hydrogel with cell-adaptable network for enhancing cellular mechanotransduction, metabolic energetics, and bone regeneration. J. Am. Chem. Soc. 145, 15218–15229 (2023).

    Article  CAS  PubMed  Google Scholar 

  64. Wang, H. Y. & Heilshorn, S. C. Adaptable hydrogel networks with reversible linkages for tissue engineering. Adv. Mater. 27, 3717–3736 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Mooney, D. J., Langer, R. & Ingber, D. E. Cytoskeletal filament assembly and the control of cell spreading and function by extracellular-matrix. J. Cell Sci. 108, 2311–2320 (1995).

    Article  CAS  PubMed  Google Scholar 

  66. Reznikov, N., Steele, J. A. M., Fratzl, P. & Stevens, M. M. A materials science vision of extracellular matrix mineralization. Nat. Rev. Mater. 1, 16041 (2016).

    Article  CAS  Google Scholar 

  67. Yang, B. G. et al. Enhanced mechanosensing of cells in synthetic 3D matrix with controlled biophysical dynamics. Nat. Commun. 12, 3514 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Zhang, K. Y., Feng, Q., Fang, Z. W., Gu, L. & Bian, L. M. Structurally dynamic hydrogels for biomedical applications: pursuing a fine balance between macroscopic stability and microscopic dynamics. Chem. Rev. 121, 11149–11193 (2021).

    Article  CAS  PubMed  Google Scholar 

  69. Zhao, P. C. et al. Directed conformational switching of a zinc finger analogue regulates the mechanosensing and differentiation of stem cells. Angew. Chem. Int. Ed. 61, e202203847 (2022).

    Article  CAS  Google Scholar 

  70. Scott, K. E., Fraley, S. I. & Rangamani, P. A spatial model of YAP/TAZ signaling reveals how stiffness, dimensionality, and shape contribute to emergent outcomes. Proc. Natl Acad. Sci. USA 118, e2021571118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Necci, M., Piovesan, D., Clementel, D., Dosztanyi, Z. & Tosatto, S. C. E. MobiDB-lite 3.0: fast consensus annotation of intrinsic disorder flavors in proteins. Bioinformatics 36, 5533–5534 (2020).

    Article  CAS  Google Scholar 

  72. Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Souza, P. C. T. et al. Martini 3: a general purpose force field for coarse-grained molecular dynamics. Nat. Methods 18, 382–388 (2021).

    Article  CAS  PubMed  Google Scholar 

  74. Alessandri, R. et al. Martini 3 coarse-grained force field: small molecules. Adv. Theor. Simul. 5, 2100391 (2022).

    Article  CAS  Google Scholar 

  75. Kroon, P. C. et al. Martinize2 and Vermouth: unified framework for topology generation. eLife 12, RP90627 (2023).

    Google Scholar 

  76. Huang, J. et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat. Methods 14, 71–73 (2017).

    Article  CAS  PubMed  Google Scholar 

  77. Vanommeslaeghe, K. et al. CHARMM general force field: a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J. Comput. Chem. 31, 671–690 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Vanommeslaeghe, K. & MacKerell, A. D. Automation of the CHARMMgeneral force field (CGenFF) I: bond perception and atom typing. J. Chem. Inf. Model. 52, 3144–3154 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Vanommeslaeghe, K., Raman, E. P. & MacKerell, A. D. Automation of the CHARMM general force field (CGenFF) II: assignment of bonded parameters and partial atomic charges. J. Chem. Inf. Model. 52, 3155–3168 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Yu, W. B., He, X. B., Vanommeslaeghe, K. & MacKerell, A. D. Extension of the CHARMM general force field to sulfonyl-containing compounds and its utility in biomolecular simulations. J. Chem. Inf. Model. 33, 2451–2468 (2012).

    CAS  Google Scholar 

  81. Mayne, C. G., Saam, J., Schulten, K., Tajkhorshid, E. & Gumbart, J. C. Rapid parameterization of small molecules using the force field toolkit. J. Chem. Inf. Model. 34, 2757–2770 (2013).

    CAS  Google Scholar 

  82. Frisch, M. et al. Gaussian 09, revision D.01 (Gaussian, 2009).

  83. Stark, A. C., Andrews, C. T. & Elcock, A. H. Toward optimized potential functions for protein–protein interactions in aqueous solutions: osmotic second virial coefficient calculations using the MARTINI coarse-grained force field. J. Chem. Theory Comput. 9, 4176–4185 (2013).

    Article  CAS  Google Scholar 

  84. Benayad, Z., von Bülow, S., Stelzl, L. S. & Hummer, G. Simulation of FUS protein condensates with an adapted coarse-grained model. J. Chem. Theory Comput. 17, 525–537 (2021).

    Article  CAS  PubMed  Google Scholar 

  85. Abraham, M. J. et al. GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1, 19–25 (2015).

    Article  Google Scholar 

  86. Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys. 126, 014101 (2007).

    Article  PubMed  Google Scholar 

  87. Parrinello, M. & Rahman, A. Polymer transitions in single-crystals—a new molecular-dynamic method. J. Appl. Phys. 52, 7182–7190 (1981).

    Article  CAS  Google Scholar 

  88. Barker, J. A. & Watts, R. O. Monte Carlo studies of the dielectric properties of water-like models. Mol. Phys. 26, 789–792 (2006).

    Article  Google Scholar 

  89. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. Model. 14, 33–38 (1996).

    Article  CAS  Google Scholar 

  90. Li, T. et al. MD simulation inputs and data. Zenodo https://doi.org/10.5281/zenodo.15111903 (2025).

Download references

Acknowledgements

This work was supported by National Natural Science Foundation of China (Key Program, grant number 52433010 to L.B.). This work was financially supported by the National Key Research and Development Program (reference 2022YFB3804403 to L.B.). This work was supported by the National Natural Science Foundation of China (grant number 52473129 to P.Z.) and the Fundamental Research Funds for the Central Universities (grant number 2023ZYGXZR096 to P.Z.). This work was also supported by the GJYC program of Guangzhou (grant number 2024D03J0004 to L.B. and P.Z.), Guangdong Basic and Applied Basic Research Foundation (grant number 2025A1515012036 to P.Z.). This work was supported by the Collaborative Research Fund from the Research Grants Council of Hong Kong (project number C5044-21G to L.B.). This work was supported by the Health and Medical Research Fund, the Food and Health Bureau, the Government of the Hong Kong Special Administrative Region (08190416 to L.B.). This work was partially supported by the Research Grants Council Areas of Excellence Scheme (reference number AoE/M402/20 to L.B. and AoE/P-705/16 to Y.W.). We thank X. Yang for valuable discussions.

Author information

Authors and Affiliations

Contributions

L.B., P.Z. and Y.W. supervised the study. X.X., L.B. and P.Z. conceived of and designed the experiments. T.L. and Y.Q. contributed to the computational experiments. L.M. contributed to the AFM experiments. J.W. contributed to the microrheological tests. X.X., T.L., L.M., J.W., Y.Q., B.Y., Z.L., Z.Y., K.Z., Z.C., T.N., J.X., Y.W., P.Z. and L.B. provided discussions and analysed the experiments. X.X. and L.B. wrote the paper. All authors contributed to the final paper.

Corresponding authors

Correspondence to Yi Wang, Pengchao Zhao or Liming Bian.

Ethics declarations

Competing interests

A patent application by L.B., based on the methods presented in this paper, has been filed. The other authors declare no competing interests.

Peer review

Peer review information

Nature Chemistry thanks J. Andrew MacKay and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 The increased valence of hydrophobic moieties decreases the internal dynamics of coacervates.

a, Fluorescence images of the FRAP recovery of Cy5-labelled coacervates with different valences. b, FRAP measurements showing a dramatic decrease in recovery speed with increasing valence (n = 3 independent coacervates per group). Data are presented as mean values ± SD. c, Relative mean-square displacement of nanoparticles encapsulated in the Coa-Nap-L, Coa-Nap, and Coa-Nap-P coacervates. d, The water content decreased with increasing valence (n = 3 independent coacervates per group). Data are presented as mean values ± SD. Statistical analyses were performed using ordinary one-way analysis of variance (ANOVA) with Tukey’s post hoc test. Statistical significance: #P < 0.0001 (Coa-Nap-L vs. Coa-Nap), ***P = 0.0003 (Coa-Nap vs. Coa-Nap-P), #P < 0.0001 (Coa-Nap-L vs. Coa-Nap-P).

Source data

Extended Data Fig. 2 Structural and dynamic properties of the gelatin-based coacervates in MD simulations.

a-b, Specific surface area (SSA) (a), and density (b) of the complex in the last 1 µs of the 5-µs simulations. c, Average end-to-end distance of gelatin chains. d, Mean squared displacement (MSD) of gelatin chains in the x-y dimension during the last 1 µs of simulations. Diffusion coefficients of the gelatin chains are labelled on the corresponding MSD curves with a unit of 10−7 cm2/s. In all panels, shaded regions and error bars stand for the standard error of the means calculated from four replicas (n = 4). Statistical analyses were performed using ordinary one-way analysis of variance (ANOVA) with Tukey’s post hoc test. Statistical significance: #P < 0.0001.

Source data

Supplementary information

Supplementary Information (download PDF )

Supplementary Figs. 1–33, Tables 1–4 and synthesis of compounds.

Reporting Summary (download PDF )

Supplementary Video 1 (download MP4 )

Flowability of gelatin coacervate.

Supplementary Video 2 (download MP4 )

MD simulation (run1) of Gel.

Supplementary Video 3 (download MP4 )

MD simulation (run1) of Coa-Nap-L.

Supplementary Video 4 (download MP4 )

MD simulation (run1) of Coa-Nap.

Supplementary Video 5 (download MP4 )

MD simulation (run1) of Coa-Nap-P.

Supplementary Table 1 (download XLSX )

Sequences of primers.

Source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xie, X., Li, T., Ma, L. et al. A designer minimalistic model parallels the phase-separation-mediated assembly and biophysical cues of extracellular matrix. Nat. Chem. 17, 1216–1226 (2025). https://doi.org/10.1038/s41557-025-01837-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41557-025-01837-5

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing