Stimulus-responsive self-assembly of protein-based fractals by computational design

Abstract

Fractal topologies, which are statistically self-similar over multiple length scales, are pervasive in nature. The recurrence of patterns in fractal-shaped branched objects, such as trees, lungs and sponges, results in a high surface area to volume ratio, which provides key functional advantages including molecular trapping and exchange. Mimicking these topologies in designed protein-based assemblies could provide access to functional biomaterials. Here we describe a computational design approach for the reversible self-assembly of proteins into tunable supramolecular fractal-like topologies in response to phosphorylation. Guided by atomic-resolution models, we develop fusions of Src homology 2 (SH2) domain or a phosphorylatable SH2-binding peptide, respectively, to two symmetric, homo-oligomeric proteins. Mixing the two designed components resulted in a variety of dendritic, hyperbranched and sponge-like topologies that are phosphorylation-dependent and self-similar over three decades (~10 nm–10 μm) of length scale, in agreement with models from multiscale computational simulations. Designed assemblies perform efficient phosphorylation-dependent capture and release of cargo proteins.

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Fig. 1: Multiscale computational design approach for fractal assembly design.
Fig. 2: Assembly formation, dissolution and inhibition in vitro.
Fig. 3: Assembly formation and characterization with helium ion microscopy, AFM and transmission electron microscopy.
Fig. 4: Assembly characterization with cryo-ET.
Fig. 5: Fractal assemblies capture and release greater amounts of cargo compared to globular assemblies.

Data availability

The authors declare that all data supporting the findings of this study are available within the paper and its Supplementary Information files. Raw data used to generate all figures are available via Figshare (https://figshare.com/projects/Stimulus-responsive_Self-Assembly_of_Protein-Based_Fractals_by_Computational_Design/61976), and cryo-ET maps are available in the EMDB (accession codes EMD-20062 and EMD-20063).

Code availability

Scripts and input files used for Rosetta simulations and code used for coarse-grained simulations are available from a GitHub repository (https://github.com/sagark101/Nchem-Fractal-Assembly).

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Acknowledgements

The authors acknowledge support from the NSF (1330760 to S.D.K. and L.W.; DGE-1433187 to N.E.H.; 1429062 to S.D.K.) and the NIH (R01GM080139 to M.C.). Cryoelectron microscopy was supported by the Rutgers New Jersey CryoEM/ET Core Facility. The authors thank J. Chodera for providing Src kinase and YopH phosphatase plasmids, V. Nanda, K.-B. Lee, G. Montelione, H. Cho, M. Liu, A. Permaul, O. Dineen, I. Patel and R. Patel for experimental assistance, and E. Tinberg, V. Nanda and D. Baker for helpful discussions.

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Contributions

N.E.H. and W.A.H. contributed equally to this work. N.E.H., W.A.H. and S.D.K. designed the research. W.A.H. developed the computational methodology for design and image analyses. N.E.H., D.Z., M.E.S. and M.K. expressed, purified and assayed proteins. N.E.H., V.M., T.G. and L.C.F. performed HIM. N.E.H., M.P., P.R. and S.-H.L. performed optical and fluorescence microscopy. D.Z. performed DLS, M.K. performed BLI and L.Y. performed TEM. I.M.-B. performed confocal microscopy. A.G.D. and L.P.W. performed polymer foam immobilization and activity assays. W.D., M.B., M.C. and W.A.H. performed cryo-ET and analyses. S.D.K., N.E.H. and W.A.H. wrote the manuscript. All authors discussed the results and commented on the manuscript.

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Correspondence to Sagar D. Khare.

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Supplementary information

Supplementary Information

Supplementary Information contains the methods section, additional discussion and references section, Supplementary Figs. 1 to 37, Supplementary Tables 1 to 3 and descriptions of Supplementary Videos 1 to 3

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A zip file containing scripts

Supplementary Video 1

Formation of dendritic assemblies by AtzC-SH2 and AtzA-pY proteins visualized by light microscopy

Supplementary Video 2

Cryo-electron tomography data and node assignments for a small (<20 connected component-containing) assembly

Supplementary Video 3

Cryo-electron tomography data and node assignments for the large (~6,000 connected component-containing) assembly

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Hernández, N.E., Hansen, W.A., Zhu, D. et al. Stimulus-responsive self-assembly of protein-based fractals by computational design. Nat. Chem. 11, 605–614 (2019). https://doi.org/10.1038/s41557-019-0277-y

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