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Stimulus-responsive Self-Assembly of Enzymatic Fractals by Computational Design

Nancy E. Hernández, William A. Hansen, Denzel Zhu, Maria E. Shea, Marium Khalid, Viacheslav Manichev, Matthew Putnis, Muyuan Chen, Anthony G. Dodge, Lu Yang, Melissa Banal, Torgny Gustaffson, Leonard C. Feldman, Sang-Hyuk Lee, Lawrence P. Wackett, Wei Dai, View ORCID ProfileSagar D. Khare
doi: https://doi.org/10.1101/274183
Nancy E. Hernández
1Department of Chemistry & Chemical Biology, Rutgers University, Piscataway, NJ
2Institute for Quantitative Biomedicine, Rutgers University, Piscataway, NJ
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William A. Hansen
2Institute for Quantitative Biomedicine, Rutgers University, Piscataway, NJ
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Denzel Zhu
3Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ
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Maria E. Shea
4Department of Molecular Biology & Biochemistry, Rutgers University, Piscataway, NJ
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Marium Khalid
5Department of Biomedical Engineering, Rutgers University, Piscataway, NJ
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Viacheslav Manichev
1Department of Chemistry & Chemical Biology, Rutgers University, Piscataway, NJ
6Institute of Advanced Materials, Devices, and Nanotechnology, Rutgers University, Piscataway NJ
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Matthew Putnis
2Institute for Quantitative Biomedicine, Rutgers University, Piscataway, NJ
5Department of Biomedical Engineering, Rutgers University, Piscataway, NJ
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Muyuan Chen
7Program in Structural and Computational Biology and Molecular Biophysics, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX
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Anthony G. Dodge
8BioTechnology Institute, University of Minnesota, St. Paul, MN
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Lu Yang
1Department of Chemistry & Chemical Biology, Rutgers University, Piscataway, NJ
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Melissa Banal
9Department of Cell Biology and Neuroscience, Rutgers, University, Piscataway, NJ
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Torgny Gustaffson
6Institute of Advanced Materials, Devices, and Nanotechnology, Rutgers University, Piscataway NJ
10Department of Physics and Astronomy, Rutgers University, Piscataway, NJ
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Leonard C. Feldman
6Institute of Advanced Materials, Devices, and Nanotechnology, Rutgers University, Piscataway NJ
10Department of Physics and Astronomy, Rutgers University, Piscataway, NJ
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Sang-Hyuk Lee
2Institute for Quantitative Biomedicine, Rutgers University, Piscataway, NJ
10Department of Physics and Astronomy, Rutgers University, Piscataway, NJ
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Lawrence P. Wackett
8BioTechnology Institute, University of Minnesota, St. Paul, MN
11Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, St. Paul, MN
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Wei Dai
2Institute for Quantitative Biomedicine, Rutgers University, Piscataway, NJ
9Department of Cell Biology and Neuroscience, Rutgers, University, Piscataway, NJ
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Sagar D. Khare
1Department of Chemistry & Chemical Biology, Rutgers University, Piscataway, NJ
2Institute for Quantitative Biomedicine, Rutgers University, Piscataway, NJ
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  • ORCID record for Sagar D. Khare
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Abstract

Fractal topologies, which are statistically self-similar over multiple length scales, are pervasive in nature. The recurrence of patterns at increasing length scales in fractal-shaped branched objects, e.g., trees, lungs, and sponges, results in high effective surface areas, and provides key functional advantages, e.g., for molecular trapping and exchange. Mimicking these topologies in designed protein-based assemblies will provide access to novel classes of functional biomaterials for wide ranging applications. Here, we describe a modular, multi-scale computational design method for the reversible self-assembly of proteins into tunable supramolecular fractal-like topologies in response to phosphorylation. Computationally-guided atomic-resolution modeling of fusions of symmetric, oligomeric proteins with Src homology 2 (SH2) binding domain and its phosphorylatable ligand peptide was used to design iterative branching leading to fractal-like assembly formation by enzymes of the atrazine degradation pathway. Structural characterization using various microscopy techniques and Cryo-electron tomography revealed a variety of dendritic, hyperbranched, and sponge-like topologies which are self-similar over three decades (∼10nm-10μm) of length scale, in agreement with models from multi-scale computational simulations. We demonstrate control over mesoscale topology (by linker design), formation dynamics, and functional enhancements due to dynamic multi-component assemblies constructed with three atrazine degradation pathway enzymes. The described design method should enable the construction of a variety of novel, spatiotemporally responsive catalytic biomaterials featuring fractal topologies.

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Posted March 01, 2018.
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Stimulus-responsive Self-Assembly of Enzymatic Fractals by Computational Design
Nancy E. Hernández, William A. Hansen, Denzel Zhu, Maria E. Shea, Marium Khalid, Viacheslav Manichev, Matthew Putnis, Muyuan Chen, Anthony G. Dodge, Lu Yang, Melissa Banal, Torgny Gustaffson, Leonard C. Feldman, Sang-Hyuk Lee, Lawrence P. Wackett, Wei Dai, Sagar D. Khare
bioRxiv 274183; doi: https://doi.org/10.1101/274183
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Stimulus-responsive Self-Assembly of Enzymatic Fractals by Computational Design
Nancy E. Hernández, William A. Hansen, Denzel Zhu, Maria E. Shea, Marium Khalid, Viacheslav Manichev, Matthew Putnis, Muyuan Chen, Anthony G. Dodge, Lu Yang, Melissa Banal, Torgny Gustaffson, Leonard C. Feldman, Sang-Hyuk Lee, Lawrence P. Wackett, Wei Dai, Sagar D. Khare
bioRxiv 274183; doi: https://doi.org/10.1101/274183

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