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

Nancy E. Hernández, William A. Hansen, Denzel Zhu, Maria E. Shea, Marium Khalid, Viacheslav Manichev, Matthew Putnins, Muyuan Chen, Anthony G. Dodge, Lu Yang, Ileana Marrero-Berríos, Melissa Banal, Phillip Rechani, Torgny Gustafsson, Leonard C. Feldman, Sang Hyuk Lee, Lawrence P. Wackett, Wei Dai, Sagar D. Khare

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)605-614
Number of pages10
JournalNature Chemistry
Issue number7
StatePublished - Jul 1 2019

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)


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