On the Mechanism of Self-Assembly by a Hydrogel-Forming Peptide

Research output: Contribution to journalArticle


Self-assembling peptide-based hydrogels are a class of tunable soft materials that have been shown to be highly useful for a number of biomedical applications. The dynamic formation of the supramolecular fibrils that compose these materials has heretofore remained poorly characterized. A better understanding of this process would provide important insights into the behavior of these systems and could aid in the rational design of new peptide hydrogels. Here, we report the determination of the microscopic steps that underpin the self-assembly of a hydrogel-forming peptide, SgI37-49. Using theoretical models of linear polymerization to analyze the kinetic self-assembly data, we show that SgI37-49 fibril formation is driven by fibril-catalyzed secondary nucleation and that all the microscopic processes involved in SgI37-49 self-assembly display an enzyme-like saturation behavior. Moreover, this analysis allows us to quantify the rates of the underlying processes at different peptide concentrations and to calculate the time evolution of these reaction rates over the time course of self-assembly. We demonstrate here a new mechanistic approach for the study of self-assembling hydrogel-forming peptides, which is complementary to commonly used materials science characterization techniques.


  • Gabriel A. Braun
  • Beatrice E. Ary
  • Alexander J. Dear
  • Matthew C.H. Rohn
  • Abigail M. Payson
  • David S.M. Lee
  • Robert C. Parry
  • Connie Friedman
  • Tuomas P.J. Knowles
  • Sara Linse
  • Karin S. Åkerfeldt
External organisations
  • Haverford College
  • University of Cambridge
  • Harvard University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Biochemistry and Molecular Biology
  • Polymer Chemistry
Original languageEnglish
Pages (from-to)4781-4794
Number of pages14
Issue number12
Early online date2020 Nov 10
Publication statusPublished - 2020 Dec 14
Publication categoryResearch