Branched peptides integrate into self-assembled nanostructures and enhance biomechanics of peptidic hydrogels

Raffaele Pugliese, Federico Fontana, Amanda Marchini, Fabrizio Gelain

Research output: Contribution to journalArticlepeer-review


Self-assembling peptides (SAP) have drawn an increasing interest in the tissue engineering community. They display unquestionable biomimetic properties, tailorability and promising biocompatibility. However their use has been hampered by poor mechanical properties making them fragile soft scaffolds. To increase SAP hydrogel stiffness we introduced a novel strategy based on multiple ramifications of (LDLK)3, a well-known linear SAP, connected with one or multiple “lysine knots”. Differently branched SAPs were tested by increasing the number of (LDLK)3-like branches and by adding the neuro-regenerative functional motif BMHP1 as a single branch. While pure branched peptides did not have appealing self-assembling propensity, when mixed with the corresponding linear SAP they increased the stiffness of the overall hydrogel of multiple times. Notably, optimal results (or peak) were obtained 1) at similar molar ratio (between linear and branched peptides) for all tested sequences and 2) for the branched SAPs featuring the highest number of branches made of (LDLK)3. The functional motif BMHP1, as expected, seemed not to contribute to the increase of the storage modulus as efficiently as (LDLK)3. Interestingly, branched SAPs improved the β-sheet self-arrangement of (LDLK)3 and allowed for the formation of assembled nanofibers. Indeed in coarse-grained molecular dynamics we showed they readily integrate in the assembled aggregates providing “molecular connections” among otherwise weakly paired β-structures. Lastly, branched SAPs did not affect the usual response of human neural stem cells cultured on (LDLK)3-like scaffolds in vitro. Hence, branched SAPs may be a valuable new tool to enhance mechanical properties of self-assembling peptide biomaterials harmlessly; as neither chemical nor enzymatic cross-linking reactions are involved. As a consequence, branched SAPs may enlarge the field of application of SAPs in tissue engineering and beyond. Statement of Significance Self-assembling peptides stand at the forefront of regenerative medicine because they feature biomimetic nano-architectures that mimic the complexity of natural peptide-based extracellular matrices of living tissues. Their superior biocompatibility and ease of scale-up production are hampered by weak mechanical properties due to transient non-covalent interactions among and within the self-assembled peptide chains, thus limiting their potential applications. We introduced new branched self-assembling peptides to be used as “molecular connectors” among self-assembled nanostructures made of linear SAPs. Branched SAPs could be mixed with linear SAPs before self-assembling in order to have them intermingled with different β-sheets of linear SAPs after gelation. This strategy caused a manifold increase of the stiffness of the assembled hydrogels (proportional to the number of self-assembling branches), did not affect SAP propensity to form β-sheet but, instead, further stimulated their secondary structure rearrangements. It is now possible to modularly improve SAP scaffold mechanical properties without using harmful chemical reactions. Therefore, branched SAPs represent an additional tool to be adopted for efficient and harmless SAP scaffold customization in tissue engineering.

Original languageEnglish
Pages (from-to)258-271
Number of pages14
JournalActa Biomaterialia
Publication statusPublished - Jan 15 2018


  • Branched self-assembling peptide
  • Coarse-grained dynamics
  • Nanostructured scaffold
  • Neural stem cells
  • Rheology

ASJC Scopus subject areas

  • Biotechnology
  • Biomaterials
  • Biochemistry
  • Biomedical Engineering
  • Molecular Biology


Dive into the research topics of 'Branched peptides integrate into self-assembled nanostructures and enhance biomechanics of peptidic hydrogels'. Together they form a unique fingerprint.

Cite this