Peptides that self-assemble into nanostructures are of tremendous interest for biological, medical, photonic and nanotechnological applications. The enormous sequence space that is available from 20 amino acids probably harbours many interesting candidates, but it is currently not possible to predict supramolecular behaviour from sequence alone. Here, we demonstrate computational tools to screen for the aqueous self-assembly propensity in all of the 8,000 possible tripeptides and evaluate these by comparison with known examples. We applied filters to select for candidates that simultaneously optimize the apparently contradicting requirements of aggregation propensity and hydrophilicity, which resulted in a set of design rules for self-assembling sequences. A number of peptides were subsequently synthesized and characterized, including the first reported tripeptides that are able to form a hydrogel at neutral pH. These tools, which enable the peptide sequence space to be searched for supramolecular properties, enable minimalistic peptide nanotechnology to deliver on its promise.

We report on a simple carbohydrate amphiphile able to self-assemble into nanofibers upon enzymatic dephosphorylation. The self-assembly can be triggered by alkaline phosphatase (ALP) in solution or in situ by the ALP produced by osteosarcoma cell line, SaOs2. In the latter case, assembly and localized gelation occurs mainly on the cell surface. The gelation of the pericellular environment induces a reduction of the SaOs2 metabolic activity at an initial stage (≤7 h) that results in cell death at longer exposure periods (≥24 h). We show that this effect depends on the phosphatase concentration, and thus, it is cell-selective with prechondrocytes ATDC5 (that express ∼15-20 times lower ALP activity compared to SaOs2) not being affected at concentrations ≤1 mM. These results demonstrate that simple carbohydrate derivatives can be used in an antiosteosarcoma strategy with limited impact on the surrounding healthy cells/tissues.

Here, we use a closed-loop discovery and optimization approach for searching the peptide sequence space. Combining an evolutionary algorithm with machine learning and in vitro assay allowed for rapid development of new antimicrobial peptides.

Peptide co-assembly is of interest for the development of functional supramolecular biomaterials. Herein, computational simulations were combined with experimental validation to aid the design and understanding of cooperative co-assembly of a structure-forming tripeptide (FFD) and a functional copper-binding tripeptide (GHK) leading to hydrogel formation in response to complexation with copper ions.

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A modular two-component supramolecular hydrogel composed of a peptide core and carbohydrate shell as a minimalistic mimic of proteoglycans.

Co-assembly of peptides and polysaccharides can give rise to formation of nanostructures with tunable morphologies. We show that in situ enzymatic exchange of a dipeptide sequences in aromatic peptide amphiphiles/polysaccharide co-assemblies enables dynamic formation and degradation of different nanostructures depending on the nature of the polysaccharide present. This is achieved in a one-pot system composed of Fmoc-cystic acid (CA), Fmoc-lysine (K) plus phenylalanine amide (F) in the presence of thermolysin which, through dynamic hydrolysis and amide formation gives rise to dynamic peptide library composed of the corresponding Fmocdipeptides (CAF and KF). When the cationic polysaccharide chitosan is added to this mixture, selective amplification of the CAF peptide is observed giving rise to formation of nanosheets through co-assembly. By contrast, upon addition of anionic heparin, KF is formed which gives rise to a nanotube morphology. The dynamic adaptive potential was demonstrated by sequential morphology changes depending on the sequence of polysaccharide addition. This first demonstration of the ability to access different peptide sequences and nanostructures depending on presence of biopolymers may pave the way to biomaterials that can adapt their structure and function and may be of relevance in design of materials able to undergo dynamic morphogenesis.

Millions of years of biological evolution have driven the development of highly sophisticated molecular machinery found within living systems. These systems produce polymers such as proteins and nucleic acids with incredible fidelity and function. In nature, the precise molecular sequence is the factor that determines the function of these macromolecules. Given that the ability to precisely define sequence emerges naturally, the fact that biology achieves unprecedented control over the unit sequence of the monomers through evolved enzymatic catalysis is incredible. Indeed, the ability to engineer systems that allow polymer synthesis with precise sequence control is a feat that technology is yet to replicate in artificial synthetic systems. This is the case because, without access to evolutionary control for finely tuned biological catalysts, the inability to correct errors or harness multiple competing processes means that the prospects for digital control of polymerization have been firmly bootstrapped to biological systems or limited to stepwise synthetic protocols. In this Account, we give an overview of strategies that have been used over the last 5 years in efforts to program polymer synthesis with sequence control in the laboratory. We also briefly explore how the use of robotics, algorithms, and stochastic chemical processes might lead to new understanding, mechanisms, and strategies to achieve full digital control. The aim is to see whether it is possible to go beyond bootstrapping to biological polymers or stepwise chemical synthesis. We start by describing nonenzymatic techniques used to obtain sequence-controlled natural polymers, a field that lends itself to direct application of insights gleaned from biology. We discuss major advances, such as the use of rotaxane-based molecular machines and templated approaches, including the utilization of biological polymers as templates for purely synthetic chains. We then discuss synthetic polymer chemistry, whose array of techniques allows the production of polymers with enormous structural and functional diversity, but so far with only limited control over the unit sequence itself. Synthetic polymers can be subdivided into multiple classes depending on the nature of processes used to synthesize them, such as by addition or condensation. Consequently, varied approaches for sequence control have been demonstrated in the area, including but not limited to click reactions, iterative solid-phase chemistry, and exploiting the chemical affinity of the monomers themselves. In addition to those, we highlight the importance of environmental bias in possible control of polymerization at the single-unit level, such as using catalyst switching or external stimuli. Even the most successful experimental sequence control approach needs appropriate tools to verify its scope and validity; therefore, we devote part of the present Account to possible analytical approaches to sequence readout, starting with well-established tandem mass spectrometry techniques and touching on those...