Avoiding common pitfalls in designing kinetic protocols for catalytic amyloid studies.

Kinetic characterization of catalytic amyloids arguably presents a most challenging type of kinetic experiment where careful consideration of many factors is required. Here we outline common pitfalls in devising kinetic studies in such systems. Unlike the more specific protocols for various applications described in this volume, this chapter deals with general issues in setting up kinetic experiments that are incredibly important but often go without explicit mention in the specialized literature. The kinetic fundamentals described here can be also be of use to the enzymologists working with more traditional catalysts.

Screening of oxidative behavior in catalytic amyloid assemblies.

Once considered a thermodynamic minimum of the protein fold or as simply by-products of a misfolding process, amyloids are increasingly showing remarkable potential for promoting enzyme-like catalysis. Recent studies have demonstrated a diverse range of catalytic behaviors that amyloids can promote way beyond the hydrolytic behaviors originally reported. We and others have demonstrated the strong propensity of catalytic amyloids to facilitate redox reactions both in the presence and in the absence of metal cofactors. Here, we present a detailed protocol for measuring the oxidative ability of supramolecular peptide assemblies.

Computational modelling of supramolecular metallopeptide assemblies.

Among the important questions in supramolecular peptide self-assemblies are their interactions with metallic compounds and ions. In the last decade, intensive efforts have been devoted to understanding the structural properties of these interactions including their dynamical and catalytic impact in natural and de novo systems. Since structural insights from experimental approaches could be particularly challenging, computational chemistry methods are interesting complementary tools. Here, we present the general multiscale strategies we developed and applied for the study of metallopeptide assemblies. These strategies include prediction of metal binding site, docking of metallic moieties, classical and accelerated molecular dynamics and finally QM/MM calculations. The systems of choice for this chapter are, on one side, peptides involved in neurodegenerative diseases and, on the other, de novo fibrillar systems with catalytic properties. Both successes and remaining challenges are highlighted so that the protocol could be apply to other system of this kind.

Fishing for Catalysis: Experimental Approaches to Narrowing Search Space in Directed Evolution of Enzymes.

Directed evolution has transformed protein engineering offering a path to rapid improvement of protein properties. Yet, in practice it is limited by the hyper-astronomic protein sequence search space, and approaches to identify mutagenic hot spots, i.e., locations where mutations are most likely to have a productive impact, are needed. In this perspective, we categorize and discuss recent progress in the experimental approaches (broadly defined as structural, bioinformatic, and dynamic) to hot spot identification. Recent successes in harnessing protein dynamics and machine learning approaches provide new opportunities for the field and will undoubtedly help directed evolution reach its full potential.

Machine learning overcomes human bias in the discovery of self-assembling peptides.

Peptide materials have a wide array of functions, from tissue engineering and surface coatings to catalysis and sensing. Tuning the sequence of amino acids that comprise the peptide modulates peptide functionality, but a small increase in sequence length leads to a dramatic increase in the number of peptide candidates. Traditionally, peptide design is guided by human expertise and intuition and typically yields fewer than ten peptides per study, but these approaches are not easily scalable and are susceptible to human bias. Here we introduce a machine learning workflow-AI-expert-that combines Monte Carlo tree search and random forest with molecular dynamics simulations to develop a fully autonomous computational search engine to discover peptide sequences with high potential for self-assembly. We demonstrate the efficacy of the AI-expert to efficiently search large spaces of tripeptides and pentapeptides. The predictability of AI-expert performs on par or better than our human experts and suggests several non-intuitive sequences with high self-assembly propensity, outlining its potential to overcome human bias and accelerate peptide discovery.

NMR-guided directed evolution.

Directed evolution is a powerful tool for improving existing properties and imparting completely new functionalities to proteins1-4. Nonetheless, its potential in even small proteins is inherently limited by the astronomical number of possible amino acid sequences. Sampling the complete sequence space of a 100-residue protein would require testing of 20100 combinations, which is beyond any existing experimental approach. In practice, selective modification of relatively few residues is sufficient for efficient improvement, functional enhancement and repurposing of existing proteins5. Moreover, computational methods have been developed to predict the locations and, in certain cases, identities of potentially productive mutations6-9. Importantly, all current approaches for prediction of hot spots and productive mutations rely heavily on structural information and/or bioinformatics, which is not always available for proteins of interest. Moreover, they offer a limited ability to identify beneficial mutations far from the active site, even though such changes may markedly improve the catalytic properties of an enzyme10. Machine learning methods have recently showed promise in predicting productive mutations11, but they frequently require large, high-quality training datasets, which are difficult to obtain in directed evolution experiments. Here we show that mutagenic hot spots in enzymes can be identified using NMR spectroscopy. In a proof-of-concept study, we converted myoglobin, a non-enzymatic oxygen storage protein, into a highly efficient Kemp eliminase using only three mutations. The observed levels of catalytic efficiency exceed those of proteins designed using current approaches and are similar with those of natural enzymes for the reactions that they are evolved to catalyse. Given the simplicity of this experimental approach, which requires no a priori structural or bioinformatic knowledge, we expect it to be widely applicable and to enable the full potential of directed enzyme evolution.

De novo designed peptides form a highly catalytic ordered nanoarchitecture on a graphite surface.

Here we demonstrate that short peptides, de novo designed from first principles, self-assemble on the surface of graphite to produce a highly robust and catalytic nanoarchitecture, which promotes peroxidation reactions with activities that rival those of natural enzymes in both single and multi-substrate reactions. These designable peptides recapitulate the symmetry of the underlying graphite surface and act as molecular scaffolds to immobilize hemin molecules on the electrode in a hierarchical self-assembly manner. The highly ordered and uniform hybrid graphite-peptide-hemin nanoarchitecture shows the highest faradaic efficiency of any hybrid electrode reported. Given the explosive growth of the types of chemical reactions promoted by self-assembled peptide materials, this new approach to creating complex electrocatalytic assemblies will yield highly efficient and practically applicable electrocatalysts.

Catalytic amyloids: Is misfolding folding?

Originally regarded as a disease symptom, amyloids have shown a rich diversity of functions, including biologically beneficial ones. As such, the traditional view of polypeptide aggregation into amyloid-like structures being 'misfolding' should rather be viewed as 'alternative folding.' Various amyloid folds have been recently used to create highly efficient catalysts with specific catalytic efficiencies rivaling those of enzymes. Here we summarize recent developments and applications of catalytic amyloids, derived from both de novo and bioinspired designs, and discuss how progress in the last 2 years reflects on the field as a whole.

Self-Assembling Catalytic Peptide Nanomaterials Capable of Highly Efficient Peroxidase Activity.

The self-assembly of short peptides gives rise to versatile nanomaterials capable of promoting efficient catalysis. We have shown that short, seven-residue peptides bind hemin to produce functional catalytic materials which display highly efficient peroxidation activity, reaching a catalytic efficiency of 3×105 m-1 s-1 . Self-assembly is essential for catalysis as non-assembling controls show no activity. We have also observed peroxidase activity even in the absence of hemin, suggesting the potential to alter redox properties of substrates upon association with the assemblies. These results demonstrate the practical utility of self-assembled peptides in various catalytic applications and further support the evolutionary link between amyloids and modern-day enzymes.

Covalent Linkage and Macrocylization Preserve and Enhance Synergistic Interactions in Catalytic Amyloids.

The self-assembly of short peptides into catalytic amyloid-like nanomaterials has proven to be a powerful tool in both understanding the evolution of early proteins and identifying new catalysts for practically useful chemical reactions. Here we demonstrate that both parallel and antiparallel arrangements of ß-sheets can accommodate metal ions in catalytically productive coordination environments. Moreover, synergistic relationships, identified in catalytic amyloid mixtures, can be captured in macrocyclic and sheet-loop-sheet species, that offer faster rates of assembly and provide more complex asymmetric arrangements of functional groups, thus paving the way for future designs of amyloid-like catalytic proteins. Our findings show how initial catalytic activity in amyloid assemblies can be propagated and improved in more-complex molecules, providing another link in a complex evolutionary chain between short, potentially abiotically produced peptides and modern-day enzymes.

Synergistic Interactions Are Prevalent in Catalytic Amyloids.

Interactions between multiple functional groups are key to catalysis. Previously, we reported synergistic interactions in catalytic amyloids formed by mixtures of heptameric peptides that lead to significant improvements in esterase activity. Herein, we describe the in-depth investigation of synergistic interactions within a family of amyloid fibrils, exploring the results of functional group interactions, the effects of chirality and the use of mixed enantiomers within fibrils. Remarkably, we find that synergistic interactions (either positive or negative) are found in the vast majority of binary mixtures of catalytic amyloid-forming peptides. The productive arrangements of functionalities rapidly identified by mixing different peptides will undoubtedly lead to the development of more active catalysts for a variety of different transformations.

Semi-Rationally Designed Short Peptides Self-Assemble and Bind Hemin to Promote Cyclopropanation.

The self-assembly of short peptides gives rise to versatile nanoassemblies capable of promoting efficient catalysis. We have semi-rationally designed a series of seven-residue peptides that form hemin-binding catalytic amyloids to facilitate enantioselective cyclopropanation with efficiencies that rival those of engineered hemin proteins. These results demonstrate that: 1) Catalytic amyloids can bind complex metallocofactors to promote practically important multisubstrate transformations. 2) Even essentially flat surfaces of amyloid assemblies can impart a substantial degree of enantioselectivity without the need for extensive optimization. 3) The ease of peptide preparation allows for straightforward incorporation of unnatural amino acids and the preparation of peptides made from d-amino acids with complete reversal of enantioselectivity.

De novo protein design, a retrospective.

Proteins are molecular machines whose function depends on their ability to achieve complex folds with precisely defined structural and dynamic properties. The rational design of proteins from first-principles, or de novo, was once considered to be impossible, but today proteins with a variety of folds and functions have been realized. We review the evolution of the field from its earliest days, placing particular emphasis on how this endeavor has illuminated our understanding of the principles underlying the folding and function of natural proteins, and is informing the design of macromolecules with unprecedented structures and properties. An initial set of milestones in de novo protein design focused on the construction of sequences that folded in water and membranes to adopt folded conformations. The first proteins were designed from first-principles using very simple physical models. As computers became more powerful, the use of the rotamer approximation allowed one to discover amino acid sequences that stabilize the desired fold. As the crystallographic database of protein structures expanded in subsequent years, it became possible to construct proteins by assembling short backbone fragments that frequently recur in Nature. The second set of milestones in de novo design involves the discovery of complex functions. Proteins have been designed to bind a variety of metals, porphyrins, and other cofactors. The design of proteins that catalyze hydrolysis and oxygen-dependent reactions has progressed significantly. However, de novo design of catalysts for energetically demanding reactions, or even proteins that bind with high affinity and specificity to highly functionalized complex polar molecules remains an importnant challenge that is now being achieved. Finally, the protein design contributed significantly to our understanding of membrane protein folding and transport of ions across membranes. The area of membrane protein design, or more generally of biomimetic polymers that function in mixed or non-aqueous environments, is now becoming increasingly possible.

Kemp Eliminases of the AlleyCat Family Possess High Substrate Promiscuity.

Minimalist enzymes designed to catalyze model reactions provide useful starting points for creating catalysts for practically important chemical transformations. We have shown that Kemp eliminases of the AlleyCat family facilitate conversion of leflunomide (an immunosupressor pro-drug) to its active form teriflunomide with outstanding rate enhancement (nearly four orders of magnitude) and catalytic proficiency (more than seven orders of magnitude) without any additional optimization. This remarkable activity is achieved by properly positioning the substrate in close proximity to the catalytic glutamate with very high pKa.

Catalytic Nanoassemblies Formed by Short Peptides Promote Highly Enantioselective Transfer Hydrogenation.

Self-assembly enables formation of incredibly diverse supramolecular structures with practically important functions from simple and inexpensive building blocks. Here, we show how a semirational, bottom-up approach to create emerging properties can be extended to a design of highly enantioselective catalytic nanoassemblies. The designed peptides comprising as few as two amino acid residues spontaneously self-assemble in the presence of metal ions to form supramolecular, vesicle-like nanoassemblies that promote transfer hydrogenation of ketones in an aqueous phase with excellent conversion rates and enantioselectivities (>90% ee).

Minimalist de novo Design of Protein Catalysts.

The field of protein design has grown enormously in the past few decades. In this review we discuss the minimalist approach to design of artificial enzymes, in which protein sequences are created with the minimum number of elements for folding and function. This method relies on identifying starting points in catalytically inert scaffolds for active site installation. The progress of the field from the original helical assemblies of the 1980s to the more complex structures of the present day is discussed, highlighting the variety of catalytic reactions which have been achieved using these methods. We outline the strengths and weaknesses of the minimalist approaches, describe representative design cases and put it in the general context of the de novo design of proteins.

Copper-Containing Catalytic Amyloids Promote Phosphoester Hydrolysis and Tandem Reactions.

Self-assembly of short de novo designed peptides gives rise to catalytic amyloids capable of facilitating multiple chemical transformations. We show that catalytic amyloids can efficiently hydrolyze paraoxon, a widely used, highly toxic organophosphate pesticide. Moreover, these robust and inexpensive metal-containing materials can be easily deposited on various surfaces producing catalytic flow devices. Finally, functional promiscuity of catalytic amyloids promotes tandem hydrolysis/oxidation reactions. High efficiency discovered in a very small library of peptides suggests an enormous potential for further improvement of catalytic properties both in terms of catalytic efficiency and substrate scope.

A Designed Enzyme Promotes Selective Post-translational Acylation.

A computationally designed, allosterically regulated catalyst (CaM M144H) produced by substituting a single residue in calmodulin, a non-enzymatic protein, is capable of efficient and site selective post-translational acylation of lysines in peptides with highly diverse sequences. Calmodulin's binding partners are involved in regulating a large number of cellular processes; this new chemical-biology tool will help to identify them and provide structural insight into their interactions with calmodulin.

Preparation and Screening of Catalytic Amyloid Assemblies.

Aggregation of proteins into amyloids has long been recognized as one of the major contributors to disease and aging. Amyloids are known to catalyze their own formation but they have been considered the rock-bottom thermodynamic minimum of the protein fold without much functionality. We have recently demonstrated that aggregation of short peptides in the presence of metal ions gives rise to efficient catalytic activity. Here we present a detailed protocol for the synthesis and purification of these peptides and the preparation of amyloid-like fibrils. Then we describe an easy-to-perform, high-throughput assay to measure their hydrolytic activity.