Quest for a turnover mechanism in peptide-based enzyme mimics

Determining the esterase activity of peptides and peptide assemblies

Catalytic peptides are gaining attention as alternatives to enzymes, especially in industrial applications. Recent advances in peptide design have improved their catalytic efficiency with approaches such as self-assembly and metal ion complexation. However, the fundamental principles governing peptide catalysis at the sequence level are still being explored. Ester hydrolysis, a well-studied reaction, serves as a widely employed method to evaluate the catalytic potential of peptides. The standard colorimetric reaction involving para-nitrophenyl acetate hydrolysis acts as a benchmark assay, providing a straightforward and efficient screening method for rapidly identifying potential catalysts. However, maintaining standardized conditions is crucial for reproducible results, given that factors such as pH, temperature, and substrate concentration can introduce unwanted variability. This necessity becomes particularly pronounced when working with peptides, which often exhibit slower reaction rates compared to enzymes, making even minor variations significantly influential on the final outcome. In this context, we present a refined protocol for assessing the catalytic activity of peptides and peptide assemblies, addressing critical considerations for reproducibility and accuracy.

Manually curated dataset of catalytic peptides for ester hydrolysis

Catalytic peptides are low cost biomolecules able to catalyse chemical reactions such as ester hydrolysis. This dataset provides a list of catalytic peptides currently reported in literature. Several parameters were evaluated, including sequence length, composition, net charge, isoelectric point, hydrophobicity, self-assembly propensity and mechanism of catalysis. Along with the analysis of physico-chemical properties, the SMILES representation for each sequence was generated to provide an easy-to-use means of training machine learning models. This offers a unique opportunity for the development and validation of proof-of-concept predictive models. Being a reliable manually curated dataset, it also enables the benchmark for comparison of new models or models trained on automatically gathered peptide-oriented datasets. Moreover, the dataset provides an insight in the currently developed catalytic mechanisms and can be used as the foundation for the development of next-generation peptide-based catalysts.

Esterase Sequence Composition Patterns for the Identification of Catalytic Triad Microenvironment Motifs

Ester hydrolysis is of wide biomedical interest, spanning from the green synthesis of pharmaceuticals to biomaterials' development. Existing peptide-based catalysts exhibit low catalytic efficiency compared to natural enzymes, due to the conformational heterogeneity of peptides. Moreover, there is lack of understanding of the correlation between the primary sequence and catalytic function. For this purpose, we statistically analyzed 22 EC 3.1 hydrolases with known catalytic triads, characterized by unique and well-defined mechanisms. The aim was to identify patterns at the sequence level that will better inform the creation of short peptides containing important information for catalysis, based on the catalytic triad, oxyanion holes and the triad residues microenvironments. Moreover, fragmentation schemes of the primary sequence of selected enzymes alongside the study of their amino acid frequencies, composition, and physicochemical properties are proposed. The results showed highly conserved catalytic sites with distinct positional patterns and chemical microenvironments that favor catalysis and revealed variations in catalytic site composition that could be useful for the design of minimalistic catalysts.

Enzyme Mimics: Advances and Applications

Enzyme mimics or artificial enzymes are a class of catalysts that have been actively pursued for decades and have heralded much interest as potentially viable alternatives to natural enzymes. Aside from having catalytic activities similar to their natural counterparts, enzyme mimics have the desired advantages of tunable structures and catalytic efficiencies, excellent tolerance to experimental conditions, lower cost, and purely synthetic routes to their preparation. Although still in the midst of development, impressive advances have already been made. Enzyme mimics have shown immense potential in the catalysis of a wide range of chemical and biological reactions, the development of chemical and biological sensing and anti-biofouling systems, and the production of pharmaceuticals and clean fuels. This Review concerns the development of various types of enzyme mimics, namely polymeric and dendrimeric, supramolecular, nanoparticulate and proteinic enzyme mimics, with an emphasis on their synthesis, catalytic properties and technical applications. It provides an introduction to enzyme mimics and a comprehensive summary of the advances and current standings of their applications, and seeks to inspire researchers to perfect the design and synthesis of enzyme mimics and to tailor their functionality for a much wider range of applications.