Enzyme function and evolution through the lens of bioinformatics.

Enzymes have been shaped by evolution over billions of years to catalyse the chemical reactions that support life on earth. Dispersed in the literature, or organised in online databases, knowledge about enzymes can be structured in distinct dimensions, either related to their quality as biological macromolecules, such as their sequence and structure, or related to their chemical functions, such as the catalytic site, kinetics, mechanism, and overall reaction. The evolution of enzymes can only be understood when each of these dimensions is considered. In addition, many of the properties of enzymes only make sense in the light of evolution. We start this review by outlining the main paradigms of enzyme evolution, including gene duplication and divergence, convergent evolution, and evolution by recombination of domains. In the second part, we overview the current collective knowledge about enzymes, as organised by different types of data and collected in several databases. We also highlight some increasingly powerful computational tools that can be used to close gaps in understanding, in particular for types of data that require laborious experimental protocols. We believe that recent advances in protein structure prediction will be a powerful catalyst for the prediction of binding, mechanism, and ultimately, chemical reactions. A comprehensive mapping of enzyme function and evolution may be attainable in the near future.

EzMechanism: an automated tool to propose catalytic mechanisms of enzyme reactions.

Over the years, hundreds of enzyme reaction mechanisms have been studied using experimental and simulation methods. This rich literature on biological catalysis is now ripe for use as the foundation of new knowledge-based approaches to investigate enzyme mechanisms. Here, we present a tool able to automatically infer mechanistic paths for a given three-dimensional active site and enzyme reaction, based on a set of catalytic rules compiled from the Mechanism and Catalytic Site Atlas, a database of enzyme mechanisms. EzMechanism (pronounced as 'Easy' Mechanism) is available to everyone through a web user interface. When studying a mechanism, EzMechanism facilitates and improves the generation of hypotheses, by making sure that relevant information is considered, as derived from the literature on both related and unrelated enzymes. We validated EzMechanism on a set of 62 enzymes and have identified paths for further improvement, including the need for additional and more generic catalytic rules.

The 3D Modules of Enzyme Catalysis: Deconstructing Active Sites into Distinct Functional Entities.

Enzyme catalysis is governed by a limited toolkit of residues and organic or inorganic co-factors. Therefore, it is expected that recurring residue arrangements will be found across the enzyme space, which perform a defined catalytic function, are structurally similar and occur in unrelated enzymes. Leveraging the integrated information in the Mechanism and Catalytic Site Atlas (M-CSA) (enzyme structure, sequence, catalytic residue annotations, catalysed reaction, detailed mechanism description), 3D templates were derived to represent compact groups of catalytic residues. A fuzzy template-template search, allowed us to identify those recurring motifs, which are conserved or convergent, that we define as the "modules of enzyme catalysis". We show that a large fraction of these modules facilitate binding of metal ions, co-factors and substrates, and are frequently the result of convergent evolution. A smaller number of convergent modules perform a well-defined catalytic role, such as the variants of the catalytic triad (i.e. Ser-His-Asp/Cys-His-Asp) and the saccharide-cleaving Asp/Glu triad. It is also shown that enzymes whose functions have diverged during evolution preserve regions of their active site unaltered, as shown by modules performing similar or identical steps of the catalytic mechanism. We have compiled a comprehensive library of catalytic modules, that characterise a broad spectrum of enzymes. These modules can be used as templates in enzyme design and for better understanding catalysis in 3D.

Capturing the geometry, function, and evolution of enzymes with 3D templates.

Structural templates are 3D signatures representing protein functional sites, such as ligand binding cavities, metal coordination motifs, or catalytic sites. Here we explore methods to generate template libraries and algorithms to query structures for conserved 3D motifs. Applications of templates are discussed, as well as some exemplar cases for examining evolutionary links in enzymes. We also introduce the concept of using more than one template per structure to represent flexible sites, as an approach to better understand catalysis through snapshots captured in enzyme structures. Functional annotation from structure is an important topic that has recently resurfaced due to the new more accurate methods of protein structure prediction. Therefore, we anticipate that template-based functional site detection will be a powerful tool in the task of characterizing a vast number of new protein models.

Conformational Variation in Enzyme Catalysis: A Structural Study on Catalytic Residues.

Conformational variation in catalytic residues can be captured as alternative snapshots in enzyme crystal structures. Addressing the question of whether active site flexibility is an intrinsic and essential property of enzymes for catalysis, we present a comprehensive study on the 3D variation of active sites of 925 enzyme families, using explicit catalytic residue annotations from the Mechanism and Catalytic Site Atlas and structural data from the Protein Data Bank. Through weighted pairwise superposition of the functional atoms of active sites, we captured structural variability at single-residue level and examined the geometrical changes as ligands bind or as mutations occur. We demonstrate that catalytic centres of enzymes can be inherently rigid or flexible to various degrees according to the function they perform, and structural variability most often involves a subset of the catalytic residues, usually those not directly involved in the formation or cleavage of bonds. Moreover, data suggest that 2/3 of active sites are flexible, and in half of those, flexibility is only observed in the side chain. The goal of this work is to characterise our current knowledge of the extent of flexibility at the heart of catalysis and ultimately place our findings in the context of the evolution of catalysis as enzymes evolve new functions and bind different substrates.

Using mechanism similarity to understand enzyme evolution.

Enzyme reactions take place in the active site through a series of catalytic steps, which are collectively termed the enzyme mechanism. The catalytic step is thereby the individual unit to consider for the purposes of building new enzyme mechanisms - i.e. through the mix and match of individual catalytic steps, new enzyme mechanisms and reactions can be conceived. In the case of natural evolution, it has been shown that new enzyme functions have emerged through the tweaking of existing mechanisms by the addition, removal, or modification of some catalytic steps, while maintaining other steps of the mechanism intact. Recently, we have extracted and codified the information on the catalytic steps of hundreds of enzymes in a machine-readable way, with the aim of automating this kind of evolutionary analysis. In this paper, we illustrate how these data, which we called the "rules of enzyme catalysis", can be used to identify similar catalytic steps across enzymes that differ in their overall function and/or structural folds. A discussion on a set of three enzymes that share part of their mechanism is used as an exemplar to illustrate how this approach can reveal divergent and convergent evolution of enzymes at the mechanistic level. Supplementary Information: The online version contains supplementary material available at 10.1007/s12551-022-01022-9.

De Novo Synthesis of Elastin-like Polypeptides (ELPs): An Applied Overview on the Current Experimental Techniques.

Elastin-like polypeptides (ELPs) are protein-based biopolymers genetically produced from polypeptides composed of a repeating pentapeptide sequence V-P-G-X-G. The inherent properties of recombinant ELPs, such as smart nature, controlled sequence complexity, physicochemical properties, and biocompatibility, make these polymers suitable for use in nanobiotechnological applications, as biofunctionalized scaffolds for tissue-engineering purposes and drug delivery. In this work, we report the design and synthesis of two elastomeric self-assembling polypeptides (ELPs) that mimic the endogenous human tropoelastin. Using molecular biology techniques, two artificial genes that encode two ELP concatemers of approximate molecular mass 60 kDa, one of them carrying biotin-binding peptide motifs, were constructed. These motifs could facilitate biofunctionalization of the ELPs through tethering biotinylated factors, such as growth factors. The ELPs were heterologously overexpressed in E. coli and subsequently purified in two steps: a nonchromatographic technique by organic solvent extraction, followed by nickel-nitrilotriacetic acid (Ni-NTA) affinity chromatography. The characterization of the biochemical properties and biocompatibility of ELPs was also performed in this study. The ELP carrying the biotin-binding motifs was tested for its capability to bind biotin, and indeed, it was observed that it can bind biotinylated proteins specifically. Additionally, results concerning the cytotoxicity of the ELPs exhibited excellent compatibility of the ELPs with mammalian cells in vitro. We anticipate that these ELPs can be used as components of a scaffold that mimics the extracellular matrix (ECM) for the regeneration of endogenously highly elastic tissues.

On the presence of short-range periodicities in protein structures that are not related to established secondary structure elements.

Standard secondary structure elements such as α-helices or ß-sheets, are characterized by repeating backbone torsion angles (φ,ψ) at the single residue level. Two-residue motifs of the type (φ,ψ)2 are also observed in nonlinear conformations, mainly turns. Taking these observations a step further, it can be argued that there is no a priori reason why the presence of higher order periodicities can not be envisioned in protein structures, such as, for example, periodic transitions between successive residues of the type (…-α-ß-α-ß-α-…), or (…-ß-αL -ß-αL -ß-…), or (…-α-ß-αL -α-ß-αL -…), and so forth, where the symbols (α,ß,αL ) refer to the established Ramachandran-based residue conformations. From all such possible higher order periodicities, here we examine the deposited (with the PDB) protein structures for the presence of short-range periodical conformations comprising five consecutive residues alternating between two (and only two) distinct Ramachandran regions, for example, conformations of the type (α-ß-α-ß-α) or (ß-αL -ß-αL -ß), and so forth. Using a probabilistic approach, we have located several thousands of such peptapeptides, and these were clustered and analyzed in terms of their structural characteristics, their sequences, and their putative functional correlations using a gene ontology-based approach. We show that such nonstandard short-range periodicities are present in a large and functionally diverse sample of proteins, and can be grouped into two structurally conserved major types. Examination of the structural context in which these peptapeptides are observed gave no conclusive evidence for the presence of a persistent structural or functional role of these higher order periodic conformations.