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.

GRaSP-web: a machine learning strategy to predict binding sites based on residue neighborhood graphs.

Proteins are essential macromolecules for the maintenance of living systems. Many of them perform their function by interacting with other molecules in regions called binding sites. The identification and characterization of these regions are of fundamental importance to determine protein function, being a fundamental step in processes such as drug design and discovery. However, identifying such binding regions is not trivial due to the drawbacks of experimental methods, which are costly and time-consuming. Here we propose GRaSP-web, a web server that uses GRaSP (Graph-based Residue neighborhood Strategy to Predict binding sites), a residue-centric method based on graphs that uses machine learning to predict putative ligand binding site residues. The method outperformed 6 state-of-the-art residue-centric methods (MCC of 0.61). Also, GRaSP-web is scalable as it takes 10-20 seconds to predict binding sites for a protein complex (the state-of-the-art residue-centric method takes 2-5h on the average). It proved to be consistent in predicting binding sites for bound/unbound structures (MCC 0.61 for both) and for a large dataset of multi-chain proteins (4500 entries, MCC 0.61). GRaSPWeb is freely available at https://grasp.ufv.br.

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.

The Enzyme Portal: an integrative tool for enzyme information and analysis.

Enzymes play essential roles in all life processes and are used extensively in the biomedical and biotechnological fields. However, enzyme-related information is spread across multiple resources making its retrieval time-consuming. In response to this challenge, the Enzyme Portal has been established to facilitate enzyme research, by providing a freely available hub where researchers can easily find and explore enzyme-related information. It integrates relevant enzyme data for a wide range of species from various resources such as UniProtKB, PDBe and ChEMBL. Here, we describe what type of enzyme-related data the Enzyme Portal provides, how the information is organized and, by show-casing two potential use cases, how to access and retrieve it.

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.

GRaSP: a graph-based residue neighborhood strategy to predict binding sites.

MOTIVATION: The discovery of protein-ligand-binding sites is a major step for elucidating protein function and for investigating new functional roles. Detecting protein-ligand-binding sites experimentally is time-consuming and expensive. Thus, a variety of in silico methods to detect and predict binding sites was proposed as they can be scalable, fast and present low cost. RESULTS: We proposed Graph-based Residue neighborhood Strategy to Predict binding sites (GRaSP), a novel residue centric and scalable method to predict ligand-binding site residues. It is based on a supervised learning strategy that models the residue environment as a graph at the atomic level. Results show that GRaSP made compatible or superior predictions when compared with methods described in the literature. GRaSP outperformed six other residue-centric methods, including the one considered as state-of-the-art. Also, our method achieved better results than the method from CAMEO independent assessment. GRaSP ranked second when compared with five state-of-the-art pocket-centric methods, which we consider a significant result, as it was not devised to predict pockets. Finally, our method proved scalable as it took 10-20 s on average to predict the binding site for a protein complex whereas the state-of-the-art residue-centric method takes 2-5 h on average. AVAILABILITY AND IMPLEMENTATION: The source code and datasets are available at https://github.com/charles-abreu/GRaSP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A global analysis of function and conservation of catalytic residues in enzymes.

The catalytic residues of an enzyme comprise the amino acids located in the active center responsible for accelerating the enzyme-catalyzed reaction. These residues lower the activation energy of reactions by performing several catalytic functions. Decades of enzymology research has established general themes regarding the roles of specific residues in these catalytic reactions, but it has been more difficult to explore these roles in a more systematic way. Here, we review the data on the catalytic residues of 648 enzymes, as annotated in the Mechanism and Catalytic Site Atlas (M-CSA), and compare our results with those in previous studies. We structured this analysis around three key properties of the catalytic residues: amino acid type, catalytic function, and sequence conservation in homologous proteins. As expected, we observed that catalysis is mostly accomplished by a small set of residues performing a limited number of catalytic functions. Catalytic residues are typically highly conserved, but to a smaller degree in homologues that perform different reactions or are nonenzymes (pseudoenzymes). Cross-analysis yielded further insights revealing which residues perform particular functions and how often. We obtained more detailed specificity rules for certain functions by identifying the chemical group upon which the residue acts. Finally, we show the mutation tolerance of the catalytic residues based on their roles. The characterization of the catalytic residues, their functions, and conservation, as presented here, is key to understanding the impact of mutations in evolution, disease, and enzyme design. The tools developed for this analysis are available at the M-CSA website and allow for user specific analysis of the same data.

Identifying pseudoenzymes using functional annotation: pitfalls of common practice.

Pseudoenzymes are proteins that are evolutionary related to enzymes but lack relevant catalytic activity. They are usually evolved from enzymatic ancestors that have lost their catalytic activities. The loss of catalytic function is one extreme amongst the other evolutionary changes that can occur to enzymes, like the changing of substrate specificity or the reaction catalysed. However, the loss of catalytic function events remain poorly characterised, except for some notable examples, like the pseudokinases. In this review, we aim to analyse current knowledge related to pseudoenzymes across a large number of enzymes families. This aims to be a review of the data available in biological databases, rather than a more traditional literature review. In particular, we use UniProtKB as the source for functional annotation and M-CSA (Mechanism and Catalytic Site Atlas) for information on the catalytic residues of enzymes. We show that explicit annotation of lack of activity is not exhaustive in UniProtKB and that a protocol using lack of catalytic annotation as an indication for lack of function can be an adequate alternative, after some corrections. After identifying pseudoenzymes related to enzymes in M-CSA, we were able to comment on their prevalence across enzyme families, and on the correlation between lack of catalytic function and the mutation of catalytic residues. These analyses challenge two common ideas in the emerging literature: that pseudoenzymes are ubiquitous across enzyme families and that mutations in the catalytic residues of enzyme homologues are always a good indication of lack of activity.

Exploring Chemical Biosynthetic Design Space with Transform-MinER.

Transform-MinER (Transforming Molecules in Enzyme Reactions) is a web application facilitating the exploration of chemical biosynthetic space, guiding the user toward promising start points for enzyme design projects or directed evolution experiments. Two types of search are possible: Molecule Search allows a user to submit a source substrate enabling Transform-MinER to search for enzyme reactions acting on similar substrates, whereas Path Search additionally allows a user to submit a target molecule enabling Transform-MinER to search for a path of enzyme reactions acting on similar substrates to link source and target. Transform-MinER searches for potential reaction centers in the source substrate and uses chemoinformatic fingerprints to identify those that are situated in molecular environments similar to native counterparts, prioritizing steps that move closer to the target using reactions most similar to native in its exploration of search space. The ligand-based methodology behind Transform-MinER is presented, and its performance is validated yielding 90% success rates: first, on a data set of native pathways from the KEGG database, and second, on a data set of de novo enzyme reactions.

Emerging concepts in pseudoenzyme classification, evolution, and signaling.

The 21st century is witnessing an explosive surge in our understanding of pseudoenzyme-driven regulatory mechanisms in biology. Pseudoenzymes are proteins that have sequence homology with enzyme families but that are proven or predicted to lack enzyme activity due to mutations in otherwise conserved catalytic amino acids. The best-studied pseudoenzymes are pseudokinases, although examples from other families are emerging at a rapid rate as experimental approaches catch up with an avalanche of freely available informatics data. Kingdom-wide analysis in prokaryotes, archaea and eukaryotes reveals that between 5 and 10% of proteins that make up enzyme families are pseudoenzymes, with notable expansions and contractions seemingly associated with specific signaling niches. Pseudoenzymes can allosterically activate canonical enzymes, act as scaffolds to control assembly of signaling complexes and their localization, serve as molecular switches, or regulate signaling networks through substrate or enzyme sequestration. Molecular analysis of pseudoenzymes is rapidly advancing knowledge of how they perform noncatalytic functions and is enabling the discovery of unexpected, and previously unappreciated, functions of their intensively studied enzyme counterparts. Notably, upon further examination, some pseudoenzymes have previously unknown enzymatic activities that could not have been predicted a priori. Pseudoenzymes can be targeted and manipulated by small molecules and therefore represent new therapeutic targets (or anti-targets, where intervention should be avoided) in various diseases. In this review, which brings together broad bioinformatics and cell signaling approaches in the field, we highlight a selection of findings relevant to a contemporary understanding of pseudoenzyme-based biology.

Transform-MinER: transforming molecules in enzyme reactions.

Motivation: One goal of synthetic biology is to make new enzymes to generate new products, but identifying the starting enzymes for further investigation is often elusive and relies on expert knowledge, intensive literature searching and trial and error. Results: We present Transform Molecules in Enzyme Reactions, an online computational tool that transforms query substrate molecules into products using enzyme reactions. The most similar native enzyme reactions for each transformation are found, highlighting those that may be of most interest for enzyme design and directed evolution approaches. Availability and implementation: https://www.ebi.ac.uk/thornton-srv/transform-miner.

Ranking Enzyme Structures in the PDB by Bound Ligand Similarity to Biological Substrates.

There are numerous applications that use the structures of protein-ligand complexes from the PDB, such as 3D pharmacophore identification, virtual screening, and fragment-based drug design. The structures underlying these applications are potentially much more informative if they contain biologically relevant bound ligands, with high similarity to the cognate ligands. We present a study of ligand-enzyme complexes that compares the similarity of bound and cognate ligands, enabling the best matches to be identified. We calculate the molecular similarity scores using a method called PARITY (proportion of atoms residing in identical topology), which can conveniently be combined to give a similarity score for all cognate reactants or products in the reaction. Thus, we generate a rank-ordered list of related PDB structures, according to the biological similarity of the ligands bound in the structures.

Mechanism and Catalytic Site Atlas (M-CSA): a database of enzyme reaction mechanisms and active sites.

M-CSA (Mechanism and Catalytic Site Atlas) is a database of enzyme active sites and reaction mechanisms that can be accessed at www.ebi.ac.uk/thornton-srv/m-csa. Our objectives with M-CSA are to provide an open data resource for the community to browse known enzyme reaction mechanisms and catalytic sites, and to use the dataset to understand enzyme function and evolution. M-CSA results from the merging of two existing databases, MACiE (Mechanism, Annotation and Classification in Enzymes), a database of enzyme mechanisms, and CSA (Catalytic Site Atlas), a database of catalytic sites of enzymes. We are releasing M-CSA as a new website and underlying database architecture. At the moment, M-CSA contains 961 entries, 423 of these with detailed mechanism information, and 538 with information on the catalytic site residues only. In total, these cover 81% (195/241) of third level EC numbers with a PDB structure, and 30% (840/2793) of fourth level EC numbers with a PDB structure, out of 6028 in total. By searching for close homologues, we are able to extend M-CSA coverage of PDB and UniProtKB to 51 993 structures and to over five million sequences, respectively, of which about 40% and 30% have a conserved active site.

cuRRBS: simple and robust evaluation of enzyme combinations for reduced representation approaches.

DNA methylation is an important epigenetic modification in many species that is critical for development, and implicated in ageing and many complex diseases, such as cancer. Many cost-effective genome-wide analyses of DNA modifications rely on restriction enzymes capable of digesting genomic DNA at defined sequence motifs. There are hundreds of restriction enzyme families but few are used to date, because no tool is available for the systematic evaluation of restriction enzyme combinations that can enrich for certain sites of interest in a genome. Herein, we present customised Reduced Representation Bisulfite Sequencing (cuRRBS), a novel and easy-to-use computational method that solves this problem. By computing the optimal enzymatic digestions and size selection steps required, cuRRBS generalises the traditional MspI-based Reduced Representation Bisulfite Sequencing (RRBS) protocol to all restriction enzyme combinations. In addition, cuRRBS estimates the fold-reduction in sequencing costs and provides a robustness value for the personalised RRBS protocol, allowing users to tailor the protocol to their experimental needs. Moreover, we show in silico that cuRRBS-defined restriction enzymes consistently out-perform MspI digestion in many biological systems, considering both CpG and CHG contexts. Finally, we have validated the accuracy of cuRRBS predictions for single and double enzyme digestions using two independent experimental datasets.

Unique Triphenylphosphonium Derivatives for Enhanced Mitochondrial Uptake and Photodynamic Therapy.

In this study, unique methyl-functionalized derivatives (T*PP+) of the drug carrier triphenylphosphonium (TPP+) that exhibit significant enhancement of the accumulation of both the cation and its conjugated cargo in cell mitochondria are designed. We show that the presence of methyl group(s) at key positions within the phenyl ring results in an increase in the hydrophobicity and solvent accessible surface area of T*PP+. In particular, when the para position of the phenyl ring in T*PP+ is functionalized with a methyl group, the cation is most exposed to the surrounding environment, leading to a large decrease in water entropy and an increase in the level of van der Waals interaction with and partition into a nonpolar solvent. Therefore, stronger binding between the hydrophobic T*PP+ and mitochondrial membrane occurs. This is exemplified in a (hexachloro-fluorescein)-TPP+ conjugate system, where an ∼12 times increase in the rate of mitochondrial uptake and a 2 times increase in photodynamic therapy (PDT) efficacy against HeLa and FU97 cancer cells are achieved when TPP+ is replaced with T*PP+. Importantly, nearly all the FU97 cells treated with the (hexachloro-fluorescein)-T*PP+ conjugate are killed as compared to only half the population of cells in the case of the (hexachloro-fluorescein)-TPP+ conjugate at a similar PDT light dosage. This study thus forms a platform for the healthcare community to explore alternative TPP+ derivatives that can act as optimal drug transporters for enhanced mitochondrially targeted therapies.

Binding free energy calculations on E-selectin complexes with sLex oligosaccharide analogs.

Molecular dynamics simulations and binding free energy calculations were employed to examine the interaction between E-selectin and six structurally related oligosaccharides including the physiological ligand sialyl Lewis x. Molecular dynamics simulations revealed that sialyl Lewis x and its mimics share a common binding region and similar interactions with E-selectin involving the formation of hydrogen bonds with Glu80, Asn82, Asn83, Arg97, Asn105, Asp106, and Glu107 residues and electrostatic contacts with Ca2+ and the positively charged Lys111 and Lys 113 residues. Regarding binding free energy calculations, the performance of the rigorous but computationally expensive pathway methods TI, BAR, and MBAR was compared to the less rigorous but faster end-point methods MM/PBSA and MM/GBSA aimed at identifying a suitable approach to deal with the very subtle binding free energy differences within the ligands under study. All methods succeeded in predicting increased binding affinities for sialyl Lewis x analogs compared to the native ligand with absolute errors <1 kcal/mol. The best correlation with experimental data was obtained by TI (r2  = 0.84), followed by MBAR (r2  = 0.80), BAR (r2  = 0.73), MM/PBSA (r2  = 0.73) and MM/GBSA (r2  = 0.47). These results provide valuable information to increase understanding about E-selectin-oligosaccharide interactions and conduct further research aimed at designing novel ligands targeting this protein.

Improving the Biodesulfurization of Crude Oil and Derivatives: A QM/MM Investigation of the Catalytic Mechanism of NADH-FMN Oxidoreductase (DszD).

The development of biocatalytic desulfurization strategies of petroleum and its derivatives could result in more economic alternatives than the widely used chemical desulfurization. The organism Rhodococcus erythropolis IGTS8 has been shown to metabolize organic sulfur compounds through a mechanism known as 4S pathway, which involves four enzymes (DszA, DszB, DszC, and DszD) and has been explored in biodesulfurization. Here we have applied QM/MM methods to study the catalytic mechanism of the enzyme DszD, a NADH-FMN oxidoreductase that occupies a central place on the 4S pathway by catalyzing the formation of the FMNH2 that is used by the two monooxynases in the cycle: DszA and DszC. In addition, to clarify the catalytic mechanism of this enzyme, this study analyzed in detail the role played by the active site Thr residue and of Asn and Ala enzyme mutants. The results help to explain previous experimental evidence and suggest new strategies for improving biodesulfurization through an increase in the activity of DszD.

Synthesis and Hydrolytic Studies on the Air-Stable [(4-CN-PhO)(E)P(µ-N(t)Bu)]2 (E = O, S, and Se) Cyclodiphosphazanes.

Reaction of 4-CN-PhOH with [ClP(µ-N(t)Bu)]2 (1) (2:1 ratio) in the presence of Et3N produced the functionalized cyclodiphosph(III/III)azane [(4-CN-PhO)P(µ-N(t)Bu)]2 (2). Oxidation of 2 produced cyclodiphosph(V/V)azanes [(4-CN-PhO)(E)P(µ-N(t)Bu)]2 [E = O (3), S (4), and Se (5)]. This is the first example of a series of cyclodiphosph(V/V)azane derivatives obtained from a single cyclophosph(III/III)azane precursor where all the accessible chalcogen oxidized products are air-stable over prolonged periods of time.