MACiE (Mechanism, Annotation and Classification in Enzymes) is a database of enzyme reaction mechanisms. Each entry in MACiE consists of an overall reaction describing the chemical compounds involved, as well as the species name in which the reaction occurs. The individual reaction stages for each overall reaction are listed with mechanisms, alternative mechanisms, and amino acids involved.

The EzCatDB database analyzes and classifies enzyme catalytic mechanisms on the basis of information from literature and data that are derived from entries in the Protein Data Bank (PDB). Each data set contains corresponding enzyme information, such as E.C. number, PDB entries with their annotated ligand information and active site residues, information on catalytic mechanisms, and links to other databases, such as Swiss-prot, CATH, KEGG, PDBsum, and PubMed.

MACiE, which stands for Mechanism, Annotation and Classification in Enzymes, is a collaborative project on enzyme reaction mechanisms. MACiE currently contains 223 fully annotated enzyme reaction mechanisms, which comprise 218 EC numbers (161 EC sub-subclasses) and 310 distinct CATH codes. It is a joint effortbetween the Mitchell Group at the Unilever Centre for Molecular Informatics part of the University of Cambridge and the Thornton Group at the European Bioinformatics Institute.

Raw data for experiments depicted on Figure 2 https://www.researchsquare.com/article/rs-2305070/v2

Raw data for experiments depicted on Figure 3 https://www.researchsquare.com/article/rs-2305070/v2

The mechanisms that underly the adaptation enzyme activities and stabilities to temperature are fundamental to our understanding of molecular evolution and how enzymes work. Herein, we investigate the molecular and evolutionary mechanisms of enzyme temperature adaption, combining deep mechanistic studies with comprehensive sequence analyses of thousands of enzymes. We show that temperature adaptation in ketosteroid isomerase (KSI) arises primarily from one residue change with limited, local epistasis and we establish the underlying physical mechanisms. This residue change occurs in diverse KSI backgrounds, suggesting parallel adaptation to temperature. We identify residues associated with organismal growth temperature in 1005 diverse bacterial enzyme families, suggesting widespread parallel adaptation. We assess the properties of these residues, molecular interactions and interaction networks that appear to underly temperature adaptation.

With the increasing popularity of artificial intelligence methods and structural bioinformatics tools, such as AlphaFold, cultivating students' ability to conduct quantitative analysis using big data on protein structures has become a new challenge in biochemistry education. This paper constructs a teaching case based on a serine hydrolase, integrating the principles of statistical mechanics, the Dunbrack backbone-dependent rotamer library, the Boltzmann probability-energy relationship, and transition state theory. Students are guided through the entire process, from structural dataset acquisition and conformational probability distribution analysis to catalytic rate enhancement prediction, all within a Jupyter Notebook environment. Students analyze the χ₁ dihedral angle distribution of the catalytic serine (Ser195) in different binding states (apo, substrate analog GSA, and transition state analog TSA), calculate pseudo-energies corresponding to conformational preferences, and derive catalytic acceleration from ΔE₀. This case not only strengthens students' database searching, statistical analysis, and scripting skills, but also deepens their understanding of the enzyme catalytic mechanism of "ground state destabilization," laying a methodological foundation for future research in protein design and computational enzyme engineering.

This study explores ligand-driven conformational changes in adenylate kinase (AK), which is known for its open-to-close conformational transitions upon ligand binding and release. By utilizing string free energy simulations, we determine the free energy profiles for both enzyme opening and ligand release and compare them with profiles from the apoenzyme. Results reveal a three-step ligand release process, which initiates with the opening of the adenosine triphosphate-binding subdomain (ATP lid), followed by ligand release and concomitant opening of the adenosine monophosphate-binding subdomain (AMP lid). The ligands then transition to nonspecific positions before complete dissociation. In these processes, the first step is energetically driven by ATP lid opening, whereas the second step is driven by ATP release. In contrast, the AMP lid opening and its ligand release make minor contributions to the total free energy for enzyme opening. Regarding the ligand binding mechanism, our results suggest that AMP lid closure occurs via an induced-fit mechanism triggered by AMP binding, whereas ATP lid closure follows conformational selection. This difference in the closure mechanisms provides an explanation with implications for the debate on ligand-driven conformational changes of AK. Additionally, we determine an X-ray structure of an AK variant that exhibits significant rearrangements in the stacking of catalytic arginines, explaining its reduced catalytic activity. In the context of apoenzyme opening, the sequence of events is different. Here, the AMP lid opens first while the ATP lid remains closed, and the free energy associated with ATP lid opening varies with orientation, aligning with the reported AK opening and closing rate heterogeneity. Finally, this study, in conjunction with our previous research, provides a comprehensive view of the intricate interplay between various structural elements, ligands, and catalytic residues that collectively contribute to the robust catalytic power of the enzyme.

Data and analysis supporting the publication titled 'Enzymatic Δ1-dehydrogenation of 3-ketosteroids – Reconciliation of Kinetic Isotope Effects with the Reaction Mechanism' (2021) created by Michał Glanowski, Patrycja Wójcik, Magdalena Procner, Tomasz Borowski, Dawid Lupa, Przemysław Mielczarek, Maria Oszajca, Katarzyna Świderek, Vicent Moliner, Andrzej J. Bojarski, Maciej Szaleniec, ACS Catalysis 2021, 11, 8211−8225. Online access: https://doi.org/10.1021/acscatal.1c01479

Δ1-Dehydrogenation of 3-ketosteroids catalyzed by FAD-dependent 3-ketosteroid dehydrogenases (Δ1-KSTD) is a crucial step in steroid degradation and synthesis of several steroid drugs. The catalytic mechanism assumes the formation of a double bond in two steps, proton abstraction by tyrosyl ion and a rate-limiting hydride transfer to FAD. This hypothesis was never verified by quantum-mechanical studies despite contradictory results from kinetic isotope effect (KIE) reported in ’60 by Jerussi and Ringold (Biochemistry 1965, 4 (10)). In this paper, we present results that reconcile the mechanistic hypothesis with experimental evidence. Quantum mechanics/molecular mechanics molecular dynamics (QM/MM MD) simulations show that the proposed mechanism is indeed the most probable, but barriers associated with substrate activation (13.4-16.3 kcal/mol) and hydride transfer (15.5-18.0 kcal/mol) are very close (1.7-2.1 kcal/mol) which explains normal KIE values for steroids labeled either at C1 or C2 atoms. We confirm that tyrosyl ion acting as the catalytic base is indeed necessary for efficient activation of the steroid. We explain the lower value of the observed KIE (1.5-3.5) by the nature of the free energy surface, the presence of diffusion limitation and to a smaller extent conformational changes of the enzyme upon substrate binding. Finally, we confirm the Ping-Pong bi bi kinetics of the whole Δ1-dehydrogenation and demonstrate that substrate binding, steroid dehydrogenation and enzyme reoxidation proceed at comparable rates.

This repository contains data acquired in this study i.e., raw data from stopped-flow spectrophotometer used to obtain kinetic traces for steady-state and pre-steady-state kinetics, including measurements of the kinetic isotope effect. The data were fitted with kinetic models yielding kinetic constants and confirming the Ping-Pong bi bi mechanism. The pre-steady-state kinetics conducted at different micro and macroviscosites were used to measure Kinetic Solvent Viscosity Effects (KSVE). Furthermore, a pre-steady-state experiment with 17-methyltestosterone was subjected to a global-fitting procedure in Octave which resulted in establishing microkinetic constants of substrate binding and release, constant of substrate oxidation/FAD reduction as well as of the reverse process.

The authors acknowledge financial support from the National Science Centre Poland under the OPUS grant number UMO-2016/21/B/ST4/03798.

HMG-CoA reductase (HMGR) is the target of statins, cholesterol-lowering drugs prescribed to millions of patients worldwide. More recent research indicates that HMGR could be a useful target in the development of antimicrobial agents. Over the last seven decades, researchers have proposed a series of increasingly complex reaction mechanisms for this biomedically important enzyme.The maturation of the mechanistic proposals for HMGR have paralleled advances in a diverse set of research areas, such as molecular biology and computational chemistry. Thus, the development of the HMGR mechanism provides a useful case study for following the advances in state-of-the-art methods in enzyme mechanism research. Similarly, the questions raised by these mechanism proposals reflect the limitations of the methods used to develop them.The mechanism of HMGR, a four-electron oxidoreductase, is unique and far more complex than originally thought. The reaction contains multiple chemical steps, coupled to large-scale domain motions of the homodimeric enzyme. The first proposals for the HMGR mechanism were based on kinetic and labeling experiments, drawing analogies to the mechanism of known dehydrogenases. Advances in molecular biology and bioinformatics enabled researchers to use site-directed mutagenesis experiments and protein sequencing to identify catalytically important glutamate, aspartate, and histidine residues. These studies, in turn, have generated new and more complicated mechanistic proposals.With the development of protein crystallography, researchers solved HMGR crystal structures to reveal an unexpected lysine residue at the center of the active site. The many crystal structures of HMGR led to increasingly complex mechanistic proposals, but the inherent limitations of the protein crystallography left a number of questions unresolved. For example, the protonation state of the glutamate residue within the active site cannot be clearly determined from the crystal structure. The differing protonation state of this residue leads to different proposed mechanisms for the enzyme.As computational analysis of large biomolecules has become more feasible, the application of methods such as hybrid quantum mechanics/molecular mechanics (QM/MM) calculations to the HMGR mechanism have led to the most detailed mechanistic proposal yet. As these methodologies continue to improve, they prove to be very powerful for the study of enzyme mechanisms in conjunction with protein crystallography. Nevertheless, even the most current mechanistic proposal for HMGR remains incomplete due to limitations of the current computational methodologies. Thus, HMGR serves as a model for how the combination of increasingly sophisticated experimental and computational methods can elucidate very complex enzyme mechanisms.

Protein-Protein, Genetic, and Chemical Interactions for Liu H (2013):Structures of enzyme-intermediate complexes of yeast Nit2: insights into its catalytic mechanism and different substrate specificity compared with mammalian Nit2. curated by BioGRID (https://thebiogrid.org); ABSTRACT: The Nit (nitrilase-like) protein subfamily constitutes branch 10 of the nitrilase superfamily. Nit proteins are widely distributed in nature. Mammals possess two members of the Nit subfamily, namely Nit1 and Nit2. Based on sequence similarity, yeast Nit2 (yNit2) is a homologue of mouse Nit1, a tumour-suppressor protein whose substrate specificity is not yet known. Previous studies have shown that mammalian Nit2 (also a putative tumour suppressor) is identical to ω-amidase, an enzyme that catalyzes the hydrolysis of α-ketoglutaramate (α-KGM) and α-ketosuccinamate (α-KSM) to α-ketoglutarate (α-KG) and oxaloacetate (OA), respectively. In the present study, crystal structures of wild-type (WT) yNit2 and of WT yNit2 in complex with α-KG and with OA were determined. In addition, the crystal structure of the C169S mutant of yNit2 (yNit2-C169S) in complex with an endogenous molecule of unknown structure was also solved. Analysis of the structures revealed that α-KG and OA are covalently bound to Cys169 by the formation of a thioester bond between the sulfhydryl group of the cysteine residue and the γ-carboxyl group of α-KG or the β-carboxyl group of OA, reflecting the presumed reaction intermediates. However, an enzymatic assay suggests that α-KGM is a relatively poor substrate of yNit2. Finally, a ligand was found in the active site of yNit2-C169S that may be a natural substrate of yNit2 or an endogenous regulator of enzyme activity. These crystallographic analyses provide information on the mode of substrate/ligand binding at the active site of yNit2 and insights into the catalytic mechanism. These findings suggest that yNit2 may have broad biological roles in yeast, especially in regard to nitrogen homeostasis, and provide a framework for the elucidation of the substrate specificity and biological role of mammalian Nit1.

Bacteria that cause most of the hospital-acquired infections make use of class C β-lactamase (CBL) among other enzymes to resist a wide spectrum of modern antibiotics and pose a major public health concern. Other than the general features, details of the defensive mechanism by CBL, leading to the hydrolysis of drug molecules, remain a matter of debate, in particular the identification of the general base and role of the active site residues and substrate. In an attempt to unravel the detailed molecular mechanism, we carried out extensive hybrid quantum mechanical/molecular mechanical Car–Parrinello molecular dynamics simulation of the reaction with the aid of the metadynamics technique. On this basis, we report here the mechanism of the formation of the acyl–enzyme complex from the Henry–Michaelis complex formed by β-lactam antibiotics and CBL. We considered two β-lactam antibiotics, namely, cephalothin and aztreonam, belonging to two different subfamilies. A general mechanism for the formation of a β-lactam antibiotic–CBL acyl–enzyme complex is elicited, and the individual roles of the active site residues and substrate are probed. The general base in the acylation step has been identified as Lys67, while Tyr150 aids the protonation of the β-lactam nitrogen through either the substrate carboxylate group or a water molecule.

Protein-Protein, Genetic, and Chemical Interactions for Moyle-Heyrman G (2012):Two-step mechanism for modifier of transcription 1 (Mot1) enzyme-catalyzed displacement of TATA-binding protein (TBP) from DNA. curated by BioGRID (https://thebiogrid.org); ABSTRACT: The TATA box binding protein (TBP) is a central component of the transcription preinitiation complex, and its occupancy at a promoter is correlated with transcription levels. The TBP-promoter DNA complex contains sharply bent DNA and its interaction lifetime is limited by the ATP-dependent TBP displacement activity of the Snf2/Swi2 ATPase Mot1. Several mechanisms for Mot1 action have been proposed, but how it catalyzes TBP removal from DNA is unknown. To better understand the Mot1 mechanism, native gel electrophoresis and FRET were used to determine how Mot1 affects the trajectory of DNA in the TBP-DNA complex. Strikingly, in the absence of ATP, Mot1 acts to unbend DNA, whereas TBP remains closely associated with the DNA in a stable Mot1-TBP-DNA ternary complex. Interestingly, and in contrast to full-length Mot1, the isolated Mot1 ATPase domain binds DNA, and its affinity for DNA is nucleotide-dependent, suggesting parallels between the Mot1 mechanism and DNA translocation-based mechanisms of chromatin remodeling enzymes. Based on these findings, a model is presented for Mot1 that links a DNA conformational change with ATP-induced DNA translocation.

This dataset contains atomic coordinates of the molecular dynamics simulations described in "Substrate-Assisted Mechanism for the Degradation of N-glycans by a Gut Bacterial Mannoside Phosphorylase" by M. Alfonso-Prieto, I. Cuxart, G. Potocki-Véronèse, I. André and C. Rovira, published in ACS Catalysis (https://doi.org/10.1021/acscatal.3c00451). Further details on the setup of the simulations can be found in the Supplementary Information of the article.

If you use this dataset, please cite this zenodo upload (https://doi.org/10.5281/zenodo.7704778), as well as the the original journal article (https://doi.org/10.1021/acscatal.3c00451).

This dataset is organized in the following folders:

Snapshots_Figures_Main_Text.zip, that contains a README.txt file and:

- Figure_3 contains representative structures (atomic coordinates) of the hexameric form of UhgbMP in complex with 3 different disaccharide molecules, Man-b-(1,4)-GlcNAc, Man-b-(1,4)-Glc and Man-b-(1,4)-Man.

- Figure_4 contains representative structures (atomic coordinates) of the hexameric form of UhgbMP at the three minima observed along the reaction coordinate corresponding to phosphorolysis of the disaccharide Man-b-(1,4)-GlcNAc: Michaelis complex (MC), transition state (TS) and product (P) complex.

Files in this dataset are in PDB format. For all structures, the solvation box (water and ions) has been stripped to reduce file size. See README.txt inside Snapshots_Figures_Main_Text.zip for more information.

Protein-Protein, Genetic, and Chemical Interactions for He S (2011):Microsomal prostaglandin E synthase-1 exhibits one-third-of-the-sites reactivity. curated by BioGRID (https://thebiogrid.org); ABSTRACT: mPGES-1 (microsomal prostaglandin E synthase-1) is a newly recognized target for the treatment of inflammatory diseases. As the terminal enzyme of the prostaglandin production pathway, mPGES-1 inhibition may have a low risk of side effects. Inhibitors of mPGES-1 have attracted considerable attention as next-generation anti-inflammatory drugs. However, as mPGES-1 is a membrane protein, its enzymatic mechanism remains to be disclosed fully. We used MD (molecular dynamics) simulations, mutation analysis, hybrid experiments and co-IP (co-immunoprecipitation) to investigate the conformation transitions of mPGES-1 during catalysis. mPGES-1 forms a homotrimer with three substrate-binding sites (pockets). In the MD simulation, only one substrate molecule could bind to one of the pockets and form the active complex, suggesting that the mPGES-1 trimer has only one pocket active at any given time. This one-third-of-the-sites reactivity enzyme mechanism was verified further by hybridization experiments and MD simulations. The results of the present study revealed for the first time a novel one-third-of-the-sites reactivity enzyme mechanism for mPGES-1, and the unique substrate-binding pocket in our model constituted an active conformation that was suitable for further enzymatic mechanism study and structural-based drug design against mPGES-1.

FunTree provides a range of data resources to detect the evolution of enzyme function within distant structurally related clusters within domain super families as determined by CATH. To access the resource enter a specific CATH superfamily code or search for a structure / sequence / function (either via a EC code or KEGG ligand / reaction ID, PDB ID or UniProtKB ID). Or browse the resource via superfamily / function / structure / metabolites & reactions via the menu on the left panel. FunTree is a new resource that brings together sequence, structure, phylogenetic, chemical and mechanistic information for structurally defined enzyme superfamilies. Gathering together this range of data into a single resource allows the investigation of how novel enzyme functions have evolved within a structurally defined superfamily as well as providing a means to analyse trends across many superfamilies. This is done not only within the context of an enzyme''''s sequence and structure but also the relationships of their reactions. Developed in tandem with the CATH database, it currently comprises 276 superfamilies covering 1800 (70%) of sequence assigned enzyme reactions. Central to the resource are phylogenetic trees generated from structurally informed multiple sequence alignments using both domain structural alignments supplemented with domain sequences and whole sequence alignments based on commonality of multi-domain architectures. These trees are decorated with functional annotations such as metabolite similarity as well as annotations from manually curated resources such the catalytic site atlas and MACiE for enzyme mechanisms.

(File-01) Free enzymes molecular dynamics:

input parameters and topologies for aPGA, ecPGA and paPvdQ enzymes

general input files for MD simulations in AMBER

output restart files from minimization, equilibration and production runs

output files from minimization, equilibration and production runs

raw data for analysis and visualization:

protein backbone RMSD evolution

binding cavity dynamics analysis

principal component analysis of catalytic machinery (with states' representatives in PDF format)

(File-02) Ligand-enzyme complexes molecular dynamics:

input parameters and topologies for aPGA, ecPGA and paPvdQ in complex with C06- and C08-HSL molecules

general input files for MD simulations in AMBER

output restart files from minimization, equilibration and production runs

output files from minimization, equilibration and production runs

raw data for analysis and visualization:

protein backbone RMSD evolution

near-attack-conformation (NAC) stabilization

HSLs RMSD evolution

MM/PBSA binding energy estimation

HSLs heavy atoms RMSF

(File-03) Michaelis complex ensemble generation molecular dynamics:

input parameters and topologies for aPGA, ecPGA and paPvdQ in complex with C06- and C08-HSL molecules

general input files for MD simulations in AMBER

output restart files from ensemble generation production runs

output files from ensemble generation production runs

(Files-04-06) Ligand-enzyme QM/MM steered molecular dynamics:

input parameters for aPGA, ecPGA and paPvdQ in complex with C06- and C08-HSL molecules

ensemble of input restart files generated in stage 3

general input files for QM/MM steered MD simulations in AMBER

output restart files from QM/MM MD equilibration simulations and QM/MM steered MD simulations

output files and output work from QM/MM steered MD simulations

(File-07) Ligand-enzyme QM/MM steered molecular dynamics data for analysis and visualization:

reaction states ensembles (in PDB format) extracted from QM/MM steered MD simulations with crucial distances measured

evolution of the reaction coordinate elements in the first and second step of acylation

representative states of the reaction stages for visualization (in PDB format)

different dynamics of the residues gating access to acyl-binding cavity at TS1

different dynamics of the residues gating overall access to active site at TS2a

different system-dependent bending of the HSLs at TS1 and TS2a

Intracellular leucine aminopeptidases (PepA) are metalloproteases from the family M17. These enzymes catalyze peptide bond cleavage, removing N-terminal residues from peptide and protein substrates, with consequences for protein homeostasis and quality control. While general mechanistic studies using model substrates have been conducted on PepA enzymes from various organisms, specific information about their substrate preferences and promiscuity, choice of metal, activation mechanisms, and the steps that limit steady-state turnover remain unexplored. Here, we dissected the catalytic and chemical mechanisms of PaPepA: a leucine aminopeptidase from Pseudomonas aeruginosa. Cleavage assays using peptides and small-molecule substrate mimics allowed us to propose a mechanism for catalysis. Steady-state and pre-steady-state kinetics, pH rate profiles, solvent kinetic isotope effects, and biophysical techniques were used to evaluate metal binding and activation. This revealed that metal binding to a tight affinity site is insufficient for enzyme activity; binding to a weaker affinity site is essential for catalysis. Progress curves for peptide hydrolysis and crystal structures of free and inhibitor-bound PaPepA revealed that PaPepA cleaves peptide substrates in a processive manner. We propose three distinct modes for activity regulation: tight packing of PaPepA in a hexameric assembly controls substrate length and reaction processivity; the product leucine acts as an inhibitor, and the high concentration of metal ions required for activation limits catalytic turnover. Our work uncovers catalysis by a metalloaminopeptidase, revealing the intricacies of metal activation and substrate selection. This will pave the way for a deeper understanding of metalloenzymes and processive peptidases/proteases.

Enzyme activity is affected by amino acid mutations, particularly mutations near the active site. Increasing evidence has shown that distal mutations more than 10 Å away from the active site may significantly affect enzyme activity. However, it is difficult to study the enzyme regulation mechanism of distal mutations due to the lack of a systematic collection of three-dimensional (3D) structures, highlighting distal mutation site and the corresponding enzyme activity change. Therefore, we constructed a distal mutation database, namely, D3DistalMutation, which relates the distal mutation to enzyme activity. As a result, we observed that approximately 80% of distal mutations could affect enzyme activity and 72.7% of distal mutations would decrease or abolish enzyme activity in D3DistalMutation. Only 6.6% of distal mutations in D3DistalMutation could increase enzyme activity, which have great potential to the industrial field. Among these mutations, the Y to F, S to D, and T to D mutations are most likely to increase enzyme activity, which sheds some light on industrial catalysis. Distal mutations decreasing enzyme activity in the allosteric pocket play an indispensable role in allosteric drug design. In addition, the pockets in the enzyme structures are provided to explore the enzyme regulation mechanism of distal mutations. D3DistalMutation is accessible free of charge at https://www.d3pharma.com/D3DistalMutation/index.php.

Protein-Protein, Genetic, and Chemical Interactions for Bocik WE (2011):Mechanism of polyubiquitin chain recognition by the human ubiquitin conjugating enzyme Ube2g2. curated by BioGRID (https://thebiogrid.org); ABSTRACT: Ube2g2 is a human ubiquitin conjugating (E2) enzyme involved in the endoplasmic reticulum-associated degradation pathway, which is responsible for the identification and degradation of unfolded and misfolded proteins in the endoplasmic reticulum compartment. The Ube2g2-specific role is the assembly of Lys-48-linked polyubiquitin chains, which constitutes a signal for proteasomal degradation when attached to a substrate protein. NMR chemical shift perturbation and paramagnetic relaxation enhancement approaches were employed to characterize the binding interaction between Ube2g2 and ubiquitin, Lys-48-linked diubiquitin, and Lys-63-linked diubiquitin. Results demonstrate that ubiquitin binds to Ube2g2 with an affinity of 90 μM in two different orientations that are rotated by 180° in models generated by the RosettaDock modeling suite. The binding of Ube2g2 to Lys-48- and Lys-63-linked diubiquitin is primarily driven by interactions with individual ubiquitin subunits, with a clear preference for the subunit containing the free Lys-48 or Lys-63 side chain (i.e. the distal subunit). This preference is particularly striking in the case of Lys-48-linked diubiquitin, which exhibits an ∼3-fold difference in affinities between the two ubiquitin subunits. This difference can be attributed to the partial steric occlusion of the subunit whose Lys-48 side chain is involved in the isopeptide linkage. As such, these results suggest that Lys-48-linked polyubiquitin chains may be designed to bind certain proteins like Ube2g2 such that the terminal ubiquitin subunit carrying the reactive Lys-48 side chain can be positioned properly for chain elongation regardless of chain length.