EzCatDB: the enzyme reaction database, 2015 update

Identification of an endonuclease and N6-adenine methyltransferase from Ureaplasma parvum SV3F4 strain

Here, we report a novel endonuclease and N6-adenine DNA methyltransferase (m6A methyltransferase) in the Ureaplasma parvum SV3F4 strain. Our previous study found that the SV3F4 strain carries 17 unique genes, which are not encoded in the two previously reported U. parvum serovar 3 strain, OMC-P162 and ATCC 700970. Of these 17 unique genes, UP3_c0261 and UP3_c0262, were originally annotated as encoding hypothetical proteins. Comparative genomics analyses more recently indicated they encode a Type II restriction endonuclease and an m6A methyltransferase, respectively. The UP3_c0261 and UP3_c0262 genes were individually expressed and purified in Escherichia coli. The UP3_c0261 recombinant protein showed endonuclease activity on the pT7Blue vector, recognizing and cleaving a GTNAC motif, resulting in a 5 base 5' extension. The UP3_c0261 protein digested a polymerase chain reaction (PCR) product harboring the GTNAC motif. The endonuclease UP3_c0261 was designated as UpaF4I. Treatment of the PCR product with the recombinant protein UP3_c0262 completely blocked the restriction enzyme activity of UpaF4I. Analysis of the treated PCR product harboring a modified nucleotide by UP3_c0262 with HPLC-MS/MS and MS/MS showed that UP3_c0262 was an m6A methyltransferase containing a methylated A residue in both DNA strands of the GTNAC motif. Whole genome methylation analysis of SV3F4 showed that 99.9 % of the GTNAC motif was m6A modified. These results suggest the UP3_c0261 and UP3_c0262 genes may act as a novel Type II restriction-modification system in the Ureaplasma SV3F4 strain.

Enzyme Databases in the Era of Omics and Artificial Intelligence

Enzyme research is important for the development of various scientific fields such as medicine and biotechnology. Enzyme databases facilitate this research by providing a wide range of information relevant to research planning and data analysis. Over the years, various databases that cover different aspects of enzyme biology (e.g., kinetic parameters, enzyme occurrence, and reaction mechanisms) have been developed. Most of the databases are curated manually, which improves reliability of the information; however, such curation cannot keep pace with the exponential growth in published data. Lack of data standardization is another obstacle for data extraction and analysis. Improving machine readability of databases is especially important in the light of recent advances in deep learning algorithms that require big training datasets. This review provides information regarding the current state of enzyme databases, especially in relation to the ever-increasing amount of generated research data and recent advancements in artificial intelligence algorithms. Furthermore, it describes several enzyme databases, providing the reader with necessary information for their use.

De Novo Computational Design of a Lipase with Hydrolysis Activity towards Middle-Chained Fatty Acid Esters

Innovations in biocatalysts provide great prospects for intolerant environments or novel reactions. Due to the limited catalytic capacity and the long-term and labor-intensive characteristics of mining enzymes with the desired functions, de novo enzyme design was developed to obtain industrial application candidates in a rapid and convenient way. Here, based on the catalytic mechanisms and the known structures of proteins, we proposed a computational protein design strategy combining de novo enzyme design and laboratory-directed evolution. Starting with the theozyme constructed using a quantum-mechanical approach, the theoretical enzyme-skeleton combinations were assembled and optimized via the Rosetta "inside-out" protocol. A small number of designed sequences were experimentally screened using SDS-PAGE, mass spectrometry and a qualitative activity assay in which the designed enzyme 1a8uD₁ exhibited a measurable hydrolysis activity of 24.25 ± 0.57 U/g towards p-nitrophenyl octanoate. To improve the activity of the designed enzyme, molecular dynamics simulations and the RosettaDesign application were utilized to further optimize the substrate binding mode and amino acid sequence, thus keeping the residues of theozyme intact. The redesigned lipase 1a8uD₁-M8 displayed enhanced hydrolysis activity towards p-nitrophenyl octanoate-3.34 times higher than that of 1a8uD₁. Meanwhile, the natural skeleton protein (PDB entry 1a8u) did not display any hydrolysis activity, confirming that the hydrolysis abilities of the designed 1a8uD₁ and the redesigned 1a8uD₁-M8 were devised from scratch. More importantly, the designed 1a8uD₁-M8 was also able to hydrolyze the natural middle-chained substrate (glycerol trioctanoate), for which the activity was 27.67 ± 0.69 U/g. This study indicates that the strategy employed here has great potential to generate novel enzymes exhibiting the desired reactions.

How synonymous mutations alter enzyme structure and function over long timescales

The specific activity of enzymes can be altered over long timescales in cells by synonymous mutations that alter a messenger RNA molecule's sequence but not the encoded protein's primary structure. How this happens at the molecular level is unknown. Here, we use multiscale modelling of three Escherichia coli enzymes (type III chloramphenicol acetyltransferase, D-alanine-D-alanine ligase B and dihydrofolate reductase) to understand experimentally measured changes in specific activity due to synonymous mutations. The modelling involves coarse-grained simulations of protein synthesis and post-translational behaviour, all-atom simulations to test robustness and quantum mechanics/molecular mechanics calculations to characterize enzymatic function. We show that changes in codon translation rates induced by synonymous mutations cause shifts in co-translational and post-translational folding pathways that kinetically partition molecules into subpopulations that very slowly interconvert to the native, functional state. Structurally, these states resemble the native state, with localized misfolding near the active sites of the enzymes. These long-lived states exhibit reduced catalytic activity, as shown by their increased activation energies for the reactions they catalyse.

The Nϵ-Rule for Serine, but Not Cysteine Catalytic Triads

Catalytic triads, composed of a serine or cysteine nucleophile, a histidine, and a third triad residue (typically Asp/Glu/Asn), are common in enzyme active sites and catalyze a wide variety of chemical reactions. Two types of triads can be distinguished: We refer to them as Nδ- or Nϵ-configured, depending on whether the histidine imidazole Nδ or Nϵ atom is close to the nucleophile Oγ/Sγ. In this study, we have analyzed triad configuration. In structural triads, the more stable Nδ-configuration predominates. For catalytic triads, the configuration depends on the nucleophile. When it is a cysteine residue, both configuration types occur, depending on the family. However, when the nucleophile is a serine residue, the less stable Nϵ-configuration is almost exclusively found. We posit that the energetically less favored conformation is selected for in serine triads to facilitate the otherwise difficult proton transfer from the nucleophile to the histidine residue.

Water and Life: The Medium is the Message

Water, the most abundant compound on the surface of the Earth and probably in the universe, is the medium of biology, but is much more than that. Water is the most frequent actor in the chemistry of metabolism. Our quantitation here reveals that water accounts for 99.4% of metabolites in Escherichia coli by molar concentration. Between a third and a half of known biochemical reactions involve consumption or production of water. We calculated the chemical flux of water and observed that in the life of a cell, a given water molecule frequently and repeatedly serves as a reaction substrate, intermediate, cofactor, and product. Our results show that as an E. coli cell replicates in the presence of molecular oxygen, an average in vivo water molecule is chemically transformed or is mechanistically involved in catalysis ~ 3.7 times. We conclude that, for biological water, there is no distinction between medium and chemical participant. Chemical transformations of water provide a basis for understanding not only extant biochemistry, but the origins of life. Because the chemistry of water dominates metabolism and also drives biological synthesis and degradation, it seems likely that metabolism co-evolved with biopolymers, which helps to reconcile polymer-first versus metabolism-first theories for the origins of life.

Skeletal animation for visualizing dynamic shapes of macromolecules

We apply a skeletal animation technique developed for general computer graphics animation to display the dynamic shape of protein molecules. Polygon-based models for macromolecules such as atomic representations, surface models, and protein ribbon models are deformed by the motion of skeletal bones that provide coarse-grained descriptions of detailed computer graphics models. Using the animation software Blender, we developed methods to generate the skeletal bones for molecules. Our example of the superposition of normal modes demonstrates the thermal fluctuating motion obtained from normal mode analysis. The method is also applied to display the motions of protein molecules using trajectory coordinates of a molecular dynamics simulation. We found that a standard motion capture file was practical and useful for describing the motion of the molecule using available computer graphics tools.

A De Novo Designed Esterase with p-Nitrophenyl Acetate Hydrolysis Activity

Esterases are a large family of enzymes with wide applications in the industry. However, all esterases originated from natural sources, limiting their use in harsh environments or newly- emerged reactions. In this study, we designed a new esterase to develop a new protocol to satisfy the needs for better biocatalysts. The ideal spatial conformation of the serine catalytic triad and the oxygen anion hole at the substrate-binding site was constructed by quantum mechanical calculation. The catalytic triad and oxygen anion holes were then embedded in the protein scaffold using the new enzyme protocol in Rosetta 3. The design results were subsequently evaluated, and optimized designs were used for expression and purification. The designed esterase had significant lytic activities towards p-nitrophenyl acetate, which was confirmed by point mutations. Thus, this study developed a new protocol to obtain novel enzymes that may be useful in unforgiving environments or novel reactions.

EnzyMine: a comprehensive database for enzyme function annotation with enzymatic reaction chemical feature

Addition of chemical structural information in enzymatic reactions has proven to be significant for accurate enzyme function prediction. However, such chemical data lack systematic feature mining and hardly exist in enzyme-related databases. Therefore, global mining of enzymatic reactions will offer a unique landscape for researchers to understand the basic functional mechanisms of natural bioprocesses and facilitate enzyme function annotation. Here, we established a new knowledge base called EnzyMine, through which we propose to elucidate enzymatic reaction features and then link them with sequence and structural annotations. EnzyMine represents an advanced database that extends enzyme knowledge by incorporating reaction chemical feature strategies, strengthening the connectivity between enzyme and metabolic reactions. Therefore, it has the potential to reveal many new metabolic pathways involved with given enzymes, as well as expand enzyme function annotation. Database URL: http://www.rxnfinder.org/enzymine/.

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.

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.

Biocuration in the structure-function linkage database: the anatomy of a superfamily

With ever-increasing amounts of sequence data available in both the primary literature and sequence repositories, there is a bottleneck in annotating molecular function to a sequence. This article describes the biocuration process and methods used in the structure-function linkage database (SFLD) to help address some of the challenges. We discuss how the hierarchy within the SFLD allows us to infer detailed functional properties for functionally diverse enzyme superfamilies in which all members are homologous, conserve an aspect of their chemical function and have associated conserved structural features that enable the chemistry. Also presented is the Enzyme Structure-Function Ontology (ESFO), which has been designed to capture the relationships between enzyme sequence, structure and function that underlie the SFLD and is used to guide the biocuration processes within the SFLD.

Database URL:http://sfld.rbvi.ucsf.edu/

Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat

During 11–12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication and funding. An important outcome of this meeting was the creation of a Specialist Protein Resource Network that we believe will improve coordination of the activities of its member resources. We invite further protein database resources to join the network and continue the dialogue.

Key challenges for the creation and maintenance of specialist protein resources

As the volume of data relating to proteins increases, researchers rely more and more on the analysis of published data, thus increasing the importance of good access to these data that vary from the supplemental material of individual articles, all the way to major reference databases with professional staff and long-term funding. Specialist protein resources fill an important middle ground, providing interactive web interfaces to their databases for a focused topic or family of proteins, using specialized approaches that are not feasible in the major reference databases. Many are labors of love, run by a single lab with little or no dedicated funding and there are many challenges to building and maintaining them. This perspective arose from a meeting of several specialist protein resources and major reference databases held at the Wellcome Trust Genome Campus (Cambridge, UK) on August 11 and 12, 2014. During this meeting some common key challenges involved in creating and maintaining such resources were discussed, along with various approaches to address them. In laying out these challenges, we aim to inform users about how these issues impact our resources and illustrate ways in which our working together could enhance their accuracy, currency, and overall value.