29 research outputs found
ORENZA: a web resource for studying ORphan ENZyme activities
BACKGROUND: Despite the current availability of several hundreds of thousands of amino acid sequences, more than 36% of the enzyme activities (EC numbers) defined by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB) are not associated with any amino acid sequence in major public databases. This wide gap separating knowledge of biochemical function and sequence information is found for nearly all classes of enzymes. Thus, there is an urgent need to explore these sequence-less EC numbers, in order to progressively close this gap. DESCRIPTION: We designed ORENZA, a PostgreSQL database of ORphan ENZyme Activities, to collate information about the EC numbers defined by the NC-IUBMB with specific emphasis on orphan enzyme activities. Complete lists of all EC numbers and of orphan EC numbers are available and will be periodically updated. ORENZA allows one to browse the complete list of EC numbers or the subset associated with orphan enzymes or to query a specific EC number, an enzyme name or a species name for those interested in particular organisms. It is possible to search ORENZA for the different biochemical properties of the defined enzymes, the metabolic pathways in which they participate, the taxonomic data of the organisms whose genomes encode them, and many other features. The association of an enzyme activity with an amino acid sequence is clearly underlined, making it easy to identify at once the orphan enzyme activities. Interactive publishing of suggestions by the community would provide expert evidence for re-annotation of orphan EC numbers in public databases. CONCLUSION: ORENZA is a Web resource designed to progressively bridge the unwanted gap between function (enzyme activities) and sequence (dataset present in public databases). ORENZA should increase interactions between communities of biochemists and of genomicists. This is expected to reduce the number of orphan enzyme activities by allocating gene sequences to the relevant enzymes
New Insight into the Transcarbamylase Family: The Structure of Putrescine Transcarbamylase, a Key Catalyst for Fermentative Utilization of Agmatine
Transcarbamylases reversibly transfer a carbamyl group from carbamylphosphate (CP) to an amine. Although aspartate transcarbamylase and ornithine transcarbamylase (OTC) are well characterized, little was known about putrescine transcarbamylase (PTC), the enzyme that generates CP for ATP production in the fermentative catabolism of agmatine. We demonstrate that PTC (from Enterococcus faecalis), in addition to using putrescine, can utilize L-ornithine as a poor substrate. Crystal structures at 2.5 Å and 2.0 Å resolutions of PTC bound to its respective bisubstrate analog inhibitors for putrescine and ornithine use, N-(phosphonoacetyl)-putrescine and δ-N-(phosphonoacetyl)-L-ornithine, shed light on PTC preference for putrescine. Except for a highly prominent C-terminal helix that projects away and embraces an adjacent subunit, PTC closely resembles OTCs, suggesting recent divergence of the two enzymes. Since differences between the respective 230 and SMG loops of PTC and OTC appeared to account for the differential preference of these enzymes for putrescine and ornithine, we engineered the 230-loop of PTC to make it to resemble the SMG loop of OTCs, increasing the activity with ornithine and greatly decreasing the activity with putrescine. We also examined the role of the C-terminal helix that appears a constant and exclusive PTC trait. The enzyme lacking this helix remained active but the PTC trimer stability appeared decreased, since some of the enzyme eluted as monomers from a gel filtration column. In addition, truncated PTC tended to aggregate to hexamers, as shown both chromatographically and by X-ray crystallography. Therefore, the extra C-terminal helix plays a dual role: it stabilizes the PTC trimer and, by shielding helix 1 of an adjacent subunit, it prevents the supratrimeric oligomerizations of obscure significance observed with some OTCs. Guided by the structural data we identify signature traits that permit easy and unambiguous annotation of PTC sequences
pKa Modulation of the Acid/Base Catalyst within GH32 and GH68: A Role in Substrate/Inhibitor Specificity?
Glycoside hydrolases of families 32 (GH32) and 68 (GH68) belong to clan GH-J, containing hydrolytic enzymes (sucrose/fructans as donor substrates) and fructosyltransferases (sucrose/fructans as donor and acceptor substrates). In GH32 members, some of the sugar substrates can also function as inhibitors, this regulatory aspect further adding to the complexity in enzyme functionalities within this family. Although 3D structural information becomes increasingly available within this clan and huge progress has been made on structure-function relationships, it is not clear why some sugars bind as inhibitors without being catalyzed. Conserved aspartate and glutamate residues are well known to act as nucleophile and acid/bases within this clan. Based on the available 3D structures of enzymes and enzyme-ligand complexes as well as docking simulations, we calculated the pKa of the acid-base before and after substrate binding. The obtained results strongly suggest that most GH-J members show an acid-base catalyst that is not sufficiently protonated before ligand entrance, while the acid-base can be fully protonated when a substrate, but not an inhibitor, enters the catalytic pocket. This provides a new mechanistic insight aiming at understanding the complex substrate and inhibitor specificities observed within the GH-J clan. Moreover, besides the effect of substrate entrance on its own, we strongly suggest that a highly conserved arginine residue (in the RDP motif) rather than the previously proposed Tyr motif (not conserved) provides the proton to increase the pKa of the acid-base catalyst
Annotation Error in Public Databases: Misannotation of Molecular Function in Enzyme Superfamilies
Due to the rapid release of new data from genome sequencing projects, the majority of protein sequences in public databases have not been experimentally characterized; rather, sequences are annotated using computational analysis. The level of misannotation and the types of misannotation in large public databases are currently unknown and have not been analyzed in depth. We have investigated the misannotation levels for molecular function in four public protein sequence databases (UniProtKB/Swiss-Prot, GenBank NR, UniProtKB/TrEMBL, and KEGG) for a model set of 37 enzyme families for which extensive experimental information is available. The manually curated database Swiss-Prot shows the lowest annotation error levels (close to 0% for most families); the two other protein sequence databases (GenBank NR and TrEMBL) and the protein sequences in the KEGG pathways database exhibit similar and surprisingly high levels of misannotation that average 5%–63% across the six superfamilies studied. For 10 of the 37 families examined, the level of misannotation in one or more of these databases is >80%. Examination of the NR database over time shows that misannotation has increased from 1993 to 2005. The types of misannotation that were found fall into several categories, most associated with “overprediction” of molecular function. These results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized. Strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannotation
Comparative analyses imply that the enigmatic sigma factor 54 is a central controller of the bacterial exterior
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95738.pdf (publisher's version ) (Open Access)BACKGROUND: Sigma-54 is a central regulator in many pathogenic bacteria and has been linked to a multitude of cellular processes like nitrogen assimilation and important functional traits such as motility, virulence, and biofilm formation. Until now it has remained obscure whether these phenomena and the control by Sigma-54 share an underlying theme. RESULTS: We have uncovered the commonality by performing a range of comparative genome analyses. A) The presence of Sigma-54 and its associated activators was determined for all sequenced prokaryotes. We observed a phylum-dependent distribution that is suggestive of an evolutionary relationship between Sigma-54 and lipopolysaccharide and flagellar biosynthesis. B) All Sigma-54 activators were identified and annotated. The relation with phosphotransfer-mediated signaling (TCS and PTS) and the transport and assimilation of carboxylates and nitrogen containing metabolites was substantiated. C) The function annotations, that were represented within the genomic context of all genes encoding Sigma-54, its activators and its promoters, were analyzed for intra-phylum representation and inter-phylum conservation. Promoters were localized using a straightforward scoring strategy that was formulated to identify similar motifs. We found clear highly-represented and conserved genetic associations with genes that concern the transport and biosynthesis of the metabolic intermediates of exopolysaccharides, flagella, lipids, lipopolysaccharides, lipoproteins and peptidoglycan. CONCLUSION: Our analyses directly implicate Sigma-54 as a central player in the control over the processes that involve the physical interaction of an organism with its environment like in the colonization of a host (virulence) or the formation of biofilm
GlnR and PhoP Directly Regulate the Transcription of Genes Encoding Starch-Degrading, Amylolytic Enzymes in Saccharopolyspora erythraea
Abundant Trimethylornithine Lipids and Specific Gene Sequences Are Indicative of Planctomycete Importance at the Oxic/Anoxic Interface in Sphagnum-Dominated Northern Wetlands
Missing in action: enzyme functional annotations in biological databases.
Annotations of enzyme function provide critical starting points for generating and testing biological hypotheses, but the quality of functional annotations is hindered by uncertain assignments for uncharacterized sequences and by the relative sparseness of validated experimental data. Given the relentless increase in genomic data, new thinking and validation methods are urgently needed to provide high confidence in enzyme functional assignments