BRENDA, the enzyme information system in 2011

The BRENDA (BRaunschweig ENzyme Database, http://www.brenda-enzymes.org) enzyme information system is the main collection of enzyme functional and property data for the scientific community. The majority of the data are manually extracted from the primary literature. The content covers information on function, structure, occurrence, preparation and application of enzymes as well as properties of mutants and engineered variants. The number of manually annotated references increased by 30% to more than 100 000, the number of ligand structures by 45% to almost 100 000. New query, analysis and data management tools were implemented to improve data processing, data presentation, data input and data access. BRENDA now provides new viewing options such as the display of the statistics of functional parameters and the 3D view of protein sequence and structure features. Furthermore a ligand summary shows comprehensive information on the BRENDA ligands. The enzymes are linked to their respective pathways and can be viewed in pathway maps. The disease text mining part is strongly enhanced. It is possible to submit new, not yet classified enzymes to BRENDA, which then are reviewed and classified by the International Union of Biochemistry and Molecular Biology. A new SBML output format of BRENDA kinetic data allows the construction of organism-specific metabolic models

Self-organization of signal transduction

We propose a model of parameter learning for signal transduction, where the objective function is defined by signal transmission efficiency. We apply this to learn kinetic rates as a form of evolutionary learning, and look for parameters which satisfy the objective. This is a novel approach compared to the usual technique of adjusting parameters only on the basis of experimental data. The resulting model is self-organizing, i.e. perturbations in protein concentrations or changes in extracellular signaling will automatically lead to adaptation. We systematically perturb protein concentrations and observe the response of the system. We find compensatory or co-regulation of protein expression levels. In a novel experiment, we alter the distribution of extracellular signaling, and observe adaptation based on optimizing signal transmission. We also discuss the relationship between signaling with and without transients. Signaling by transients may involve maximization of signal transmission efficiency for the peak response, but a minimization in steady-state responses. With an appropriate objective function, this can also be achieved by concentration adjustment. Self-organizing systems may be predictive of unwanted drug interference effects, since they aim to mimic complex cellular adaptation in a unified way.Comment: updated version, 13 pages, 4 figures, 3 Tables, supplemental tabl

Serine biosynthesis with one carbon catabolism represents a novel pathway for ATP generation in cells using alternative glycolysis with zero net ATP production

Recent experimental evidence indicates that some cancer cells have an alternative glycolysis pathway with net zero ATP production, implying that upregulation of glycolysis in these cells may not be related to the generation of ATP. Here we use a genome-scale model of human cell metabolism to investigate the potential metabolic alterations in cells using net zero ATP glycolysis. We uncover a novel pathway for ATP generation that involves reactions from the serine biosynthesis and one-carbon metabolism pathways. This pathway has a predicted two-fold higher flux rate in cells using net zero ATP glycolysis than those using standard glycolysis and generates twice as much ATP with significantly lower rate of lactate- but higher rate of alanine secretion. Thus, in cells using the standard- or the net zero ATP glycolysis pathways a significant portion of the glycolysis flux is always associated with ATP generation, and the ratio between the flux rates of the two pathways determines the rate of ATP generation and lactate and alanine secretion during glycolysis

Serine biosynthesis with one carbon catabolism represents a novel pathway for ATP generation in cells using alternative glycolysis with zero net ATP production

Recent experimental evidence indicates that some cancer cells have an alternative glycolysis pathway with net zero ATP production, implying that upregulation of glycolysis in these cells may not be related to the generation of ATP. Here we use a genome-scale model of human cell metabolism to investigate the potential metabolic alterations in cells using net zero ATP glycolysis. We uncover a novel pathway for ATP generation that involves reactions from the serine biosynthesis and one-carbon metabolism pathways. This pathway has a predicted two-fold higher flux rate in cells using net zero ATP glycolysis than those using standard glycolysis and generates twice as much ATP with significantly lower rate of lactate- but higher rate of alanine secretion. Thus, in cells using the standard- or the net zero ATP glycolysis pathways a significant portion of the glycolysis flux is always associated with ATP generation, and the ratio between the flux rates of the two pathways determines the rate of ATP generation and lactate and alanine secretion during glycolysis

Evaluation of rate law approximations in bottom-up kinetic models of metabolism.

BackgroundThe mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question.ResultsIn this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations.ConclusionsOverall, our work generally supports the use of approximate rate laws when building large scale kinetic models, due to the key role that physiologically meaningful flux and concentration ranges play in determining network dynamics. However, we also showed that detailed mechanistic models show a clear benefit in prediction accuracy when data is available. The work here should help to provide guidance to future kinetic modeling efforts on the choice of rate law and parameterization approaches

MetaCrop 2.0: managing and exploring information about crop plant metabolism

MetaCrop is a manually curated repository of high-quality data about plant metabolism, providing different levels of detail from overview maps of primary metabolism to kinetic data of enzymes. It contains information about seven major crop plants with high agronomical importance and two model plants. MetaCrop is intended to support research aimed at the improvement of crops for both nutrition and industrial use. It can be accessed via web, web services and an add-on to the Vanted software. Here, we present several novel developments of the MetaCrop system and the extended database content. MetaCrop is now available in version 2.0 at http://metacrop.ipk-gatersleben.de

Assignment of novel functions to Helicobacter pylori 26695’s genome

Helicobacter pylori is a pathogenic bacterium that colonizes the human epithelia, causing duodenal and gastric ulcers as well as gastric cancer. The genome of H. pylori 26695 has been sequenced and annotated. In addition, two genome-scale metabolic models have been developed. In order to maintain accurate and relevant information on coding sequences (CDS) and to retrieve new information, the assignment of new functions to Helicobacter pylori 26695’s genes was performed. The use of software tools, on-line databases and an annotation pipeline for inspecting each gene allowed the attribution of validated E.C. numbers to metabolic genes, and the assignment of 177 new functions to the CDS of this bacterium. This information provides relevant biological information for the scientific community dealing with this organism and can be used as the basis for a new metabolic model reconstruction.(undefined

IUPHAR-DB: updated database content and new features

The International Union of Basic and Clinical Pharmacology (IUPHAR) database, IUPHAR-DB (http://www.iuphar-db.org) is an open access, online database providing detailed, expert-driven annotation of the primary literature on human and rodent receptors and other drug targets, together with the substances that act on them. The present release includes information on the products of 646 genes from four major protein classes (G protein-coupled receptors, nuclear hormone receptors, voltage- and ligand-gated ion channels) and ∼3180 bioactive molecules (endogenous ligands, licensed drugs and key pharmacological tools) that interact with them. We have described previously the classification and curation of data for small molecule ligands in the database; in this update we have annotated 366 endogenous peptide ligands with their amino acid sequences, post-translational modifications, links to precursor genes, species differences and relationships with other molecules in the database (e.g. those derived from the same precursor). We have also matched targets with their endogenous ligands (peptides and small molecules), with particular attention paid to identifying bioactive peptide ligands generated by post-translational modification of precursor proteins. Other improvements to the database include enhanced information on the clinical relevance of targets and ligands in the database, more extensive links to other databases and a pilot project for the curation of enzymes as drug targets

BKM-react, an integrated biochemical reaction database

<p>Abstract</p> <p>Background</p> <p>The systematic, complete and correct reconstruction of genome-scale metabolic networks or metabolic pathways is one of the most challenging tasks in systems biology research. An essential requirement is the access to the complete biochemical knowledge - especially on the biochemical reactions. This knowledge is extracted from the scientific literature and collected in biological databases. Since the available databases differ in the number of biochemical reactions and the annotation of the reactions, an integrated knowledge resource would be of great value.</p> <p>Results</p> <p>We developed a comprehensive non-redundant reaction database containing known enzyme-catalyzed and spontaneous reactions. Currently, it comprises 18,172 unique biochemical reactions. As source databases the biochemical databases <it>BRENDA</it>, <it>KEGG</it>, and <it>MetaCyc </it>were used. Reactions of these databases were matched and integrated by aligning substrates and products. For the latter a two-step comparison using their structures (<it>via InChIs</it>) and names was performed. Each biochemical reaction given as a reaction equation occurring in at least one of the databases was included.</p> <p>Conclusions</p> <p>An integrated non-redundant reaction database has been developed and is made available to users. The database can significantly facilitate and accelerate the construction of accurate biochemical models.</p