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PubMed2005

A combined approach to drug metabolism and toxicity assessment.

The challenge of predicting the metabolism or toxicity of a drug in humans has been approached using in vivo animal models, in vitro systems, high throughput genomics and proteomics methods, and, more recently, computational approaches. Understanding the complexity of biological systems requires a broader perspective rather than focusing on just one method in isolation for prediction. Multiple methods may therefore be necessary and combined for a more accurate prediction. In the field of drug metabolism and toxicology, we have seen the growth, in recent years, of computational quantitative structure-activity relationships (QSARs), as well as empirical data from microarrays. In the current study we have further developed a novel computational approach, MetaDrug, that 1) predicts metabolites for molecules based on their chemical structure, 2) predicts the activity of the original compound and its metabolites with various absorption, distribution, metabolism, excretion, and toxicity models, 3) incorporates the predictions with human cell signaling and metabolic pathways and networks, and 4) integrates networks and metabolites, with relevant toxicogenomic or other high throughput data. We have demonstrated the utility of such an approach using recently published data from in vitro metabolism and microarray studies for aprepitant, 2(S)-((3,5-bis(trifluoromethyl)benzyl)-oxy)-3(S)phenyl-4-((3-oxo-1,2,4-triazol-5-yl)methyl)morpholine (L-742694), trovofloxacin, 4-hydroxytamoxifen, and artemisinin and other artemisinin analogs to show the predicted interactions with cytochromes P450, pregnane X receptor, and P-glycoprotein, and the metabolites and the networks of genes that are affected. As a comparison, we used a second computational approach, MetaCore, to generate statistically significant gene networks with the available expression data. These case studies demonstrate the combination of QSARs and systems biology methods.

Drug-Related Side Effects and Adverse Reactions↗
PubMed2002

MMT--a pathway modeling tool for data from rapid sampling experiments.

The identification of metabolic regulation is a major concern in metabolic engineering. Metabolic regulation phenomena depend on intracellular compounds such as enzymes, metabolites and cofactors. A complete understanding of metabolic regulation requires quantitative information about these compounds under in vivo conditions. This quantitative knowledge in combination with the known network of metabolic pathways allows the construction of mathematical models that describe the dynamic changes in metabolite concentrations over time. Rapid sampling combined with pulse experiments is a useful tool for the identification of metabolic regulation owing to the transient data they provide. Enzymatic tests in combination with ESI-LC-MS (Electrospray Ionization Liquid Chromatographic Tandem Mass Spectrometry) and HPLC measurements have been used to identify up to 30 metabolites and nucleotides from rapid sampling experiments. A metabolic modeling tool (MMT) that is built on a relational database was developed specifically for analysis of rapid sampling experiments. The tool allows to construct complex pathway models with information stored in the relational database. Parameter fitting and simulation algorithms for the resulting system of Ordinary Differential Equations (ODEs) are part of MMT. Additionally explicit sensitivity functions are calculated. The integration of all necessary algorithms in one tool allows fast model analysis and comparison. Complex models have been developed to describe the central metabolic pathways of Escherichia coli during a glucose pulse experiment.

Algorithms↗
PubMed2002

Extreme pathway analysis of human red blood cell metabolism.

The development of high-throughput technologies and the resulting large-scale data sets have necessitated a systems approach to the analysis of metabolic networks. One way to approach the issue of complex metabolic function is through the calculation and interpretation of extreme pathways. Extreme pathways are a mathematically defined set of generating vectors that describe the conical steady-state solution space for flux distributions through an entire metabolic network. Herein, the extreme pathways of the well-characterized human red blood cell metabolic network were calculated and interpreted in a biochemical and physiological context. These extreme pathways were divided into groups based on such criteria as their cofactor and by-product production, and carbon inputs including those that 1) convert glucose to pyruvate; 2) interchange pyruvate and lactate; 3) produce 2,3-diphosphoglycerate that binds to hemoglobin; 4) convert inosine to pyruvate; 5) induce a change in the total adenosine pool; and 6) dissipate ATP. Additionally, results from a full kinetic model of red blood cell metabolism were predicted based solely on an interpretation of the extreme pathway structure. The extreme pathways for the red blood cell thus give a concise representation of red blood cell metabolism and a way to interpret its metabolic physiology.

2,3-Diphosphoglycerate↗
PubMed1999

Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering.

Rational metabolic engineering requires powerful theoretical methods such as pathway analysis, in which the topology of metabolic networks is considered. All metabolic capabilities in steady states are composed of elementary flux modes, which are minimal sets of enzymes that can each generate valid steady states. The modes of the fructose-2,6-bisphosphate cycle, the combined tricarboxylic-acid-glyoxylate-shunt system and tryptophan synthesis are used here for illustration. This approach can be used for many biotechnological applications such as increasing the yield of a product, channelling a product into desired pathways and in functional reconstruction from genomic data.

Biochemistry↗
PubMed2006

Robustness and evolvability in genetic regulatory networks.

Living organisms are robust to a great variety of genetic changes. Gene regulation networks and metabolic pathways self-organize and reaccommodate to make the organism perform with stability and reliability under many point mutations, gene duplications and gene deletions. At the same time, living organisms are evolvable, which means that these kind of genetic perturbations can eventually make the organism acquire new functions and adapt to new environments. It is still an open problem to determine how robustness and evolvability blend together at the genetic level to produce stable organisms that yet can change and evolve. Here we address this problem by studying the robustness and evolvability of the attractor landscape of genetic regulatory network models under the process of gene duplication followed by divergence. We show that an intrinsic property of this kind of networks is that, after the divergence of the parent and duplicate genes, with a high probability the previous phenotypes, encoded in the attractor landscape of the network, are preserved and new ones might appear. The above is true in a variety of network topologies and even for the case of extreme divergence in which the duplicate gene bears almost no relation with its parent. Our results indicate that networks operating close to the so-called "critical regime" exhibit the maximum robustness and evolvability simultaneously.

Animals↗
PubMed2004

The iProClass integrated database for protein functional analysis.

Increasingly, scientists have begun to tackle gene functions and other complex regulatory processes by studying organisms at the global scales for various levels of biological organization, ranging from genomes to metabolomes and physiomes. Meanwhile, new bioinformatics methods have been developed for inferring protein function using associative analysis of functional properties to complement the traditional sequence homology-based methods. To fully exploit the value of the high-throughput system biology data and to facilitate protein functional studies requires bioinformatics infrastructures that support both data integration and associative analysis. The iProClass database, designed to serve as a framework for data integration in a distributed networking environment, provides comprehensive descriptions of all proteins, with rich links to over 50 databases of protein family, function, pathway, interaction, modification, structure, genome, ontology, literature, and taxonomy. In particular, the database is organized with PIRSF family classification and maps to other family, function, and structure classification schemes. Coupled with the underlying taxonomic information for complete genomes, the iProClass system (http://pir.georgetown.edu/iproclass/) supports associative studies of protein family, domain, function, and structure. A case study of the phosphoglycerate mutases illustrates a systematic approach for protein family and phylogenetic analysis. Such studies may serve as a basis for further analysis of protein functional evolution, and its relationship to the co-evolution of metabolic pathways, cellular networks, and organisms.

Amino Acid Sequence↗
PubMedDate not supplied

Clinical approach to treatable inborn metabolic diseases: an introduction.

In view of the major improvements in treatment, it has become increasingly important that in order for first-line physicians not to miss a treatable disorder they should be able initiate a simple method of clinical screening, particularly in the emergency room. We present a simplified classification of treatable inborn errors of metabolism in three groups. Group 1 includes inborn errors of intermediary metabolism that give rise to an acute or chronic intoxication. It encompasses aminoacidopathies, organic acidurias, urea cycle disorders, sugar intolerances, metal disorders and porphyrias. Clinical expression can be acute or systemic or can involve a specific organ, and can strike in the neonatal period or later and intermittently from infancy to late adulthood. Most of these disorders are treatable and require the emergency removal of the toxin by special diets, extracorporeal procedures, cleansing drugs or vitamins. Group 2 includes inborn errors of intermediary metabolism that affect the cytoplasmic and mitochondrial energetic processes. Cytoplasmic defects encompass those affecting glycolysis, glycogenosis, gluconeogenesis, hyperinsulinisms, and creatine and pentose phosphate pathways; the latter are untreatable. Mitochondrial defects include respiratory chain disorders, and Krebs cycle and pyruvate oxidation defects, mostly untreatable, and disorders of fatty acid oxidation and ketone bodies that are treatable. Group 3 involves cellular organelles and includes lysosomal, peroxisomal, glycosylation, and cholesterol synthesis defects. Among these, some lysosomal disorders can be efficiently treated by enzyme replacement or substrate reduction therapies. Physicians can be faced with the possibility of a treatable inborn error in an emergency, either in the neonatal period or late in infancy to adulthood, or as chronic and progressive symptoms--general (failure to thrive), neurological, or specific for various organs or systems. These symptoms are summarized in four tables. In addition, an extensive list of medications used in the treatment of inborn errors is presented.

Humans↗
PubMedDate not supplied

B6-responsive disorders: a model of vitamin dependency.

Pyridoxal phosphate is the cofactor for over 100 enzyme-catalysed reactions in the body, including many involved in the synthesis or catabolism of neurotransmitters. Inadequate levels of pyridoxal phosphate in the brain cause neurological dysfunction, particularly epilepsy. There are several different mechanisms that lead to an increased requirement for pyridoxine and/or pyridoxal phosphate. These include: (i) inborn errors affecting the pathways of B(6) vitamer metabolism; (ii) inborn errors that lead to accumulation of small molecules that react with pyridoxal phosphate and inactivate it; (iii) drugs that react with pyridoxal phosphate; (iv) coeliac disease, which is thought to lead to malabsorption of B(6) vitamers; (v) renal dialysis, which leads to increased losses of B(6) vitamers from the circulation; (vi) drugs that affect the metabolism of B(6) vitamers; and (vii) inborn errors affecting specific pyridoxal phosphate-dependent enzymes. The last show a very variable degree of pyridoxine responsiveness, from 90% in X-linked sideroblastic anaemia (delta-aminolevulinate synthase deficiency) through 50% in homocystinuria (cystathionine beta-synthase deficiency) to 5% in ornithinaemia with gyrate atrophy (ornithine delta-aminotransferase deficiency). The possible role of pyridoxal phosphate as a chaperone during folding of nascent enzymes is discussed. High-dose pyridoxine or pyridoxal phosphate may have deleterious side-effects (particularly peripheral neuropathy with pyridoxine) and this must be considered in treatment regimes. None the less, in some patients, particularly infants with intractable epilepsy, treatment with pyridoxine or pyridoxal phosphate can be life-saving, and in other infants with inborn errors of metabolism B(6) treatment can be extremely beneficial.

Dietary Supplements↗
PubMed2007

HMDB: the Human Metabolome Database.

The Human Metabolome Database (HMDB) is currently the most complete and comprehensive curated collection of human metabolite and human metabolism data in the world. It contains records for more than 2180 endogenous metabolites with information gathered from thousands of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the HMDB also contains an extensive collection of experimental metabolite concentration data compiled from hundreds of mass spectra (MS) and Nuclear Magnetic resonance (NMR) metabolomic analyses performed on urine, blood and cerebrospinal fluid samples. This is further supplemented with thousands of NMR and MS spectra collected on purified, reference metabolites. Each metabolite entry in the HMDB contains an average of 90 separate data fields including a comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, biofluid concentrations, disease associations, pathway information, enzyme data, gene sequence data, SNP and mutation data as well as extensive links to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided. The HMDB is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. The HMDB is available at: www.hmdb.ca.

Databases, Factual↗