Ellis, L.B., Hershberger, C.D., Bryan, E.M., and Wackett, L.P.. "The University of Minnesota Biocatalysis/Biodegradation Database: emphasizing enzymes." Nucleic Acids Res. 29
(1).
2001.
pp. 340-3.
[ .pdf ] [ PubMed ]
The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.ahc.umn.edu/) provides curated information on microbial catabolic enzymes and their organization into metabolic pathways. Currently, it contains information on over 400 enzymes. In the last year the enzyme page was enhanced to contain more internal and external links; it also displays the different metabolic pathways in which each enzyme participates. In collaboration with the Nomenclature Commission of the International Union of Biochemistry and Molecular Biology, 35 UM-BBD enzymes were assigned complete EC codes during 2000. Bacterial oxygenases are heavily represented in the UM-BBD; they are known to have broad substrate specificity. A compilation of known reactions of naphthalene and toluene dioxygenases were recently added to the UM-BBD; 73 and 108 were listed respectively. In 2000 the UM-BBD is mirrored by two prestigious groups: the European Bioinformatics Institute and KEGG (the Kyoto Encyclopedia of Genes and Genomes). Collaborations with other groups are being developed. The increased emphasis on UM-BBD enzymes is important for predicting novel metabolic pathways that might exist in nature or could be engineered. It also is important for current efforts in microbial genome annotation.
Keywords: Bacteria_genetics ; Bacteria_metabolism ; Biodegradation ; Catalysis ; *Databases Factual ; Enzymes_genetics ; Enzymes_*metabolism ; Fungi_genetics ; Fungi_metabolism ; Information Storage and Retrieval ; Internet
Ellis, L.B., Hershberger, C.D., and Wackett, L.P.. "The University of Minnesota Biocatalysis/Biodegradation database: microorganisms, genomics and prediction." Nucleic Acids Res. 28
(1).
2000.
pp. 377-9.
[ .pdf ] [ PubMed ]
The University of Minnesota Biocatalysis/Biodegradation Database (http://www.labmed.umn.edu/umbbd/ ) begins its fifth year having met its initial goals. It contains approximately 100 pathways for microbial catabolic metabolism of primarily xenobiotic organic compounds, including information on approximately 650 reactions, 600 compounds and 400 enzymes, and containing approximately 250 microorganism entries. It includes information on most known microbial catabolic reaction types and the organic functional groups they transform. Having reached its first goals, it is ready to move beyond them. It is poised to grow in many different ways, including mirror sites; fold prediction for its sequenced enzymes; closer ties to genome and microbial strain databases; and the prediction of biodegradation pathways for compounds it does not contain.
Keywords: Biodegradation ; Catalysis ; *Databases Factual ; *Genome ; *Microbiology
Ellis, L.B., Hershberger, C.D., and Wackett, L.P.. "The University of Minnesota Biocatalysis/Biodegradation Database: specialized metabolism for functional genomics." Nucleic Acids Res. 27
(1).
1999.
pp. 373-6.
[ .pdf ] [ PubMed ]
The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://www.labmed.umn.edu/umbbd/i nde x.html) first became available on the web in 1995 to provide information on microbial biocatalytic reactions of, and biodegradation pathways for, organic chemical compounds, especially those produced by man. Its goal is to become a representative database of biodegradation, spanning the diversity of known microbial metabolic routes, organic functional groups, and environmental conditions under which biodegradation occurs. The database can be used to enhance understanding of basic biochemistry, biocatalysis leading to speciality chemical manufacture, and biodegradation of environmental pollutants. It is also a resource for functional genomics, since it contains information on enzymes and genes involved in specialized metabolism not found in intermediary metabolism databases, and thus can assist in assigning functions to genes homologous to such less common genes. With information on >400 reactions and compounds, it is poised to become a resource for prediction of microbial biodegradation pathways for compounds it does not contain, a process complementary to predicting the functions of new classes of microbial genes.
Keywords: Bacteria_genetics ; Bacteria_*metabolism ; Bacterial Proteins_metabolism ; *Biodegradation ; Biotechnology ; *Catalysis ; *Databases Factual_trends ; Environmental Pollution ; Enzymes_chemistry ; Enzymes_genetics ; Enzymes_metabolism ; Genes ; Bacterial_genetics ; Genes ; Bacterial_physiology ; Human ; Information Storage and Retrieval ; Internet ; Minnesota ; Universities
Hofestadt, R. and Thelen, S.. "Quantitative modeling of biochemical networks." In Silico Biol. 1
(1).
1998.
pp. 39-53.
[ PubMed ] [ WebSite ]
Today different database systems for molecular structures (genes and proteins) and metabolic pathways are available. All these systems are characterized by the static data representation. For progress in biotechnology the dynamic representation of this data is important. The metabolism can be characterized as a complex biochemical network. Different models for the quantitative simulation of biochemical networks are discussed, but no useful formalization is available. This paper shows that the theory of Petrinets is useful for the quantitative modeling of biochemical networks.
Keywords: *Biochemistry ; Biotechnology ; Catalysis ; Computational Biology ; *Computer Simulation ; Databases Factual ; Glycolysis ; Models Biological ; Protein Engineering
Kuffner, R., Zimmer, R., and Lengauer, T.. "Pathway analysis in metabolic databases via differential metabolic display (DMD)." Bioinformatics. 16
(9).
2000.
pp. 825-36.
[ .pdf ] [ PubMed ] [ WebSite ]
MOTIVATION: A number of metabolic databases are available electronically, some with features for querying and visualizing metabolic pathways and regulatory networks. We present a unifying, systematic approach based on PETRI nets for storing, displaying, comparing, searching and simulating such nets from a number of different sources. RESULTS: Information from each data source is extracted and compiled into a PETRI net. Such PETRI nets then allow to investigate the (differential) content in metabolic databases, to map and integrate genomic information and functional annotations, to compare sequence and metabolic databases with respect to their functional annotations, and to define, generate and search paths and pathways in nets. We present an algorithm to systematically generate all pathways satisfying additional constraints in such PETRI nets. Finally, based on the set of valid pathways, so-called differential metabolic displays (DMDs) are introduced to exhibit specific differences between biological systems, i.e. different developmental states, disease states, or different organisms, on the level of paths and pathways. DMDs will be useful for target finding and function prediction, especially in the context of the interpretation of expression data.
Keywords: *Algorithms ; Catalysis ; Computational Biology_*methods ; Computer Simulation ; *Data Display ; *Databases Factual ; Enzymes_genetics ; Enzymes_metabolism ; Glycolysis ; Metabolism_*physiology ; Mycoplasma_metabolism ; Yeasts_metabolism
Mavrovouniotis, M.L.. "Describing multiple levels of abstraction in the metabolism." Proc Int Conf Intell Syst Mol Biol.
vol. 2.
1994.
pp. 294-302.
[ PubMed ]
We discuss some central issues that arise in the computer representation of the metabolism and its subsystems. We provide a framework for the representation of metabolites and bioreactions at multiple levels of detail. The framework is based on defining an explicit linear mapping of metabolites and reactions from one level of detail to another. A simple reaction mechanism serves as an illustration and shows the emergence of the concept of a catalyst from metabolic abstraction levels.
Keywords: Catalysis ; *Computer Simulation ; *Metabolism