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
Goble, C.A., Stevens, R., Ng, G., Bechhofer, S., Paton, N.W., Baker, P.G., Peim, M., and Brass, A.. "Transparent access to multiple bioinformatics information sources" IBM Systems Journal. 40
(2).
2001.
pp. 532--551.
[ .pdf ]
This paper describes the Transparent Access to Multiple Bioinformatics Information Sources project, known as TAMBIS, in which a domain ontology for molecular biology and bioinformatics is used in a retrieval-based information integration system for biologists. The ontology, represented using a description logic and managed by a terminology server, is used both to drive a visual query interface and as a global schema against which complex intersource queries are expressed. These source-independent declarative queries are then rewritten into collections of ordered source-dependent queries for execution by a middleware layer. In bioinformatics, the majority of data sources are not databases but tools with limited accessible interfaces. The ontology helps manage the interoperation between these resources. The paper emphasizes the central role that is played by the ontology in the system. The project distinguishes itself from others in the following ways: the ontology, developed by a biologist, is substantial; the retrieval interface is sophisticated; the description logic is managed by a sophisticated terminology server. A full pilot application is available as a JavaTM applet integrating five sources concerned with proteins. This pilot is currently undergoing field trials with working biologists and is being used to answer real questions in biology, one of which is used as a case study throughout the paper.
Karp, P.D.. "Pathway databases: a case study in computational symbolic theories." Science. 293
(5537).
2001.
pp. 2040-4.
[ .pdf ] [ PubMed ]
A pathway database (DB) is a DB that describes biochemical pathways, reactions, and enzymes. The EcoCyc pathway DB (see http://ecocyc.org) describes the metabolic, transport, and genetic-regulatory networks of Escherichia coli. EcoCyc is an example of a computational symbolic theory, which is a DB that structures a scientific theory within a formal ontology so that it is available for computational analysis. It is argued that by encoding scientific theories in symbolic form, we open new realms of analysis and understanding for theories that would otherwise be too large and complex for scientists to reason with effectively.
Keywords: Artificial Intelligence ; *Computational Biology ; Culture Media ; *Databases Factual ; Escherichia coli_enzymology ; Escherichia coli_*genetics ; Escherichia coli_growth and development ; Escherichia coli_*metabolism ; *Genome Bacterial ; Internet ; Software
Oliveira, J.S., Bailey, C.G., Jones-Oliveira, J.B., and Dixon, D.A.. "An algebraic-combinatorial model for the identification and mapping of biochemical pathways." Bull Math Biol. 63
(6).
2001.
pp. 1163-96.
[ .pdf ] [ PubMed ]
We develop the mathematical machinery for the construction of an algebraic-combinatorial model using Petri nets to construct an oriented matroid representation of biochemical pathways. For demonstration purposes, we use a model metabolic pathway example from the literature to derive a general biochemical reaction network model. The biomolecular networks define a connectivity matrix that identifies a linear representation of a Petri net. The sub-circuits that span a reaction network are subject to flux conservation laws. The conservation laws correspond to algebraic-combinatorial dual invariants, that are called S- (state) and T- (transition) invariants. Each invariant has an associated minimum support. We show that every minimum support of a Petri net invariant defines a unique signed sub-circuit representation. We prove that the family of signed sub-circuits has an implicit order that defines an oriented matroid. The oriented matroid is then used to identify the feasible sub-circuit pathways that span the biochemical network as the positive cycles in a hyper-digraph.
Keywords: Linear Models ; Mathematical Computing ; *Models Biological ; *Models Chemical
Srivastava, R., Peterson, M.S., and Bentley, W.E.. "Stochastic kinetic analysis of the Escherichia coli stress circuit using sigma(32)-targeted antisense." Biotechnol Bioeng. 75
(1).
2001.
pp. 120-9.
[ PubMed ]
A stochastic Petri net model was developed for simulating the sigma(32) stress circuit in E. coli. Transcription factor sigma(32) is the principal regulator of the response of E. coli to heat shock. Stochastic Petri net (SPN) models are well suited for kinetics characterization of fluxes in biochemical pathways. Notably, there exists a one-to-one mapping of model tokens and places to molecules of particular species. Our model was validated against experiments in which ethanol (inducer of heat shock response) and sigma(32)-targeted antisense (downward regulator) were used to perturb the sigma(32) regulatory pathway. The model was also extended to simulate the effects of recombinant protein production. Results show that the stress response depends heavily on the partitioning of sigma(32) within the cell; that is, sigma(32) becomes immediately available to mediate a stress response because it exists primarily in a sequestered, inactive form, complexed with chaperones DnaK, DnaJ, and GrpE. Recombinant proteins, however, also compete for chaperone proteins, particularly when folded improperly. Our simulations indicate that when the expression of recombinant protein has a low requirement for DnaK, DnaJ, and GrpE, the overall sigma(32) levels may drop, but the level of heat shock proteins will increase. Conversely, when the overexpressed recombinant protein has a strong requirement for the chaperones, a severe response is predicted. Interestingly, both cases were observed experimentally.
Keywords: Antisense Elements (Genetics) ; Computer Simulation ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; Ethanol ; Gene Expression Regulation Bacterial ; Heat-Shock Proteins_genetics ; Heat-Shock Proteins_metabolism ; *Models Biological ; Recombinant Proteins_genetics ; Sigma Factor_*genetics ; Sigma Factor_*metabolism ; Solvents ; Stochastic Processes
Zauner, K.P. and Conrad, M.. "Enzymatic computing." Biotechnol Prog. 17
(3).
2001.
pp. 553-9.
[ .pdf ] [ PubMed ]
The conformational dynamics of enzymes is a computational resource that fuses milieu signals in a nonlinear fashion. Response surface methodology can be used to elicit computational functionality from enzyme dynamics. We constructed a tabletop prototype to implement enzymatic signal processing in a device context and employed it in conjunction with malate dehydrogenase to perform the linearly inseparable exclusive-or operation. This shows that proteins can execute signal processing operations that are more complex than those performed by individual threshold elements. We view the experiments reported, though restricted to the two-variable case, as a stepping stone to computational networks that utilize the precise reproducibility of proteins, and the concomitant reproducibility of their nonlinear dynamics, to implement complex pattern transformations.
Keywords: Calcium_chemistry ; Calcium_metabolism ; Enzymes_*chemistry ; Enzymes_*metabolism ; Image Processing ; Computer-Assisted ; Magnesium_chemistry ; Magnesium_metabolism ; Malate Dehydrogenase_chemistry ; Malate Dehydrogenase_metabolism ; Models Chemical ; *Models Molecular ; Osmolar Concentration ; Protein Conformation