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Detection of potential enzyme targets by metabolic modelling and optimization: Application to a simple enzymopathy
- Source :
- Bioinformatics. 23:2281-2289
- Publication Year :
- 2007
- Publisher :
- Oxford University Press (OUP), 2007.
-
Abstract
- Motivation: A very promising approach in drug discovery involves the integration of available biomedical data through mathematical modelling and data mining. We have developed a method called optimization program for drug discovery (OPDD) that allows new enzyme targets to be identified in enzymopathies through the integration of metabolic models and biomedical data in a mathematical optimization program. The method involves four steps: (i) collection of the necessary information about the metabolic system and disease; (ii) translation of the information into mathematical terms; (iii) computation of the optimization programs prioritizing the solutions that propose the inhibition of a reduced number of enzymes and (iv) application of additional biomedical criteria to select and classify the solutions. Each solution consists of a set of predicted values for metabolites, initial substrates and enzyme activities, which describe a biologically acceptable steady state of the system that shifts the pathologic state towards a healthy state.Results: The OPDD was used to detect target enzymes in an enzymopathy, the human hyperuricemia. An existing S-system model and bibliographic information about the disease were used. The method detected six single-target enzyme solutions involving dietary modification, one of them coinciding with the conventional clinical treatment using allopurinol. The OPDD detected a large number of possible solutions involving two enzyme targets. All except one contained one of the previously detected six enzyme targets. The purpose of this work was not to obtain solutions for direct clinical implementation but to illustrate how increasing levels of biomedical information can be integrated together with mathematical models in drug discovery.Contact: julio.vera@informartik.uni-rostock.de or julio_vera_g@yahoo.esSupplementary information: Supplementary data are available at Bioinformatics online.
- Subjects :
- Statistics and Probability
Hyperuricemia
Computational biology
Biology
Models, Biological
Biochemistry
Bibliographic information
Set (abstract data type)
Drug Delivery Systems
Multienzyme Complexes
Ribose-Phosphate Pyrophosphokinase
Humans
Computer Simulation
Enzyme Inhibitors
Molecular Biology
chemistry.chemical_classification
Supplementary data
Mathematical model
Drug discovery
business.industry
Biomedical information
Computer Science Applications
Biotechnology
Computational Mathematics
Enzyme
Computational Theory and Mathematics
chemistry
Drug Design
State (computer science)
business
Subjects
Details
- ISSN :
- 13674811 and 13674803
- Volume :
- 23
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....7e3554c06d7ec7ecce8b414428c34165