Article ID: | iaor2009480 |
Country: | United Kingdom |
Volume: | 23 |
Start Page Number: | 2281 |
End Page Number: | 2289 |
Publication Date: | Jan 2007 |
Journal: | Bioinformatics |
Authors: | Torres Nstor V., Vera Julio, Curto Raul, Cascante Marta |
Keywords: | programming: mathematical |
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.