Non-linear optimization of biochemical pathways: applications to metabolic engineering and parameter estimation.

TLDR

Biochemical kinetic simulations enable consistency checks with experimental data, answer hypothetical questions, and explore model behaviors. The study proposes a generic method that integrates numerical optimization with biochemical kinetic simulations for designing improved metabolic pathways and estimating pathway parameters. The approach couples numerical optimization to biochemical kinetic simulations to estimate parameters from measured variables. The authors evaluated optimization methods for global optimum discovery, recommend a diverse suite in simulation software, and implemented the strategy in Gepasi with illustrative examples. Gepasi 3.20, incorporating the described methodology, is available online at http://gepasi.dbs.aber.ac.uk/softw/Gepasi; contact [e-mail].

Abstract

Abstract MOTIVATION: The simulation of biochemical kinetic systems is a powerful approach that can be used for: (i) checking the consistency of a postulated model with a set of experimental measurements, (ii) answering 'what if?' questions and (iii) exploring possible behaviours of a model. Here we describe a generic approach to combine numerical optimization methods with biochemical kinetic simulations, which is suitable for use in the rational design of improved metabolic pathways with industrial significance (metabolic engineering) and for solving the inverse problem of metabolic pathways, i.e. the estimation of parameters from measured variables. RESULTS: We discuss the suitability of various optimization methods, focusing especially on their ability or otherwise to find global optima. We recommend that a suite of diverse optimization methods should be available in simulation software as no single one performs best for all problems. We describe how we have implemented such a simulation-optimization strategy in the biochemical kinetics simulator Gepasi and present examples of its application. AVAILABILITY: The new version of Gepasi (3.20), incorporating the methodology described here, is available on the Internet at http://gepasi.dbs.aber.ac.uk/softw/Gepasi. html. CONTACT: [e-mail]