Toward whole cell modeling and simulation: comprehensive functional genomics through the constraint-based approach.
The increasing availability of various system-level, or so-called 'omics', datasets, in concert with existing data from the primary research literature, is facilitating the development of genome-scale metabolic models for many organisms. By incorporating the metabolic reaction stoichiometry as well as other physicochemical properties into systemic network reconstructions, these models account for the constraints that restrict an organism's phenotypic behavior. Accordingly, unlike many contemporary modeling strategies, this constraint-based modeling approach does not attempt to predict network behavior exactly; rather, it seeks to clearly distinguish those network states that a system can achieve from those that it cannot. A variety of analytical tools have been designed and developed to probe these models, thus enabling studies that investigate the metabolic capabilities of a number of organisms, that generate and test experimental hypotheses, and that predict accurately metabolic phenotypes and evolutionary outcomes. This chapter introduces the concepts that underlie the constraint-based modeling approach, and describes several of its applications with an emphasis on those potentially relevant to the drug development field. In addition, while this chapter focuses on the primary application of the constraint-based approach to date, namely in modeling metabolic networks, the latter sections of the chapter discuss its relatively recent application to modeling other cellular systems. Finally, the chapter concludes with an assessment of future directions focusing on the efforts that will be required to utilize the constraint-based approach in generating a holistic model of a viable organism.
Joyce
Andrew R
AR
Bioinformatics Program, University of California, San Diego, La Jolla, California, USA. ajoyce@ucsd.edu
Palsson
Bernhard O
BO
D000818:Animals; D003198:Computer Simulation; D003625:Data Collection; D015195:Drug Design; D023281:Genomics; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D015398:Signal Transduction; D014158:Transcription, Genetic