title: The advantage of global fitting of data involving complex linked reactions.
abstract: In this chapter, we demonstrate the advantage of the simultaneous multicurve nonlinear least-squares analysis over that of the conventional single-curve analysis. Fitting results are subjected to thorough Monte Carlo analysis for rigorous assessment of confidence intervals and parameter correlations. The comparison is performed on a practical example of simulated steady-state reaction kinetics complemented with isothermal calorimetry (ITC) data resembling allosteric behavior of rabbit muscle pyruvate kinase (RMPK). Global analysis improves accuracy and confidence limits of model parameters. Cross-correlation between parameters is also reduced with accompanying enhancement of the model-testing power. This becomes especially important for validation of models with "difficult" highly cross-correlated parameters. We show how proper experimental design and critical evaluation of data can improve the chance of differentiating models.
authors: Faculty of Mathematics and Physics, Institute of Physics, Charles University, Prague, Czech Republic.
authors: Petr
authors: P
authors: Herman
authors: J Ching
authors: JC
authors: Lee
mesh_terms: D000818:Animals; D002151:Calorimetry; D016018:Least-Squares Analysis; D009010:Monte Carlo Method; D011770:Pyruvate Kinase / Q000737:chemistry / Q000378:metabolism*; D011817:Rabbits
chemical_list: D011770:Pyruvate Kinase