PMID- 22052503 OWN - NLM STAT- MEDLINE DCOM- 20120517 LR - 20111104 IS - 1940-6029 (Electronic) IS - 1064-3745 (Linking) VI - 796 DP - 2012 TI - The advantage of global fitting of data involving complex linked reactions. PG - 399-421 LID - 10.1007/978-1-61779-334-9_22 [doi] AB - 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. FAU - Herman, Petr AU - Herman P AD - Faculty of Mathematics and Physics, Institute of Physics, Charles University, Prague, Czech Republic. FAU - Lee, J Ching AU - Lee JC LA - eng GR - GM 775551/GM/NIGMS NIH HHS/United States PT - Journal Article PT - Research Support, N.I.H., Extramural PT - Research Support, Non-U.S. Gov't PL - United States TA - Methods Mol Biol JT - Methods in molecular biology (Clifton, N.J.) JID - 9214969 RN - EC 2.7.1.40 (Pyruvate Kinase) SB - IM MH - Animals MH - Calorimetry MH - Least-Squares Analysis MH - Monte Carlo Method MH - Pyruvate Kinase/chemistry/*metabolism MH - Rabbits EDAT- 2011/11/05 06:00 MHDA- 2012/05/18 06:00 CRDT- 2011/11/05 06:00 PHST- 2011/11/05 06:00 [entrez] PHST- 2011/11/05 06:00 [pubmed] PHST- 2012/05/18 06:00 [medline] AID - 10.1007/978-1-61779-334-9_22 [doi] PST - ppublish SO - Methods Mol Biol. 2012;796:399-421. doi: 10.1007/978-1-61779-334-9_22.