Literature DB >> 25484338

Fitting two- and three-site binding models to isothermal titration calorimetric data.

Chad A Brautigam1.   

Abstract

As isothermal titration calorimetry (ITC) gains popularity for the characterization of enthalpies and equilibrium association constants of simple 1:1 biomolecular interactions, its use for more complex systems is growing. The method is increasingly used to study interactions in which a single binding partner (molecule "A") interacts with multiple copies of a second partner ("B"); thus examinations of ABB and ABBB interactions are not uncommon. The structure of ITC data (commonly formatted as isotherms) has a strong bearing on the ability of the researcher to extract the necessary parameters from them. Usually, only 10-30 injections are recorded in a single ITC experiment. Even if replicates are performed, the data must support the extraction of up to twelve parameters from an ABBB system. Further, the refinement of some of the parameters is largely driven by only a subset of the data. The ability of ITC data to guide the deterministic estimation of these parameters may therefore be questioned. This work assesses the ability of both empirical and simulated ITC data of ABB and ABBB systems to support the simultaneous estimation of the desired thermodynamic parameters. The results demonstrate that multiphasic isotherms tend to (but do not always) support the estimation of multiple parameters. On the other hand, uniphasic data obtained from multi-site binding systems are more problematic. In all cases, a thorough exploration of how precisely the estimated parameters are specified by the data is justified.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Analytical ultracentrifugation; Isotherm analysis; Isothermal titration calorimetry; Three-site binding; Treponemal lipoproteins; Two-site binding

Mesh:

Substances:

Year:  2014        PMID: 25484338      PMCID: PMC4591754          DOI: 10.1016/j.ymeth.2014.11.018

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


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