Dataset Information

Evaluation and Minimization of Uncertainty in ITC Binding Measurements: Heat Error, Concentration Error, Saturation, and Stoichiometry.

ABSTRACT: Isothermal titration calorimetry (ITC) is uniquely useful for characterizing binding thermodynamics, because it straightforwardly provides both the binding enthalpy and free energy. However, the precision of the results depends on the experimental setup and how thermodynamic results are obtained from the raw data.Experiments and Monte Carlo analysis are used to study how uncertainties in injection heat and concentration propagate to binding enthalpies in various scenarios. We identify regimes in which it is preferable to fix the stoichiometry parameter, N, and evaluate the reliability of uncertainties provided by the least squares method.The noise in the injection heat is mainly proportional in character, with ~1% and ~3% uncertainty at 27C and 65C, respectively; concentration errors are ~1%. Simulations of experiments based on these uncertainties delineate how experimental design and curve fitting methods influence the uncertainty in the final results.In most cases, experimental uncertainty is minimized by using more injections and by fixing N at its known value. With appropriate technique, the uncertainty in measured binding enthalpies can be kept below ~2% under many conditions, including low C values.We quantify uncertainties in ITC data due to heat and concentration error, and identify practices to minimize these uncertainties. The resulting guidelines are important when ITC data are used quantitatively, such as to test computer simulations of binding. Reproducibility and further study are supported by free distribution of the new software developed here.

SUBMITTER: Kantonen SA

PROVIDER: S-EPMC5195854 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evaluation and Minimization of Uncertainty in ITC Binding Measurements: Heat Error, Concentration Error, Saturation, and Stoichiometry.

Kantonen Samuel A SA Henriksen Niel M NM Gilson Michael K MK

Biochimica et biophysica acta. General subjects 20160915 2

<h4>Background</h4>Isothermal titration calorimetry (ITC) is uniquely useful for characterizing binding thermodynamics, because it straightforwardly provides both the binding enthalpy and free energy. However, the precision of the results depends on the experimental setup and how thermodynamic results are obtained from the raw data.<h4>Methods</h4>Experiments and Monte Carlo analysis are used to study how uncertainties in injection heat and concentration propagate to binding enthalpies in variou ...[more]

PMID: 27599357

Similar Datasets

Project description:Mobile mapping of air pollution has the potential to provide pollutant concentration data at unprecedented spatial scales. Characterizing instrument performance in the mobile context is challenging, but necessary to analyze and interpret the resulting data. We used robust statistical methods to assess mobile platform performance using data collected with the Aclima Inc. mobile air pollution measurement and data acquisition platform installed on three Google Street View cars. They were driven throughout the greater Denver metropolitan area between July 25, 2014 and August 14, 2014, measuring ozone (O3), nitrogen dioxide (NO2), nitric oxide (NO), black carbon (BC), and size-resolve particle number counts (PN) between 0.3 μm and 5.0 μm diameter. August 6, 2014 was dedicated to parked and moving collocations among the three cars, allowing an assessment of measurement precision and bias. We used the median absolute deviation (MAD) to estimate instrument precision from outdoor, parked collocations. Bias was assessed by measurements obtained from parked cars using the standard deviation of median values over a collocated measurement period, as well as by Passing-Bablok regression statistics while the cars were moving and collocated. For the moving collocation periods, we compared the distribution of 1-σ standard deviations among the 3 cars to the estimated distribution assuming only measurement uncertainty (precision and bias). The distribution of mobile measurements agreed well with the theoretical uncertainty distribution at the lower end of the distribution for O3, NO2, and PN. We assert that the difference between the actual and theoretical distributions is due to real spatial variability between pollutants. The agreement between the parked car estimates of uncertainty and that measured during the mobile collocations (at the lower quantiles) provides evidence that on-road collocation while parked could be sufficient for estimating measurement uncertainties of a mobile platform, even when extended to the moving environment.

Dataset Information

Evaluation and Minimization of Uncertainty in ITC Binding Measurements: Heat Error, Concentration Error, Saturation, and Stoichiometry.

Publications

Evaluation and Minimization of Uncertainty in ITC Binding Measurements: Heat Error, Concentration Error, Saturation, and Stoichiometry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets