Unknown

Dataset Information

0

Integration and global analysis of isothermal titration calorimetry data for studying macromolecular interactions.


ABSTRACT: Isothermal titration calorimetry (ITC) is a powerful and widely used method to measure the energetics of macromolecular interactions by recording a thermogram of differential heating power during a titration. However, traditional ITC analysis is limited by stochastic thermogram noise and by the limited information content of a single titration experiment. Here we present a protocol for bias-free thermogram integration based on automated shape analysis of the injection peaks, followed by combination of isotherms from different calorimetric titration experiments into a global analysis, statistical analysis of binding parameters and graphical presentation of the results. This is performed using the integrated public-domain software packages NITPIC, SEDPHAT and GUSSI. The recently developed low-noise thermogram integration approach and global analysis allow for more precise parameter estimates and more reliable quantification of multisite and multicomponent cooperative and competitive interactions. Titration experiments typically take 1-2.5 h each, and global analysis usually takes 10-20 min.

SUBMITTER: Brautigam CA 

PROVIDER: S-EPMC7466939 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

altmetric image

Publications

Integration and global analysis of isothermal titration calorimetry data for studying macromolecular interactions.

Brautigam Chad A CA   Zhao Huaying H   Vargas Carolyn C   Keller Sandro S   Schuck Peter P  

Nature protocols 20160407 5


Isothermal titration calorimetry (ITC) is a powerful and widely used method to measure the energetics of macromolecular interactions by recording a thermogram of differential heating power during a titration. However, traditional ITC analysis is limited by stochastic thermogram noise and by the limited information content of a single titration experiment. Here we present a protocol for bias-free thermogram integration based on automated shape analysis of the injection peaks, followed by combinat  ...[more]

Similar Datasets

| S-EPMC3388511 | biostudies-literature
| S-EPMC5179259 | biostudies-literature
| S-EPMC7324066 | biostudies-literature
| S-EPMC2812830 | biostudies-literature
| S-EPMC3526666 | biostudies-literature
| S-EPMC6136728 | biostudies-literature
| S-EPMC3389189 | biostudies-literature
| S-EPMC1544317 | biostudies-literature
| S-EPMC5589412 | biostudies-literature
| S-EPMC4669061 | biostudies-literature