TY - JOUR
T1 - High-precision, automated integration of multiple isothermal titration calorimetric thermograms
T2 - New features of NITPIC
AU - Scheuermann, Thomas H.
AU - Brautigam, Chad A
N1 - Funding Information:
The authors wish to thank Yogarany Chelliah and Drs. Shih-Chia Tso, Ranjit Deka, Kevin Gardner, David Chuang, Michael Norgard, and Johann Deisenhofer for providing proteins and ligands used in this study. The Norgard Lab’s work on Tp0655 was supported by NIH Grant AI56305 (to Norgard), and the Chuang Lab’s research on PDK2 was supported by NIH Grant DK62306 (to Chuang). The HIF2α work in the Gardner Lab was supported by Grants RP100846 and RP130513 from the Cancer Prevention Research Institute of Texas . The synapsin III-C studies were supported by the Howard Hughes Medical Institute, when Deisenhofer was an investigator there. We thank Drs. Verna Frasca and Ivana Simonovic for acquiring some thermograms used in this work.
Publisher Copyright:
© 2014 Elsevier Inc.
PY - 2015/4/1
Y1 - 2015/4/1
N2 - Isothermal titration calorimetry (ITC) has become a standard and widely available tool to measure the thermodynamic parameters of macromolecular associations. Modern applications of the method, including global analysis and drug screening, require the acquisition of multiple sets of data; sometimes these data sets number in the hundreds. Therefore, there is a need for quick, precise, and automated means to process the data, particularly at the first step of data analysis, which is commonly the integration of the raw data to yield an interpretable isotherm. Herein, we describe enhancements to an algorithm that previously has been shown to provide an automated, unbiased, and high-precision means to integrate ITC data. These improvements allow for the speedy and precise serial integration of an unlimited number of ITC data sets, and they have been implemented in the freeware program NITPIC, version 1.1.0. We present a comprehensive comparison of the performance of this software against an older version of NITPIC and a current version of Origin, which is commonly used for integration. The new methods recapitulate the excellent performance of the previous versions of NITPIC while speeding it up substantially, and their precision is significantly better than that of Origin. This new version of NITPIC is therefore well suited to the serial integration of many ITC data sets.
AB - Isothermal titration calorimetry (ITC) has become a standard and widely available tool to measure the thermodynamic parameters of macromolecular associations. Modern applications of the method, including global analysis and drug screening, require the acquisition of multiple sets of data; sometimes these data sets number in the hundreds. Therefore, there is a need for quick, precise, and automated means to process the data, particularly at the first step of data analysis, which is commonly the integration of the raw data to yield an interpretable isotherm. Herein, we describe enhancements to an algorithm that previously has been shown to provide an automated, unbiased, and high-precision means to integrate ITC data. These improvements allow for the speedy and precise serial integration of an unlimited number of ITC data sets, and they have been implemented in the freeware program NITPIC, version 1.1.0. We present a comprehensive comparison of the performance of this software against an older version of NITPIC and a current version of Origin, which is commonly used for integration. The new methods recapitulate the excellent performance of the previous versions of NITPIC while speeding it up substantially, and their precision is significantly better than that of Origin. This new version of NITPIC is therefore well suited to the serial integration of many ITC data sets.
KW - Automated processing
KW - Isothermal titration calorimetry
KW - Serial integration
KW - Singular value decomposition
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U2 - 10.1016/j.ymeth.2014.11.024
DO - 10.1016/j.ymeth.2014.11.024
M3 - Article
C2 - 25524420
AN - SCOPUS:84925445801
SN - 0076-6879
VL - 76
SP - 87
EP - 98
JO - Methods in Enzymology
JF - Methods in Enzymology
ER -