4.7 Article

Use of fluorescence-detected sedimentation velocity to study high-affinity protein interactions

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NATURE PROTOCOLS
卷 12, 期 9, 页码 1777-1791

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NATURE PUBLISHING GROUP
DOI: 10.1038/nprot.2017.064

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  1. Intramural Research Program of the National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health

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Sedimentation velocity (SV) analytical ultracentrifugation (AUC) is a classic technique for the real-time observation of free macromolecular migration in solution driven by centrifugal force. This enables the analysis of macromolecular mass, shape, size distribution, and interactions. Although traditionally limited to determination of the sedimentation coefficient and binding affinity of proteins in the micromolar range, the implementation of modern detection and data analysis techniques has resulted in marked improvements in detection sensitivity and size resolution during the past decades. Fluorescence optical detection now permits the detection of recombinant proteins with fluorescence excitation at 488 or 561 nm at low picomolar concentrations, allowing for the study of high-affinity protein self-association and hetero-association. Compared with other popular techniques for measuring high-affinity protein-protein interactions, such as biosensing or calorimetry, the high size resolution of complexes at picomolar concentrations obtained with SV offers a distinct advantage in sensitivity and flexibility of the application. Here, we present a basic protocol for carrying out fluorescence-detected SV experiments and the determination of the size distribution and affinity of protein-antibody complexes with picomolar K-D values. Using an EGFP-nanobody interaction as a model, this protocol describes sample preparation, ultracentrifugation, data acquisition, and data analysis. A variation of the protocol applying traditional absorbance or an interference optical system can be used for protein-protein interactions in the micromolar K-D value range. Sedimentation experiments typically take similar to 3 h of preparation and 6-12 h of run time, followed by data analysis (typically taking 1-3 h).

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