Driving integrative structural modeling with serial capture affinity purification.
In: Proceedings of the National Academy of Sciences of the United States of America, Jg. 117 (2020-12-15), Heft 50, S. 31861-31870
Online
academicJournal
Zugriff:
Streamlined characterization of protein complexes remains a challenge for the study of protein interaction networks. Here we describe serial capture affinity purification (SCAP), in which two separate proteins are tagged with either the HaloTag or the SNAP-tag, permitting a multistep affinity enrichment of specific protein complexes. The multifunctional capabilities of this protein-tagging system also permit in vivo validation of interactions using acceptor photobleaching Förster resonance energy transfer and fluorescence cross-correlation spectroscopy quantitative imaging. By coupling SCAP to cross-linking mass spectrometry, an integrative structural model of the complex of interest can be generated. We demonstrate this approach using the Spindlin1 and SPINDOC protein complex, culminating in a structural model with two SPINDOC molecules docked on one SPIN1 molecule. In this model, SPINDOC interacts with the SPIN1 interface previously shown to bind a lysine and arginine methylated sequence of histone H3. Our approach combines serial affinity purification, live cell imaging, and cross-linking mass spectrometry to build integrative structural models of protein complexes.
Competing Interests: The authors declare no competing interest.
(Copyright © 2020 the Author(s). Published by PNAS.)
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Driving integrative structural modeling with serial capture affinity purification.
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Autor/in / Beteiligte Person: | Liu, X ; Zhang, Y ; Wen, Z ; Hao, Y ; Banks, CAS ; Lange, JJ ; Slaughter, BD ; Unruh, JR ; Florens, L ; Abmayr, SM ; Workman, JL ; Washburn, MP |
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Zeitschrift: | Proceedings of the National Academy of Sciences of the United States of America, Jg. 117 (2020-12-15), Heft 50, S. 31861-31870 |
Veröffentlichung: | Washington, DC : National Academy of Sciences, 2020 |
Medientyp: | academicJournal |
ISSN: | 1091-6490 (electronic) |
DOI: | 10.1073/pnas.2007931117 |
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