Published November 23, 2020 | Version v1
Dataset Open

Cross-validation of distance measurements in proteins by PELDOR/DEER and single-molecule FRET

  • 1. Institute of Structural Biology, University of Bonn, Bonn, Germany
  • 2. Physical and Synthetic Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany
  • 3. Department of Biology (Area 10), University of York, York, United Kingdom

Description

Pulsed electron-electron double resonance spectroscopy (PELDOR/DEER) and single-molecule Förster resonance energy transfer spectroscopy (smFRET) are frequently used to determine conformational changes, structural heterogeneity and inter probe distances in biological macromolecules. They provide qualitative information that facilitates mechanistic understanding of biochemical processes and quantitative data for structural modeling. To provide a comprehensive comparison of the accuracy of PELDOR/DEER and smFRET, we use a library of double cysteine variants of four proteins that undergo large-scale conformational changes upon ligand binding. With either method, we use established standard experimental protocols and data analysis routines to determine inter-probe distances in the presence and absence of ligands. The results are compared to distance predictions from structural models. Despite an overall satisfying and similar distance accuracy, some inconsistencies are identified, which we attribute to the use of cryoprotectants for PELDOR/DEER and label-protein interactions for smFRET. This large-scale cross-validation of PELDOR/DEER and smFRET highlights the strengths, weaknesses, and synergies of these two important and complementary tools in integrative structural biology.

Notes

Paper is available as a pre-print: https://doi.org/10.1101/2020.11.23.394080 and will be published in Nature Communications under manuscript number NCOMMS-20-47944C.

Files

Figure3.zip

Files (5.7 GB)

Name Size Download all
md5:50970d59ec41b742729ec2d585593743
1.5 GB Preview Download
md5:111d9a5b1e4fc6d331257fb6dfe0b8df
1.7 GB Preview Download
md5:5066716852aa42f8828cde9a591cd49d
1.8 GB Preview Download
md5:3984fcac57d6e3058023d70b5619ca25
707.3 MB Preview Download