Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins

Ganesh Agam, Christian Gebhardt, Milana Popara, Rebecca Mächtel, Julian Folz, Benjamin Ambrose, Neharika Chamachi, Sang Yoon Chung, Timothy D. Craggs, Marijn de Boer, Dina Grohmann, Taekjip Ha, Andreas Hartmann, Jelle Hendrix, Verena Hirschfeld, Christian G. Hübner, Thorsten Hugel, Dominik Kammerer, Hyun Seo Kang, Achillefs N. KapanidisGeorg Krainer, Kevin Kramm, Edward A. Lemke, Eitan Lerner, Emmanuel Margeat, Kirsten Martens, Jens Michaelis, Jaba Mitra, Gabriel G. Moya Muñoz, Robert B. Quast, Nicole C. Robb, Michael Sattler, Michael Schlierf, Jonathan Schneider, Tim Schröder, Anna Sefer, Piau Siong Tan, Johann Thurn, Philip Tinnefeld, John van Noort, Shimon Weiss, Nicolas Wendler, Niels Zijlstra, Anders Barth, Claus A.M. Seidel, Don C. Lamb, Thorben Cordes

Research output: Contribution to journalArticlepeer-review

Abstract

Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology.

Original languageEnglish
Pages (from-to)523-535
Number of pages13
JournalNature Methods
Volume20
Issue number4
Early online date27 Mar 2023
DOIs
StatePublished - Apr 2023

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Biochemistry
  • Biotechnology
  • Cell Biology

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