Simulation of FRET dyes allows quantitative comparison against experimental data
Author(s) -
Ines Reinartz,
Claude Sinner,
Daniel Nettels,
Brigitte Stucki-Buchli,
Florian Stockmar,
Paweł T. Panek,
Christoph R. Jacob,
G. Ulrich Nienhaus,
Benjamin Schuler,
Alexander Schug
Publication year - 2018
Publication title -
the journal of chemical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.071
H-Index - 357
eISSN - 1089-7690
pISSN - 0021-9606
DOI - 10.1063/1.5010434
Subject(s) - förster resonance energy transfer , complement (music) , flexibility (engineering) , biological system , molecular dynamics , folding (dsp implementation) , computer science , single molecule fret , function (biology) , molecular biophysics , statistical physics , chemical physics , nanotechnology , chemistry , physics , computational chemistry , materials science , fluorescence , biochemistry , statistics , mathematics , quantum mechanics , evolutionary biology , complementation , biology , electrical engineering , gene , phenotype , engineering
Fully understanding biomolecular function requires detailed insight into the systems' structural dynamics. Powerful experimental techniques such as single molecule Förster Resonance Energy Transfer (FRET) provide access to such dynamic information yet have to be carefully interpreted. Molecular simulations can complement these experiments but typically face limits in accessing slow time scales and large or unstructured systems. Here, we introduce a coarse-grained simulation technique that tackles these challenges. While requiring only few parameters, we maintain full protein flexibility and include all heavy atoms of proteins, linkers, and dyes. We are able to sufficiently reduce computational demands to simulate large or heterogeneous structural dynamics and ensembles on slow time scales found in, e.g., protein folding. The simulations allow for calculating FRET efficiencies which quantitatively agree with experimentally determined values. By providing atomically resolved trajectories, this work supports the planning and microscopic interpretation of experiments. Overall, these results highlight how simulations and experiments can complement each other leading to new insights into biomolecular dynamics and function.
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