Journal Article FZJ-2018-00908

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Simulation of FRET dyes allows quantitative comparison against experimental data

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2018
American Institute of Physics Melville, NY

The journal of chemical physics 148(12), 123321 - () [10.1063/1.5010434]

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Abstract: 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.

Classification:

Contributing Institute(s):
  1. Jülich Supercomputing Center (JSC)
  2. John von Neumann - Institut für Computing (NIC)
Research Program(s):
  1. 511 - Computational Science and Mathematical Methods (POF3-511) (POF3-511)

Appears in the scientific report 2018
Database coverage:
Medline ; Embargoed OpenAccess ; Current Contents - Physical, Chemical and Earth Sciences ; Ebsco Academic Search ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection
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NIC

 Datensatz erzeugt am 2018-01-29, letzte Änderung am 2021-01-29


Published on 2018-01-09. Available in OpenAccess from 2019-01-09.:
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