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Testing the use of molecular dynamics to simulate fluorophore motions and FRET

荧光团 费斯特共振能量转移 分子动力学 动力学(音乐) 化学物理 统计物理学 化学 纳米技术 生物系统 荧光 材料科学 物理 计算化学 光学 生物 声学
作者
Evelyne Deplazes,Dylan Jayatilaka,Ben Corry
出处
期刊:Physical Chemistry Chemical Physics [The Royal Society of Chemistry]
卷期号:13 (23): 11045-11045 被引量:20
标识
DOI:10.1039/c1cp20447e
摘要

Fluorescence resonance energy transfer (FRET) is commonly used to determine the proximity of fluorophores, but usually many assumptions are required to gain a quantitative relationship between the likelihood of energy transfer and fluorophore separation. Molecular Dynamics (MD) simulations provide one way of checking these assumptions, but before using simulations to study complex systems it is important to make sure that they can correctly model the motions of fluorophores and the likely FRET efficiency in a simple system. Here we simulate a well characterised situation of independent fluorophores in solution so that we can compare the predictions with expected values. Our simulations reproduce the experimental fluorescence anisotropy of Alexafluor488 and predict that of AlexaFluor568. At the ensemble level we are able to reproduce the expected isotropic and dynamic motion of the fluorophores as well as the FRET efficiency of the system. At the level of single donor-acceptor pairs, however, very long simulations are required to adequately sample the translational motion of the fluorophores and more surprisingly also the rotational motion. Our studies demonstrate how MD simulations can be used in more complex systems to check if the dynamic orientation averaging regime applies, if the fluorophores have isotropic orientational motion, to calculate the likely values of the orientation factor κ(2) and to determine the FRET efficiency of the system in both dynamic and static orientational averaging regimes. We also show that it is possible in some situations to create system specific relationships between FRET efficiency and fluorophore separation that can be used to interpret experimental data and find any correlations between κ(2) and separation that may influence distance measurements.

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