Single-photon smFRET: II. Application to continuous illumination.

IF 2.7 Q3 BIOPHYSICS Biophysical reports Pub Date : 2022-12-02 eCollection Date: 2023-03-08 DOI:10.1016/j.bpr.2022.100087
Ayush Saurabh, Matthew Safar, Mohamadreza Fazel, Ioannis Sgouralis, Steve Pressé
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Abstract

Here we adapt the Bayesian nonparametrics (BNP) framework presented in the first companion article to analyze kinetics from single-photon, single-molecule Förster resonance energy transfer (smFRET) traces generated under continuous illumination. Using our sampler, BNP-FRET, we learn the escape rates and the number of system states given a photon trace. We benchmark our method by analyzing a range of synthetic and experimental data. Particularly, we apply our method to simultaneously learn the number of system states and the corresponding kinetics for intrinsically disordered proteins using two-color FRET under varying chemical conditions. Moreover, using synthetic data, we show that our method can deduce the number of system states even when kinetics occur at timescales of interphoton intervals.

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单光子 smFRET:II.连续照明的应用。
在这里,我们调整了第一篇文章中介绍的贝叶斯非参数(BNP)框架,以分析在连续光照下产生的单光子、单分子佛斯特共振能量转移(smFRET)轨迹的动力学。利用我们的采样器 BNP-FRET,我们可以了解光子迹线的逸散率和系统状态数。我们通过分析一系列合成和实验数据,对我们的方法进行基准测试。特别是,我们将我们的方法应用于在不同化学条件下使用双色 FRET 同时学习系统状态的数量和内在无序蛋白质的相应动力学。此外,我们还利用合成数据表明,即使动力学发生的时间尺度为光子间间隔,我们的方法也能推导出系统状态的数量。
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来源期刊
Biophysical reports
Biophysical reports Biophysics
CiteScore
2.40
自引率
0.00%
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0
审稿时长
75 days
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