Summary Quantitative interpretation of single-molecule FRET experiments requires a model of the dye dynamics to link experimental energy transfer efficiencies to distances between atom positions. We have developed FRETraj, a Python module to predict FRET distributions based on accessible-contact volumes (ACV) and simulated photon statistics. FRETraj helps to identify optimal fluorophore positions on a biomolecule of interest by rapidly evaluating donor-acceptor distances. FRETraj is scalable and fully integrated into PyMOL and the Jupyter ecosystem. Here, we describe the conformational dynamics of a DNA hairpin by computing multiple ACVs along a molecular dynamics trajectory and compare the predicted FRET distribution with single-molecule experiments. FRET-assisted modeling will accelerate the analysis of structural ensembles in particular dynamic, non-coding RNAs and transient protein-nucleic acid complexes. Availability and implementation FRETraj is implemented as a cross-platform Python package available under the GPL-3.0 on Github (https://github.com/RNA-FRETools/fretraj) and is documented at https://RNA-FRETools.github.io/fretraj. Supplementary information Supplementary data are available at Bioinformatics online.

中文翻译：

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FRETraj：将单分子光谱与分子动力学相结合

总结 单分子 FRET 实验的定量解释需要染料动力学模型将实验能量转移效率与原子位置之间的距离联系起来。我们开发了 FRETraj，这是一个 Python 模块，用于根据可访问接触体积 (ACV) 和模拟光子统计预测 FRET 分布。FRETraj 通过快速评估供体-受体距离，帮助确定感兴趣的生物分子上的最佳荧光团位置。FRETraj 可扩展并完全集成到 PyMOL 和 Jupyter 生态系统中。在这里，我们通过沿分子动力学轨迹计算多个 ACV 来描述 DNA 发夹的构象动力学，并将预测的 FRET 分布与单分子实验进行比较。FRET 辅助建模将加速结构整体的分析，特别是动态的，非编码 RNA 和瞬时蛋白-核酸复合物。可用性和实施​​ FRETraj 作为跨平台 Python 包实施，在 Github (https://github.com/RNA-FRETools/fretraj) 上以 GPL-3.0 提供，并记录在 https://RNA-FRETools.github 上。 io/fretraj。补充信息 补充数据可在 Bioinformatics 在线获取。