Structural knowledge of protein assemblies in their physiological environment is paramount to understand cellular functions at the molecular level. Protein interactions from Imaging Complexes after Translocation (PICT) is a live-cell imaging technique for the structural characterization of macromolecular assemblies in living cells. PICT relies on the measurement of the separation between labelled molecules using fluorescence microscopy and cell engineering. Unfortunately, the required computational tools to extract molecular distances involve a variety of sophisticated software programs that challenge reproducibility and limit their implementation to highly specialized researchers. Here we introduce PyF2F, a Python-based software that provides a workflow for measuring molecular distances from PICT data, with minimal user programming expertise. We used a published dataset to validate PyF2F's performance.
PyF2F: a robust and simplified fluorophore-to-fluorophore distance measurement tool for Protein interactions from Imaging Complexes after Translocation experiments.
阅读:3
作者:Hernandez Altair C, Ortiz Sebastian, Betancur Laura I, DojÄiloviÄ Radovan, Picco Andrea, Kaksonen Marko, Oliva Baldo, Gallego Oriol
| 期刊: | NAR Genomics and Bioinformatics | 影响因子: | 2.800 |
| 时间: | 2024 | 起止号: | 2024 Mar 12; 6(1):lqae027 |
| doi: | 10.1093/nargab/lqae027 | ||
特别声明
1、本文转载旨在传播信息,不代表本网站观点,亦不对其内容的真实性承担责任。
2、其他媒体、网站或个人若从本网站转载使用,必须保留本网站注明的“来源”,并自行承担包括版权在内的相关法律责任。
3、如作者不希望本文被转载,或需洽谈转载稿费等事宜,请及时与本网站联系。
4、此外,如需投稿,也可通过邮箱info@biocloudy.com与我们取得联系。
