EpicTope: narrating protein sequence features to identify non-disruptive epitope tagging sites

EpicTope:叙述蛋白质序列特征以识别非破坏性表位标记位点

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作者:Joseph Zinski, Henri Chung, Parnal Joshi, Finn Warrick, Brian D Berg, Greg Glova, Maura McGrail, Darius Balciunas, Iddo Friedberg, Mary Mullins

Abstract

Epitope tagging is an invaluable technique enabling the identification, tracking, and purification of proteins in vivo. We developed a tool, EpicTope, to facilitate this method by identifying amino acid positions suitable for epitope insertion. Our method uses a scoring function that considers multiple protein sequence and structural features to determine locations least disruptive to the protein's function. We validated our approach on the zebrafish Smad5 protein, showing that multiple predicted internally tagged Smad5 proteins rescue zebrafish smad5 mutant embryos, while the N- and C-terminal tagged variants do not, also as predicted. We further show that the internally tagged Smad5 proteins are accessible to antibodies in wholemount zebrafish embryo immunohistochemistry and by western blot. Our work demonstrates that EpicTope is an accessible and effective tool for designing epitope tag insertion sites. EpicTope is available under a GPL-3 license from: https://github.com/FriedbergLab/Epictope.

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