EpicTope: Narrating Protein Sequence Features to Identify Non-disruptive Epitope Tagging Sites

Overview

Journal bioRxiv

Date 2024 Apr 1

PMID 38559275

Authors

Joseph Zinski

Henri Chung

Parnal Joshi

Finn Warrick

Brian D Berg

Greg Glova

Maura McGrail

Darius Balciunas

Iddo Friedberg

Mary Mullins

Affiliations

Soon will be listed here.

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 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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