Back

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

Zinski, J.; Chung, H.; Joshi, P.; Warrick, F.; Berg, B. D.; Glova, G.; McGrail, M. A.; Balciunas, D.; Friedberg, I.; Mullins, M. C.

2024-03-06 developmental biology
10.1101/2024.03.03.583232 bioRxiv
Show abstract

Epitope tagging is a valuable technique enabling the in vivo identification, tracking, and purification of proteins. We developed a tool, EpicTope, to facilitate this method by identifying amino acid positions most suitable for epitope insertion. Our method uses a scoring function that considers protein sequence secondary and tertiary structural features, solvent accessibility, and disordered binding regions to determine locations least disruptive to the proteins function. We validated our approach on the zebrafish Smad5 and Hdac1 proteins. We show that multiple predicted internally tagged Smad5 proteins rescue zebrafish smad5 mutant embryos, while the N- and C-terminal tagged variants do not, as predicted. Similarly, we found that optimally-predicted internal and C-terminal Hdac1 tags rescued hdac1 mutant embryos, while a less-optimal N-terminal tag did not. We further show that these functionally tagged Smad5 and Hdac1 proteins are accessible to antibodies in wholemount zebrafish embryo immunohistochemistry, by western blot, and by immunoprecipitation from embryo extracts. Our work demonstrates that EpicTope is an accessible and effective tool for designing epitope tag insertion sites.

Published in Development (predicted rank #1) · training set

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.