Probing ion channel functional architecture and domain recombination compatibility by massively parallel domain insertion profiling

Willow Coyote-Maestas, David M Nedrud, Antonio Suma, Yungui He, Kenneth A. Matreyek, Douglas M. Fowler, Vincenzo Carnevale, Chad L. Myers, Daniel Schmidt

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Protein domains are the basic units of protein structure and function. Comparative analysis of genomes and proteomes showed that domain recombination is a main driver of multidomain protein functional diversification and some of the constraining genomic mechanisms are known. Much less is known about biophysical mechanisms that determine whether protein domains can be combined into viable protein folds. Here, we use massively parallel insertional mutagenesis to determine compatibility of over 300,000 domain recombination variants of the Inward Rectifier K+ channel Kir2.1 with channel surface expression. Our data suggest that genomic and biophysical mechanisms acted in concert to favor gain of large, structured domain at protein termini during ion channel evolution. We use machine learning to build a quantitative biophysical model of domain compatibility in Kir2.1 that allows us to derive rudimentary rules for designing domain insertion variants that fold and traffic to the cell surface. Positional Kir2.1 responses to motif insertion clusters into distinct groups that correspond to contiguous structural regions of the channel with distinct biophysical properties tuned towards providing either folding stability or gating transitions. This suggests that insertional profiling is a high-throughput method to annotate function of ion channel structural regions.

Original languageEnglish (US)
Article number7114
JournalNature communications
Volume12
Issue number1
DOIs
StatePublished - Dec 2021

Bibliographical note

Funding Information:
We thank James Fraser, Gabriella Estevam, Margaret Titus, the Schmidt Lab, and Fraser lab for helpful feedback and discussion. We acknowledge support from the University of Minnesota Flow Cytometry Resource, in particular Rashi Arora, Therese Martin, and Jason Motl for providing flow cytometry technical support. Ben Hackel and Alexander Golinski for providing advice for calculating protein properties. Andrei Lupas and Vikram Alva kindly provided motif sequences from previous studies. Hellen Farrants and Kai Johnsson kindly provided DHFR and cpDHFR DNA for experiments. This work was supported by the National Institutes of Health (1R01GM136851 to D.S., 5R01GM131048 to V.C.) and a University of Minnesota Genome Center Illumina S2 grant. W.C.-M. is supported by a National Science Foundation Graduate Research Fellowship and a Howard Hughes Medical Institute Gilliam Fellowship for Advanced Study.

Publisher Copyright:
© 2021, The Author(s).

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

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