Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning

A long-standing goal in protein science and clinical genetics is to develop quantitative models of sequence, structure, and function relationships to understand how mutations cause disease. Deep mutational scanning (DMS) is a promising strategy to map how amino acids contribute to protein structure and function and to advance clinical variant interpretation. Here, we introduce 7429 single-residue missense mutations into the inward rectifier K+ channel Kir2.1 and determine how this affects folding, assembly, and trafficking, as well as regulation by allosteric ligands and ion conduction. Our data provide high-resolution information on a cotranslationally folded biogenic unit, trafficking and quality control signals, and segregated roles of different structural elements in fold stability and function. We show that Kir2.1 surface trafficking mutants are underrepresented in variant effect databases, which has implications for clinical practice. By comparing fitness scores with expert-reviewed variant effects, we can predict the pathogenicity of 'variants of unknown significance' and disease mechanisms of known pathogenic mutations. Our study in Kir2.1 provides a blueprint for how multiparametric DMS can help us understand the mechanistic basis of genetic disorders and the structure-function relationships of proteins.

Automated summary

This study introduces a large number of single-residue missense mutations into the K+ channel Kir2.1 to investigate their effects on protein folding, assembly, trafficking, and function. The findings suggest that surface trafficking mutants of Kir2.1 are underrepresented in variant effect databases, which has implications for clinical practice. By comparing fitness scores with expert-reviewed variant effects, the pathogenicity of unknown variants and disease mechanisms of known pathogenic mutations can be predicted. This study provides important insights into understanding the mechanistic basis of genetic disorders and the structure-function relationships of proteins.