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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273215/ https://www.ncbi.nlm.nih.gov/pubmed/35639599 http://dx.doi.org/10.7554/eLife.76903 |
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author | Coyote-Maestas, Willow Nedrud, David He, Yungui Schmidt, Daniel |
author_facet | Coyote-Maestas, Willow Nedrud, David He, Yungui Schmidt, Daniel |
author_sort | Coyote-Maestas, Willow |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9273215 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-92732152022-07-12 Determinants of trafficking, conduction, and disease within a K(+) channel revealed through multiparametric deep mutational scanning Coyote-Maestas, Willow Nedrud, David He, Yungui Schmidt, Daniel eLife Genetics and Genomics 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. eLife Sciences Publications, Ltd 2022-05-31 /pmc/articles/PMC9273215/ /pubmed/35639599 http://dx.doi.org/10.7554/eLife.76903 Text en © 2022, Coyote-Maestas et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Genetics and Genomics Coyote-Maestas, Willow Nedrud, David He, Yungui Schmidt, Daniel Determinants of trafficking, conduction, and disease within a K(+) channel revealed through multiparametric deep mutational scanning |
title | Determinants of trafficking, conduction, and disease within a K(+) channel revealed through multiparametric deep mutational scanning |
title_full | Determinants of trafficking, conduction, and disease within a K(+) channel revealed through multiparametric deep mutational scanning |
title_fullStr | Determinants of trafficking, conduction, and disease within a K(+) channel revealed through multiparametric deep mutational scanning |
title_full_unstemmed | Determinants of trafficking, conduction, and disease within a K(+) channel revealed through multiparametric deep mutational scanning |
title_short | Determinants of trafficking, conduction, and disease within a K(+) channel revealed through multiparametric deep mutational scanning |
title_sort | determinants of trafficking, conduction, and disease within a k(+) channel revealed through multiparametric deep mutational scanning |
topic | Genetics and Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273215/ https://www.ncbi.nlm.nih.gov/pubmed/35639599 http://dx.doi.org/10.7554/eLife.76903 |
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