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Interpreting the molecular mechanisms of disease variants in human transmembrane proteins.
Tiemann, Johanna Katarina Sofie; Zschach, Henrike; Lindorff-Larsen, Kresten; Stein, Amelie.
Affiliation
  • Tiemann JKS; Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark; Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
  • Zschach H; Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
  • Lindorff-Larsen K; Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark. Electronic address: lindorff@bio.ku.dk.
  • Stein A; Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark. Electronic address: amelie.stein@bio.ku.dk.
Biophys J ; 122(11): 2176-2191, 2023 06 06.
Article in En | MEDLINE | ID: mdl-36600598
ABSTRACT
Next-generation sequencing of human genomes reveals millions of missense variants, some of which may lead to loss of protein function and ultimately disease. Here, we investigate missense variants in membrane proteins-key drivers in cell signaling and recognition. We find enrichment of pathogenic variants in the transmembrane region across 19,000 functionally classified variants in human membrane proteins. To accurately predict variant consequences, one fundamentally needs to understand the underlying molecular processes. A key mechanism underlying pathogenicity in missense variants of soluble proteins has been shown to be loss of stability. Membrane proteins, however, are widely understudied. Here, we interpret variant effects on a larger scale by performing structure-based estimations of changes in thermodynamic stability using a membrane-specific energy function and analyses of sequence conservation during evolution of 15 transmembrane proteins. We find evidence for loss of stability being the cause of pathogenicity in more than half of the pathogenic variants, indicating that this is a driving factor also in membrane-protein-associated diseases. Our findings show how computational tools aid in gaining mechanistic insights into variant consequences for membrane proteins. To enable broader analyses of disease-related and population variants, we include variant mappings for the entire human proteome.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Signal Transduction / Membrane Proteins Type of study: Prognostic_studies Limits: Humans Language: En Journal: Biophys J Year: 2023 Document type: Article Affiliation country: Denmark

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Signal Transduction / Membrane Proteins Type of study: Prognostic_studies Limits: Humans Language: En Journal: Biophys J Year: 2023 Document type: Article Affiliation country: Denmark
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