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Undersampling and the inference of coevolution in proteins.
Kleeorin, Yaakov; Russ, William P; Rivoire, Olivier; Ranganathan, Rama.
Afiliación
  • Kleeorin Y; Center for Physics of Evolving Systems, Department of Biochemistry & Molecular Biology, University of Chicago, Chicago, IL 60637, USA.
  • Russ WP; Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
  • Rivoire O; Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, 75005 Paris, France. Electronic address: olivier.rivoire@college-de-france.fr.
  • Ranganathan R; Center for Physics of Evolving Systems, Department of Biochemistry & Molecular Biology, University of Chicago, Chicago, IL 60637, USA; The Pritzker School for Molecular Engineering, University of Chicago, Chicago, IL 60637, USA. Electronic address: ranganathanr@uchicago.edu.
Cell Syst ; 14(3): 210-219.e7, 2023 03 15.
Article en En | MEDLINE | ID: mdl-36693377
ABSTRACT
Protein structure, function, and evolution depend on local and collective epistatic interactions between amino acids. A powerful approach to defining these interactions is to construct models of couplings between amino acids that reproduce the empirical statistics (frequencies and correlations) observed in sequences comprising a protein family. The top couplings are then interpreted. Here, we show that as currently implemented, this inference unequally represents epistatic interactions, a problem that fundamentally arises from limited sampling of sequences in the context of distinct scales at which epistasis occurs in proteins. We show that these issues explain the ability of current approaches to predict tertiary contacts between amino acids and the inability to obviously expose larger networks of functionally relevant, collectively evolving residues called sectors. This work provides a necessary foundation for more deeply understanding and improving evolution-based models of proteins.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Aminoácidos Tipo de estudio: Prognostic_studies Idioma: En Revista: Cell Syst Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Aminoácidos Tipo de estudio: Prognostic_studies Idioma: En Revista: Cell Syst Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
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