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Approximating conformational Boltzmann distributions with AlphaFold2 predictions.
Brown, Benjamin P; Stein, Richard A; Meiler, Jens; Mchaourab, Hassane.
Afiliación
  • Brown BP; Department of Chemistry, Vanderbilt University, Nashville, TN, USA. Nashville, TN 37232, USA.
  • Stein RA; Center for Structural Biology, Vanderbilt University, Nashville, TN, USA. Nashville, TN 37232, USA.
  • Meiler J; Center for Applied AI in Protein Dynamics, Vanderbilt University, Nashville, TN, USA. Nashville, TN 37232, USA.
  • Mchaourab H; Center for Applied AI in Protein Dynamics, Vanderbilt University, Nashville, TN, USA. Nashville, TN 37232, USA.
bioRxiv ; 2023 Aug 07.
Article en En | MEDLINE | ID: mdl-37609301
ABSTRACT
Protein dynamics are intimately tied to biological function and can enable processes such as signal transduction, enzyme catalysis, and molecular recognition. The relative free energies of conformations that contribute to these functional equilibria are evolved for the physiology of the organism. Despite the importance of these equilibria for understanding biological function and developing treatments for disease, the computational and experimental methods capable of quantifying them are limited to systems of modest size. Here, we demonstrate that AlphaFold2 contact distance distributions can approximate conformational Boltzmann distributions, which we evaluate through examination of the joint probability distributions of inter-residue contact distances along functionally relevant collective variables of several protein systems. Further, we show that contact distance probability distributions generated by AlphaFold2 are sensitive to points mutations thus AF2 can predict the structural effects of mutations in some systems. We anticipate that our approach will be a valuable tool to model the thermodynamics of conformational changes in large biomolecular systems.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
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