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Template-free prediction of a new monotopic membrane protein fold and assembly by AlphaFold2.
Gulsevin, Alican; Han, Bing; Porta, Jason C; Mchaourab, Hassane S; Meiler, Jens; Kenworthy, Anne K.
Afiliação
  • Gulsevin A; Department of Chemistry, Vanderbilt University, Nashville, Tennessee.
  • Han B; Center for Membrane and Cell Physiology, University of Virginia, Charlottesville, Virginia; Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, Virginia.
  • Porta JC; Life Sciences Institute, University of Michigan, Ann Arbor, Michigan.
  • Mchaourab HS; Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee.
  • Meiler J; Department of Chemistry, Vanderbilt University, Nashville, Tennessee; Institute for Drug Discovery, Leipzig University, Leipzig, Germany. Electronic address: jens@meilerlab.org.
  • Kenworthy AK; Center for Membrane and Cell Physiology, University of Virginia, Charlottesville, Virginia; Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, Virginia. Electronic address: akk7hp@virginia.edu.
Biophys J ; 122(11): 2041-2052, 2023 06 06.
Article em En | MEDLINE | ID: mdl-36352786
AlphaFold2 (AF2) has revolutionized the field of protein structural prediction. Here, we test its ability to predict the tertiary and quaternary structure of a previously undescribed scaffold with new folds and unusual architecture, the monotopic membrane protein caveolin-1 (CAV1). CAV1 assembles into a disc-shaped oligomer composed of 11 symmetrically arranged protomers, each assuming an identical new fold, and contains the largest parallel ß-barrel known to exist in nature. Remarkably, AF2 predicts both the fold of the protomers and the interfaces between them. It also assembles between seven and 15 copies of CAV1 into disc-shaped complexes. However, the predicted multimers are energetically strained, especially the parallel ß-barrel. These findings highlight the ability of AF2 to correctly predict new protein folds and oligomeric assemblies at a granular level while missing some elements of higher-order complexes, thus positing a new direction for the continued development of deep-learning protein structure prediction approaches.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Furilfuramida / Proteínas de Membrana Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Furilfuramida / Proteínas de Membrana Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article