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Understanding the cell: Future views of structural biology.
Beck, Martin; Covino, Roberto; Hänelt, Inga; Müller-McNicoll, Michaela.
Afiliação
  • Beck M; Max Planck Institute of Biophysics, Max-von-Laue-Straße 3, 60438 Frankfurt am Main, Germany; Goethe University Frankfurt, Frankfurt, Germany. Electronic address: martin.beck@biophys.mpg.de.
  • Covino R; Frankfurt Institute for Advanced Studies, Ruth-Moufang-Straße 1, 60438 Frankfurt am Main, Germany. Electronic address: covino@fias.uni-frankfurt.de.
  • Hänelt I; Goethe University Frankfurt, Frankfurt, Germany. Electronic address: haenelt@biochem.uni-frankfurt.de.
  • Müller-McNicoll M; Goethe University Frankfurt, Frankfurt, Germany. Electronic address: mueller-mcnicoll@bio.uni-frankfurt.de.
Cell ; 187(3): 545-562, 2024 Feb 01.
Article em En | MEDLINE | ID: mdl-38306981
ABSTRACT
Determining the structure and mechanisms of all individual functional modules of cells at high molecular detail has often been seen as equal to understanding how cells work. Recent technical advances have led to a flush of high-resolution structures of various macromolecular machines, but despite this wealth of detailed information, our understanding of cellular function remains incomplete. Here, we discuss present-day limitations of structural biology and highlight novel technologies that may enable us to analyze molecular functions directly inside cells. We predict that the progression toward structural cell biology will involve a shift toward conceptualizing a 4D virtual reality of cells using digital twins. These will capture cellular segments in a highly enriched molecular detail, include dynamic changes, and facilitate simulations of molecular processes, leading to novel and experimentally testable predictions. Transferring biological questions into algorithms that learn from the existing wealth of data and explore novel solutions may ultimately unveil how cells work.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia / Biologia Computacional Tipo de estudo: Prognostic_studies Idioma: En Revista: Cell Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia / Biologia Computacional Tipo de estudo: Prognostic_studies Idioma: En Revista: Cell Ano de publicação: 2024 Tipo de documento: Article