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Homologues not needed: Structure prediction from a protein language model.
Ben-Tal, Nir; Kolodny, Rachel.
Afiliação
  • Ben-Tal N; Department of Biochemistry and Molecular Biology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel. Electronic address: bental@tauex.tau.ac.il.
  • Kolodny R; Department of Computer Science, University of Haifa, Mount Carmel, Haifa, 3498838, Israel. Electronic address: trachel@cs.haifa.ac.il.
Structure ; 30(8): 1047-1049, 2022 08 04.
Article em En | MEDLINE | ID: mdl-35931059
Accurate protein structure predictors use clusters of homologues, which disregard sequence specific effects. In this issue of Structure, Weißenow and colleagues report a deep learning-based tool, EMBER2, that efficiently predicts the distances in a protein structure from its amino acid sequence only. This approach should enable the analysis of mutation effects.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Aprendizado Profundo Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Aprendizado Profundo Idioma: En Ano de publicação: 2022 Tipo de documento: Article