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Accurate structure prediction of biomolecular interactions with AlphaFold 3.
Abramson, Josh; Adler, Jonas; Dunger, Jack; Evans, Richard; Green, Tim; Pritzel, Alexander; Ronneberger, Olaf; Willmore, Lindsay; Ballard, Andrew J; Bambrick, Joshua; Bodenstein, Sebastian W; Evans, David A; Hung, Chia-Chun; O'Neill, Michael; Reiman, David; Tunyasuvunakool, Kathryn; Wu, Zachary; Zemgulyte, Akvile; Arvaniti, Eirini; Beattie, Charles; Bertolli, Ottavia; Bridgland, Alex; Cherepanov, Alexey; Congreve, Miles; Cowen-Rivers, Alexander I; Cowie, Andrew; Figurnov, Michael; Fuchs, Fabian B; Gladman, Hannah; Jain, Rishub; Khan, Yousuf A; Low, Caroline M R; Perlin, Kuba; Potapenko, Anna; Savy, Pascal; Singh, Sukhdeep; Stecula, Adrian; Thillaisundaram, Ashok; Tong, Catherine; Yakneen, Sergei; Zhong, Ellen D; Zielinski, Michal; Zídek, Augustin; Bapst, Victor; Kohli, Pushmeet; Jaderberg, Max; Hassabis, Demis; Jumper, John M.
Afiliação
  • Abramson J; Core Contributor, Google DeepMind, London, UK.
  • Adler J; Core Contributor, Google DeepMind, London, UK.
  • Dunger J; Core Contributor, Google DeepMind, London, UK.
  • Evans R; Core Contributor, Google DeepMind, London, UK.
  • Green T; Core Contributor, Google DeepMind, London, UK.
  • Pritzel A; Core Contributor, Google DeepMind, London, UK.
  • Ronneberger O; Core Contributor, Google DeepMind, London, UK.
  • Willmore L; Core Contributor, Google DeepMind, London, UK.
  • Ballard AJ; Core Contributor, Google DeepMind, London, UK.
  • Bambrick J; Core Contributor, Isomorphic Labs, London, UK.
  • Bodenstein SW; Core Contributor, Google DeepMind, London, UK.
  • Evans DA; Core Contributor, Google DeepMind, London, UK.
  • Hung CC; Core Contributor, Isomorphic Labs, London, UK.
  • O'Neill M; Core Contributor, Google DeepMind, London, UK.
  • Reiman D; Core Contributor, Google DeepMind, London, UK.
  • Tunyasuvunakool K; Core Contributor, Google DeepMind, London, UK.
  • Wu Z; Core Contributor, Google DeepMind, London, UK.
  • Zemgulyte A; Core Contributor, Google DeepMind, London, UK.
  • Arvaniti E; Google DeepMind, London, UK.
  • Beattie C; Google DeepMind, London, UK.
  • Bertolli O; Google DeepMind, London, UK.
  • Bridgland A; Google DeepMind, London, UK.
  • Cherepanov A; Isomorphic Labs, London, UK.
  • Congreve M; Isomorphic Labs, London, UK.
  • Cowen-Rivers AI; Google DeepMind, London, UK.
  • Cowie A; Google DeepMind, London, UK.
  • Figurnov M; Google DeepMind, London, UK.
  • Fuchs FB; Google DeepMind, London, UK.
  • Gladman H; Google DeepMind, London, UK.
  • Jain R; Google DeepMind, London, UK.
  • Khan YA; Google DeepMind, London, UK.
  • Low CMR; Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA, USA.
  • Perlin K; Isomorphic Labs, London, UK.
  • Potapenko A; Google DeepMind, London, UK.
  • Savy P; Google DeepMind, London, UK.
  • Singh S; Isomorphic Labs, London, UK.
  • Stecula A; Google DeepMind, London, UK.
  • Thillaisundaram A; Isomorphic Labs, London, UK.
  • Tong C; Google DeepMind, London, UK.
  • Yakneen S; Isomorphic Labs, London, UK.
  • Zhong ED; Isomorphic Labs, London, UK.
  • Zielinski M; Google DeepMind, London, UK.
  • Zídek A; Department of Computer Science, Princeton University, Princeton, NJ, USA.
  • Bapst V; Google DeepMind, London, UK.
  • Kohli P; Google DeepMind, London, UK.
  • Jaderberg M; Core Contributor, Google DeepMind, London, UK.
  • Hassabis D; Core Contributor, Google DeepMind, London, UK.
  • Jumper JM; Core Contributor, Isomorphic Labs, London, UK. jaderberg@isomorphiclabs.com.
Nature ; 630(8016): 493-500, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38718835
ABSTRACT
The introduction of AlphaFold 21 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design2-6. Here we describe our AlphaFold 3 model with a substantially updated diffusion-based architecture that is capable of predicting the joint structure of complexes including proteins, nucleic acids, small molecules, ions and modified residues. The new AlphaFold model demonstrates substantially improved accuracy over many previous specialized tools far greater accuracy for protein-ligand interactions compared with state-of-the-art docking tools, much higher accuracy for protein-nucleic acid interactions compared with nucleic-acid-specific predictors and substantially higher antibody-antigen prediction accuracy compared with AlphaFold-Multimer v.2.37,8. Together, these results show that high-accuracy modelling across biomolecular space is possible within a single unified deep-learning framework.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Proteínas / Modelos Moleculares / Aprendizado Profundo / Ligantes Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Proteínas / Modelos Moleculares / Aprendizado Profundo / Ligantes Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article