Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments.

Journal

Science advances
ISSN: 2375-2548
Titre abrégé: Sci Adv
Pays: United States
ID NLM: 101653440

Informations de publication

Date de publication:
05 Apr 2024
Historique:
medline: 5 4 2024
pubmed: 5 4 2024
entrez: 5 4 2024
Statut: ppublish

Résumé

The GEMS method enables molecular dynamics simulations of large heterogeneous systems at ab initio quality.

Identifiants

DOI: 10.1126/sciadv.adn4397 PMID: 38579003
pubmed: 38579003
doi: 10.1126/sciadv.adn4397
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

eadn4397

Auteurs

Oliver T Unke (OT)

Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland.
Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany.
DFG Cluster of Excellence "Unifying Systems in Catalysis" (UniSysCat), Technische Universität Berlin, 10623 Berlin, Germany.
ORCID: 0000-0001-7503-406X

Martin Stöhr (M)

Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg.
ORCID: 0000-0002-4068-4692

Stefan Ganscha (S)

Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland.
ORCID: 0009-0009-1640-9576

Thomas Unterthiner (T)

Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland.
ORCID: 0000-0001-5361-3087

Hartmut Maennel (H)

Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland.
ORCID: 0000-0002-4833-3387

Sergii Kashubin (S)

Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland.
ORCID: 0009-0001-5498-5939

Daniel Ahlin (D)

Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland.
ORCID: 0009-0008-7528-1712

Michael Gastegger (M)

Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany.
DFG Cluster of Excellence "Unifying Systems in Catalysis" (UniSysCat), Technische Universität Berlin, 10623 Berlin, Germany.
BASLEARN - TU Berlin/BASF Joint Lab for Machine Learning, Technische Universität Berlin, 10587 Berlin, Germany.
ORCID: 0000-0001-7954-3275

Leonardo Medrano Sandonas (L)

Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg.
ORCID: 0000-0002-7673-3142

Joshua T Berryman (JT)

Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg.
ORCID: 0000-0002-6959-4607

Alexandre Tkatchenko (A)

Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg.
ORCID: 0000-0002-1012-4854

Klaus-Robert Müller (KR)

Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland.
Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany.
Department of Artificial Intelligence, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea.
Max Planck Institute for Informatics, Stuhlsatzenhausweg, 66123 Saarbrücken, Germany.
BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.
ORCID: 0000-0002-3861-7685

Classifications MeSH