Accurate structure prediction of biomolecular interactions with AlphaFold 3
Google DeepMind (United Kingdom) · Google (United Kingdom) · +3 more institutions
Abstract
Abstract The introduction of AlphaFold 2 1 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design 2–6 . 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…
Citation impact
- FWCI
- 2736.99
- Percentile
- 100%
- References
- 77
Authors
48- JAJosh AbramsonCorresponding
Google DeepMind (United Kingdom), Google (United Kingdom)
- JAJonas Adler
Google DeepMind (United Kingdom), Google (United Kingdom)
- JDJack Dunger
Google DeepMind (United Kingdom), Google (United Kingdom)
- RERichard Evans
Google DeepMind (United Kingdom), Google (United Kingdom)
- TGTim Green
Google DeepMind (United Kingdom), Google (United Kingdom)
Topics & keywords
- Computational biology
- Computer science
- Biology