Highly accurate protein structure prediction with AlphaFold
John Jumper, Richard Evans, Alexander Pritzel, David Silver, Oriol Vinyals, Demis Hassabis · Large multi-author DeepMind AlphaFold team (Jumper et al., ~20 authors); first three and final three key authors listed, with David Silver, Oriol Vinyals and Demis Hassabis among the senior/corresponding authors.
Summary
The paper introduces AlphaFold2, a deep-learning system that predicts three-dimensional protein structures directly from amino-acid sequence with near-experimental accuracy. It combines a novel attention-based Evoformer over multiple sequence alignments and pairwise representations with an end-to-end structure module that produces atomic coordinates. AlphaFold won the CASP14 assessment by a wide margin, delivering atomic-level accuracy for the majority of targets.
Key findings
- Predicts protein 3D structure from sequence at accuracy competitive with experimental methods for many proteins.
- Introduces the Evoformer and an end-to-end structure module, with per-residue confidence (pLDDT) estimates.
- Substantially outperformed all other methods at CASP14, marking a step change in computational structure prediction.
Subjects & keywords
Cite this paper
John Jumper, Richard Evans, Alexander Pritzel, David Silver, Oriol Vinyals, & Demis Hassabis [Large multi-author DeepMind AlphaFold team (Jumper et al., ~20 authors); first three and final three key authors listed, with David Silver, Oriol Vinyals and Demis Hassabis among the senior/corresponding authors.] (2021). Highly accurate protein structure prediction with AlphaFold. Nature. https://doi.org/10.1038/s41586-021-03819-2
@article{jumper2021highly,
author = {John Jumper and Richard Evans and Alexander Pritzel and David Silver and Oriol Vinyals and Demis Hassabis and {Large multi-author DeepMind AlphaFold team (Jumper et al., ~20 authors); first three and final three key authors listed, with David Silver, Oriol Vinyals and Demis Hassabis among the senior/corresponding authors.}},
title = {Highly accurate protein structure prediction with AlphaFold},
journal = {Nature},
year = {2021},
doi = {10.1038/s41586-021-03819-2},
url = {https://doi.org/10.1038/s41586-021-03819-2}
}