AI revolutions in biology: The joys and perils of AlphaFold

doi: 10.15252/embr.202154046.

Online ahead of print.

Affiliations

Item in Clipboard

Anastassis Perrakis et al.

EMBO Rep.

2021.

Abstract

AlphaFold is the most ground-breaking application of AI in science so far; it will revolutionize structural biology, but caution is warranted.

1. Baek M, DiMaio F, Anishchenko I, Dauparas J, Ovchinnikov S, Lee GR, Wang J, Cong Q, Kinch LN, Schaeffer RD et al (2021) Accurate prediction of protein structures and interactions using a three-track neural network. Science 8754: eabj8754
1. Berman H, Henrick K, Nakamura H (2003) Announcing the worldwide protein data bank. Nat Struct Mol Biol 10: 980
1. Bouatta N, Sorger P, AlQuraishi M (2021) Protein structure prediction by AlphaFold 2: are attention and symmetries all you need? Acta Crystallogr Sect D Struct Biol 77: 982-991
1. Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Di Costanzo L, Christie C, Duarte JM, Dutta S, Feng Z et al (2019) Protein Data Bank: the single global archive for 3D macromolecular structure data. Nucleic Acids Res 47: D520-D528
1. Evans R, O’Neill M, Pritzel A, Antropova N, Senior A, Green T, Žídek A, Bates R, Blackwell S, Yim J et al (2021) Protein complex prediction with AlphaFold-Multimer. bioRxiv doi.org/10.1101/2021.10.04.463034 [PREPRINT]