Abstract AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind
that can predict three-dimensional (3D) structures of proteins from amino acid sequences …

Since the first revelation of proteins functioning as macromolecular machines through their
three dimensional structures, researchers have been intrigued by the marvelous ways the …

Deep-learning language models have shown promise in various biotechnological
applications, including protein design and engineering. Here we describe ProGen, a …

De novo enzyme design has sought to introduce active sites and substrate-binding pockets
that are predicted to catalyse a reaction of interest into geometrically compatible native …

We consider the problem of predicting a protein sequence from its backbone atom
coordinates. Machine learning approaches to this problem to date have been limited by the …

The binding and catalytic functions of proteins are generally mediated by a small number of
functional residues held in place by the overall protein structure. Here, we describe deep …

Advances in DNA sequencing and machine learning are providing insights into protein
sequences and structures on an enormous scale. However, the energetics driving folding …

Deep learning generative approaches provide an opportunity to broadly explore protein
structure space beyond the sequences and structures of natural proteins. Here, we use deep …

Recently it has become possible to de novo design high affinity protein binding proteins from
target structural information alone. There is, however, considerable room for improvement as …

There has been considerable recent progress in protein structure prediction using deep
neural networks to predict inter-residue distances from amino acid sequences,–. Here we …