Pushmeet Kohli

Designing enzymes for new-to-nature chemistry and non-natural substrates with AlphaProtein Novo

This paper introduces AlphaProtein Novo, a machine-learning pipeline for de novo enzyme design that outperforms natural sequence mining in creating enzymes for new-to-nature chemistry and substrates.

Design-Evolution Synergy Enables New-to-Nature Enzyme Chemistry

This study combines design and evolution to create new-to-nature enzymes capable of performing regio- and enantioselective C-H amination reactions for synthesizing chiral piperidines.

AlphaGenome Atlas: in silico mutagenesis of the entire human genome improves prioritization and interpretation of non-coding variants

AlphaGenome Atlas predicts regulatory effects of non-coding variants across the human genome, improving their prioritization and interpretation.

AlphaGenome: advancing regulatory variant effect prediction with a unified DNA sequence model

AlphaGenome predicts functional genomic measurements from DNA sequences with high resolution and accuracy across multiple modalities, outperforming existing methods in variant effect prediction.

Protein complex prediction with AlphaFold-Multimer

AlphaFold trained on complexes, with cross-chain paired alignments and symmetry-aware losses, gets 70% of recent heteromeric interfaces acceptable or better (DockQ ≥ 0.23), 27 points above linker-joined AlphaFold.

Effective gene expression prediction from sequence by integrating long-range interactions

Enformer, a sequence-based transformer integrating elements up to 100 kb away, lifts held-out gene expression prediction (correlation 0.81 to 0.85 versus Basenji2) and variant effect prediction.

Highly accurate protein structure prediction with AlphaFold

AlphaFold, an attention network over sequence alignments and residue pairs, rivaled experimental accuracy in most CASP14 cases: median backbone r.m.s.d.95 0.96 Å versus 2.8 Å for the runner-up.