Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their
natural effectiveness has been fine-tuned as a result of millions of years of natural evolution …

Language models have recently emerged as a powerful machine-learning approach for
distilling information from massive protein sequence databases. From readily available …

Prolonged high-temperature extreme events in the ocean, marine heatwaves, can have
severe and long-lasting impacts on marine ecosystems, fisheries and associated services …

Enzyme engineering plays a central role in developing efficient biocatalysts for
biotechnology, biomedicine, and life sciences. Apart from classical rational design and …

Determining the pathogenicity of genetic variants is a critical challenge, and functional
assessment is often the only option. Experimentally characterizing millions of possible …

INTRODUCTION Enzymes possess extraordinary catalytic proficiency and specificity. These
properties ultimately derive from interactions not just between the active-site residues and …

Multiplex assays of variant effect (MAVEs), such as deep mutational scans and massively
parallel reporter assays, test thousands of sequence variants in a single experiment. Despite …

Genotype–phenotype relationships are notoriously complicated. Idiosyncratic interactions
between specific combinations of mutations occur and are difficult to predict. Yet it is …

Designing protein sequences with a particular biological function is a long-lasting challenge
for protein engineering. Recent advances in machine-learning-guided approaches focus on …