Novel and improved biocatalysts are increasingly sourced from libraries via experimental
screening. The success of such campaigns is crucially dependent on the number of …

Evolvability is the ability of a biological system to produce phenotypic variation that is both
heritable and adaptive. It has long been the subject of anecdotal observations and …

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

Predicting the effects of mutations in proteins is critical to many applications, from
understanding genetic disease to designing novel proteins to address our most pressing …

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

The functions of proteins and RNAs are defined by the collective interactions of many
residues, and yet most statistical models of biological sequences consider sites nearly …

Enzymes can be engineered at the level of their amino acid sequences to optimize key
properties such as expression, stability, substrate range, and catalytic efficiency─ or even to …

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 …

QM/MM simulations have become an indispensable tool in many chemical and biochemical
investigations. Considering the tremendous degree of success, including recognition by a …

In offline model-based optimization, we strive to maximize a black-box objective function by
only leveraging a static dataset of designs and their scores. This problem setting arises in …