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 …

Achieving cost-competitive bio-based processes requires development of stable and
selective biocatalysts. Their realization through in vitro enzyme characterization and …

Deep-learning methods have revolutionized protein structure prediction and design but are
presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which …

Designing efficient enzymes is a formidable challenge at the forefront of modern
biocatalysis. Here, we review recent developments in the field and illustrate how the …

The engineering of natural enzymes has led to the availability of a broad range of
biocatalysts that can be used for the sustainable manufacturing of a variety of chemicals and …

Designing proteins with tailored structures and functions is a long-standing goal in
bioengineering. Recently, deep learning advances have enabled protein structure …

The development of artificial metalloenzymes (ArMs) aims to expand the capabilities of
enzymatic catalysis, most notably towards new reaction mechanisms. Frequently, ArMs …

Embedding a catalytically competent transition metal into a protein scaffold affords an
artificial metalloenzyme (ArM). Such hybrid catalysts display features that are reminiscent of …

Recent advancements in photoacoustic (PA) imaging have leveraged reversibly
photoswitchable chromophores, known for their dual absorbance states, to enhance …

Enzyme engineering is limited by the challenge of rapidly generating and using large
datasets of sequence-function relationships for predictive design. To address this challenge …