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

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 …

We introduce AbDiffuser, an equivariant and physics-informed diffusion model for the joint
generation of antibody 3D structures and sequences. AbDiffuser is built on top of a new …

We seek to transform how new and emergent variants of pandemic-causing viruses,
specifically SARS-CoV-2, are identified and classified. By adapting large language models …

In recent years, generative protein sequence models have been developed to sample novel
sequences. However, predicting whether generated proteins will fold and function remains …

Emerging computational tools promise to revolutionize protein engineering for biocatalytic
applications and accelerate the development timelines previously needed to optimize an …

Deep generative models are increasingly powerful tools for the in silico design of novel
proteins. Recently, a family of generative models called diffusion models has demonstrated …

Methods from artificial intelligence (AI) trained on large datasets of sequences and
structures can now" write" proteins with new shapes and molecular functions de novo …

Advanced Artificial Intelligence (AI) enabled large language models (LLMs) to revolutionize
Natural Language Processing (NLP). Their adaptation to protein sequences spawned the …

Peptides modulate many processes of human physiology targeting ion channels, protein
receptors, or enzymes. They represent valuable starting points for the development of new …