Recent breakthroughs in AI coupled with the rapid accumulation of protein sequence and
structure data have radically transformed computational protein design. New methods …

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 …

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 …

Recent advances in machine learning have leveraged evolutionary information in multiple
sequence alignments to predict protein structure. We demonstrate direct inference of full …

The genome is a sequence that encodes the DNA, RNA, and proteins that orchestrate an
organism's function. We present Evo, a long-context genomic foundation model with a …

Protein design aims to build novel proteins customized for specific purposes, thereby
holding the potential to tackle many environmental and biomedical problems. Recent …

Attention-based models trained on protein sequences have demonstrated incredible
success at classification and generation tasks relevant for artificial-intelligence-driven …

Recent developments in deep learning, coupled with an increasing number of sequenced
proteins, have led to a breakthrough in life science applications, in particular in protein …

Adapting language models to protein sequences spawned the development of powerful
protein language models (pLMs). Concurrently, AlphaFold2 broke through in protein …

This paper demonstrates that language models are strong structure-based protein
designers. We present LM-Design, a generic approach to reprogramming sequence-based …