Joel Beazer

Aug 3, 2024 | biorxiv.org | Jeffrey A. Ruffolo |Aadyot Bhatnagar |Stephen Nayfach |Joel Beazer

AbstractGenerative models for protein design trained on experimentally determined structures have proven useful for a variety of design tasks. However, such methods are limited by the quantity and diversity of structures used for training, which represent a small, biased fraction of protein space. Here, we describe proseLM, a method for protein sequence design based on adaptation of protein language models to incorporate structural and functional context.