A New Tool for Protein Designers

Proteins are important molecules—but they aren’t the only molecules in a cell, and they don’t operate alone. In a new preprint, the team behind the protein structure prediction software RoseTTAFold has announced a tool that expands the types of chemistry that protein designers using deep learning will be able to incorporate, to reflect proteins’ environment better (bioRxiv 2023, DOI: 10.1101/2023.10.09.561603 ) . Protein structure prediction algorithms, such as AlphaFold and RoseTTAFold, have swept through the field of structural biology in recent years. These machine learning tools, trained on protein structures that have been solved experimentally, predict new 3D structures based only on proteins’ amino acid sequences. Biochemists use those predictions to develop hypotheses about how proteins work and how they fit together, and they have also used the tools to design new proteins with desired functions. The trouble is, these models overlook many types of chemistry that can influence a