RosettaFold All-Atom Online Tool

Advances in machine learning have made protein structure prediction and design much more accurate and accessible in recent years, but these tools have generally been limited to polypeptide chains. However, ligands such as small molecules, metal ions, and nucleic acids are crucial components of most proteins, both in terms of structure and biological function. Krishna et al. present a next-generation protein structure prediction and design tool, RoseTTAFold All-Atom, that can accept a wide range of ligands and covalent amino acid modifications. The authors demonstrate superior performance on protein-ligand structure prediction relative to other tools, even in the absence of an input experimental structure. They also perform de novo design of proteins to bind cofactors and small molecules and experimentally validate these designs