Design a sequence to fold into a protein structure
ProteinMPNN significantly outperforms traditional approaches like Rosetta, achieving 52.4% sequence recovery. It can design sequences for single or multiple chains and has been experimentally validated through X-ray crystallography, cryoEM, and functional studies. The method has successfully designed various protein types including monomers, cyclic homo-oligomers, and target binding proteins, representing a major advancement in computational protein design.ProteinMPNN is often used after RFdiffusion to generate sequences for a given designed structure, since RFdiffusion/RFantibody will design structures with poly-Gs as placeholders for designed residues. It can also be used directly from a starting structure to generate stabilizing mutations.