8S89

Efficient and scalable protein design using a relaxed sequence space

Summary for 8S89

• Entry DOI: 10.2210/pdb8s89/pdb
• Descriptor: DE NOVO PROTEIN P400, SULFATE ION (3 entities in total)
• Functional Keywords: de novo protein, p400
• Biological source: synthetic construct
• Total number of polymer chains: 1
• Total formula weight: 43728.92

Authors

Frank, C.J.,Dietz, H. (deposition date: 2024-03-06, release date: 2024-10-16, Last modification date: 2024-11-06)

Primary citation

Frank, C.,Khoshouei, A.,Fu beta, L.,Schiwietz, D.,Putz, D.,Weber, L.,Zhao, Z.,Hattori, M.,Feng, S.,de Stigter, Y.,Ovchinnikov, S.,Dietz, H.
Scalable protein design using optimization in a relaxed sequence space.
Science, 386:439-445, 2024

PubMed Abstract: Machine learning (ML)-based design approaches have advanced the field of de novo protein design, with diffusion-based generative methods increasingly dominating protein design pipelines. Here, we report a "hallucination"-based protein design approach that functions in relaxed sequence space, enabling the efficient design of high-quality protein backbones over multiple scales and with broad scope of application without the need for any form of retraining. We experimentally produced and characterized more than 100 proteins. Three high-resolution crystal structures and two cryo-electron microscopy density maps of designed single-chain proteins comprising up to 1000 amino acids validate the accuracy of the method. Our pipeline can also be used to design synthetic protein-protein interactions, as validated experimentally by a set of protein heterodimers. Relaxed sequence optimization offers attractive performance with respect to designability, scope of applicability for different design problems, and scalability across protein sizes.

PubMed: 39446959
DOI: 10.1126/science.adq1741

Experimental method

X-RAY DIFFRACTION (2.1 Å)