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9EXK

Scalable protein design using hallucination in a relaxed sequence space

Summary for 9EXK
Entry DOI10.2210/pdb9exk/pdb
EMDB information50040
DescriptorDe novo designed protein K12 (1 entity in total)
Functional Keywordsde novo designed protein k12, de novo protein
Biological sourcesynthetic construct
Total number of polymer chains1
Total formula weight115735.98
Authors
Frank, C.J.,Dietz, H. (deposition date: 2024-04-08, release date: 2024-10-16, Last modification date: 2024-11-06)
Primary citationFrank, 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
Cited by
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
PDB entries with the same primary citation
Experimental method
ELECTRON MICROSCOPY (3.36 Å)
Structure validation

243911

數據於2025-10-29公開中

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