Computational design of soluble and functional membrane protein analogues

• 成果类型: Article
• 署名作者: Goverde, Casper A.; Pacesa, Martin; Goldbach, Nicolas; Dornfeld, Lars J.; Balbi, Petra E. M.; Georgeon, Sandrine; Rosset, Stephane; Kapoor, Srajan; Choudhury, Jagrity; Dauparas, Justas; Schellhaas, Christian; Kozlov, Simon; Baker, David; Ovchinnikov, Sergey; Vecchio, Alex J.; Correia, Bruno E.
• 署名单位: State University of New York (SUNY) System; University at Buffalo, SUNY; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; Massachusetts Institute of Technology (MIT); University of Washington; University of Washington Seattle; Howard Hughes Medical Institute
• 刊物名称: Nature
• ISSN/ISSBN: 0028-5048
• DOI: 10.1038/s41586-024-07601-y
• 发表日期: 2024-07-11
• 关键词: de-novo design; coupled receptors; crystal-structure; EVOLUTION; claudins; insight; channel; motif

摘要

De novo design of complex protein folds using solely computational means remains a substantial challenge 1 . Here we use a robust deep learning pipeline to design complex folds and soluble analogues of integral membrane proteins. Unique membrane topologies, such as those from G-protein-coupled receptors 2 , are not found in the soluble proteome, and we demonstrate that their structural features can be recapitulated in solution. Biophysical analyses demonstrate the high thermal stability of the designs, and experimental structures show remarkable design accuracy. The soluble analogues were functionalized with native structural motifs, as a proof of concept for bringing membrane protein functions to the soluble proteome, potentially enabling new approaches in drug discovery. In summary, we have designed complex protein topologies and enriched them with functionalities from membrane proteins, with high experimental success rates, leading to a de facto expansion of the functional soluble fold space. A deep learning approach enables accurate computational design of soluble and functional analogues of membrane proteins, expanding the soluble protein fold space and facilitating new approaches to drug screening and design.