Quinton M. Dowling, Young-Jun Park, Chelsea N. Fries, Neil C. Gerstenmaier, Sebastian Ols, Erin C. Yang, Adam J. Wargacki, Annie Dosey, Yang Hsia, Rashmi Ravichandran, Carl D. Walkey, Anika L. Burrell, David Veesler, David Baker, Neil P. King
{"title":"伪对称蛋白质纳米笼的分层设计","authors":"Quinton M. Dowling, Young-Jun Park, Chelsea N. Fries, Neil C. Gerstenmaier, Sebastian Ols, Erin C. Yang, Adam J. Wargacki, Annie Dosey, Yang Hsia, Rashmi Ravichandran, Carl D. Walkey, Anika L. Burrell, David Veesler, David Baker, Neil P. King","doi":"10.1038/s41586-024-08360-6","DOIUrl":null,"url":null,"abstract":"<p>Discrete protein assemblies ranging from hundreds of kilodaltons to hundreds of megadaltons in size are a ubiquitous feature of biological systems and perform highly specialized functions<sup>1,2</sup>. Despite remarkable recent progress in accurately designing new self-assembling proteins, the size and complexity of these assemblies has been limited by a reliance on strict symmetry<sup>3</sup>. Here, inspired by the pseudosymmetry observed in bacterial microcompartments and viral capsids, we developed a hierarchical computational method for designing large pseudosymmetric self-assembling protein nanomaterials. We computationally designed pseudosymmetric heterooligomeric components and used them to create discrete, cage-like protein assemblies with icosahedral symmetry containing 240, 540 and 960 subunits. At 49, 71 and 96 nm diameter, these nanocages are the largest bounded computationally designed protein assemblies generated to date. More broadly, by moving beyond strict symmetry, our work substantially broadens the variety of self-assembling protein architectures that are accessible through design.</p>","PeriodicalId":18787,"journal":{"name":"Nature","volume":"1 1","pages":""},"PeriodicalIF":50.5000,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hierarchical design of pseudosymmetric protein nanocages\",\"authors\":\"Quinton M. Dowling, Young-Jun Park, Chelsea N. Fries, Neil C. Gerstenmaier, Sebastian Ols, Erin C. Yang, Adam J. Wargacki, Annie Dosey, Yang Hsia, Rashmi Ravichandran, Carl D. Walkey, Anika L. Burrell, David Veesler, David Baker, Neil P. King\",\"doi\":\"10.1038/s41586-024-08360-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Discrete protein assemblies ranging from hundreds of kilodaltons to hundreds of megadaltons in size are a ubiquitous feature of biological systems and perform highly specialized functions<sup>1,2</sup>. Despite remarkable recent progress in accurately designing new self-assembling proteins, the size and complexity of these assemblies has been limited by a reliance on strict symmetry<sup>3</sup>. Here, inspired by the pseudosymmetry observed in bacterial microcompartments and viral capsids, we developed a hierarchical computational method for designing large pseudosymmetric self-assembling protein nanomaterials. We computationally designed pseudosymmetric heterooligomeric components and used them to create discrete, cage-like protein assemblies with icosahedral symmetry containing 240, 540 and 960 subunits. At 49, 71 and 96 nm diameter, these nanocages are the largest bounded computationally designed protein assemblies generated to date. More broadly, by moving beyond strict symmetry, our work substantially broadens the variety of self-assembling protein architectures that are accessible through design.</p>\",\"PeriodicalId\":18787,\"journal\":{\"name\":\"Nature\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":50.5000,\"publicationDate\":\"2024-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41586-024-08360-6\",\"RegionNum\":1,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41586-024-08360-6","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Hierarchical design of pseudosymmetric protein nanocages
Discrete protein assemblies ranging from hundreds of kilodaltons to hundreds of megadaltons in size are a ubiquitous feature of biological systems and perform highly specialized functions1,2. Despite remarkable recent progress in accurately designing new self-assembling proteins, the size and complexity of these assemblies has been limited by a reliance on strict symmetry3. Here, inspired by the pseudosymmetry observed in bacterial microcompartments and viral capsids, we developed a hierarchical computational method for designing large pseudosymmetric self-assembling protein nanomaterials. We computationally designed pseudosymmetric heterooligomeric components and used them to create discrete, cage-like protein assemblies with icosahedral symmetry containing 240, 540 and 960 subunits. At 49, 71 and 96 nm diameter, these nanocages are the largest bounded computationally designed protein assemblies generated to date. More broadly, by moving beyond strict symmetry, our work substantially broadens the variety of self-assembling protein architectures that are accessible through design.
期刊介绍:
Nature is a prestigious international journal that publishes peer-reviewed research in various scientific and technological fields. The selection of articles is based on criteria such as originality, importance, interdisciplinary relevance, timeliness, accessibility, elegance, and surprising conclusions. In addition to showcasing significant scientific advances, Nature delivers rapid, authoritative, insightful news, and interpretation of current and upcoming trends impacting science, scientists, and the broader public. The journal serves a dual purpose: firstly, to promptly share noteworthy scientific advances and foster discussions among scientists, and secondly, to ensure the swift dissemination of scientific results globally, emphasizing their significance for knowledge, culture, and daily life.