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Local structural flexibility drives oligomorphism in computationally designed protein assemblies
Open accessPreprint — published as 10.1038/s41594-025-01490-z · Paper page
Abstract
Many naturally occurring protein assemblies have dynamic structures that allow them to perform specialized functions. For example, clathrin coats adopt a wide variety of architectures to adapt to vesicular cargos of various sizes. Although computational methods for designing novel self-assembling proteins have advanced substantially over the past decade, most existing methods focus on designing static structures with high accuracy. Here we characterize the structures of three distinct computationally designed protein assemblies that each form multiple unanticipated architectures, and identify flexibility in specific regions of the subunits of each assembly as the source of structural diversity. Cryo-EM single-particle reconstructions and native mass spectrometry showed that only two distinct architectures were observed in two of the three cases, while we obtained six cryo-EM reconstructions that likely represent a subset of the architectures present in solution in the third case. Structural modeling and molecular dynamics simulations indicated that the surprising observation of a defined range of architectures, instead of non-specific aggregation, can be explained by constrained flexibility within the building blocks. Our results suggest that deliberate use of structural flexibility as a design principle will allow exploration of previously inaccessible structural and functional space in designed protein assemblies.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
AlphaFold and Implications for Intrinsically Disordered Proteins
Ruff, K. M., & Pappu, R. V. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167208 · Cited by 635 · cited 1×
“Previous work has correlated the degree of flexibility and the presence of unstructured regions with AF2 pLDDT at the residue level 66–68 .”
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Research works printed but not linked: 92
- 2011, Rationally engineering natural protein assemblies in nanobiotechnology, Curr Opin Biotechnol, 22, 485, 10.1016/j.copbio.2011.05.003 · DOI
- 2016, Bioengineered protein-based nanocage for drug delivery, Adv Drug Deliv Rev, 106, 157, 10.1016/j.addr.2016.03.002 · DOI
- 2022, Engineering Self-Assembling Protein Nanoparticles for Therapeutic Delivery, Bioconjug Chem, 33, 2018, 10.1021/acs.bioconjchem.2c00030 · DOI
- Basu Mallik B , Stanislaw J , Alawathurage TM , Khmelinskaia A . De novo design of polyhedral protein assemblies: before and after the AI revolution. Chembiochem 2023;: e202300117. · DOI
- 10.1126/science.1219364 · DOI
- 10.1038/nature13404 · DOI
- 10.1126/science.aaf8818 · DOI
- 10.1038/nature18010 · DOI
- Yang EC , Divine R , Miranda MC , Borst AJ , Sheffler W , Zhang JZ , et al. Computational design of non-porous, pH-responsive antibody nanoparticles. bioRxiv. 2023;: 2023.04.17.537263. · DOI
- Huddy TF , Hsia Y , Kibler RD , Xu J , Bethel N , Nagarajan D , et al. Blueprinting expandable nanomaterials with standardized protein building blocks. bioRxiv. 2023;: 2023.06.09.544258. · DOI
- Lee S , Kibler RD , Hsia Y , Borst AJ , Philomin A , Kennedy MA , et al. Design of four component T=4 tetrahedral, octahedral, and icosahedral protein nanocages through programmed symmetry breaking. bioRxiv. 2023;: 2023.06.16.545341. · DOI
- Dowling QM , Park Y-J , Gerstenmaier N , Yang EC , Wargacki A , Hsia Y , et al. Hierarchical design of pseudosymmetric protein nanoparticles. bioRxiv. 2023;: 2023.06.16.545393. · DOI
- Watson JL , Juergens D , Bennett NR , Trippe BL , Yim J , Eisenach HE , et al. Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models. bioRxiv. 2022;: 2022.12.09.519842. · DOI · Paper page
- 2023, Top-down design of protein architectures with reinforcement learning, Science, 380, 266, 10.1126/science.adf6591 · DOI
- Ingraham J , Baranov M , Costello Z , Frappier V , Ismail A , Tie S et al. Illuminating protein space with a programmable generative model. bioRxiv. 2022;: 2022.12.01.518682. · DOI · Paper page
- Ingraham J , Garg VK , Barzilay R , Jaakkola T. Generative models for graph-based protein design. https://proceedings.neurips.cc/paper_files/paper/2019/file/f3a4ff4839c56a5f460c88cce3666a2b-Paper.pdf (accessed 14 Aug2023).
- Verkuil R , Kabeli O , Du Y , Wicky BIM , Milles LF , Dauparas J et al. Language models generalize beyond natural proteins. bioRxiv. 2022;: 2022.12.21.521521. · DOI · Paper page
- Anand N , Eguchi R , Mathews II , Perez CP , Derry A , Altman RB et al. Protein sequence design with a learned potential. Nat Commun 2022; 13: 746. · DOI · Paper page
- 10.1126/science.add2187 · DOI · Paper page
- 10.1038/nature25157 · DOI
- 10.1021/jacs.8b06442 · DOI
- 10.1038/s41467-020-19112-1 · DOI
- 10.1038/nature20607 · DOI
- 10.1016/j.cell.2023.06.013 · DOI
- 10.1126/science.aav7532 · DOI
- 10.1126/science.abd9994 · DOI
- 10.1073/pnas.1718825115 · DOI
- 10.1038/s41467-019-09836-0 · DOI
- Castells-Graells R , Meador K , Arbing MA , Sawaya MR , Gee M , Cascio D et al. Rigidified Scaffolds for 3 Angstrom Resolution Cryo-EM of Small Therapeutic Protein Targets. bioRxiv. 2022;: 2022.09.18.508009. · DOI
- 2020, Designed Protein Cages as Scaffolds for Building Multienzyme Materials, ACS Synth Biol, 9, 381, 10.1021/acssynbio.9b00407 · DOI
- 2023, Engineered repeat proteins as scaffolds to assemble multi-enzyme systems for efficient cell-free biosynthesis, Nat Commun, 14, 2587, 10.1038/s41467-023-38304-z · DOI
- 10.1021/acsnano.8b02805 · DOI
- 10.1038/s41467-019-12080-1 · DOI
- 10.7554/eLife.57659 · DOI
- 2021, Overcoming Symmetry Mismatch in Vaccine Nanoassembly through Spontaneous Amidation, Angew Chem Int Ed Engl, 60, 321, 10.1002/anie.202009663 · DOI
- 10.1126/science.abf6840 · DOI
- 2021, Elicitation of broadly protective sarbecovirus immunity by receptor-binding domain nanoparticle vaccines, Cell, 184, 5432, 10.1016/j.cell.2021.09.015 · DOI · Paper page
- 10.1016/j.cell.2019.01.046 · DOI
- 2021, Quadrivalent influenza nanoparticle vaccines induce broad protection, Nature, 592, 623, 10.1038/s41586-021-03365-x · DOI
- 10.1016/j.cell.2020.10.043 · DOI · Paper page
- Song JY , Choi WS , Heo JY , Lee JS , Jung DS , Kim S-W et al. Safety and immunogenicity of a SARS-CoV-2 recombinant protein nanoparticle vaccine (GBP510) adjuvanted with AS03: A randomised, placebo-controlled, observer-blinded phase 1/2 trial. EClinicalMedicine 2022; 51: 101569. · DOI
- 10.1016/j.eclinm.2023.102140 · DOI
- 10.1101/SQB.1962.027.001.005 · DOI
- 10.1006/jmbi.1997.1068 · DOI
- 10.1074/mcp.M900620-MCP200 · DOI · Paper page
- 10.1016/j.tim.2010.11.003 · DOI
- 10.1016/j.abb.2012.10.015 · DOI
- 2019, Polymorphic assembly of virus-capsid proteins around DNA and the cellular uptake of the resulting particles, J Control Release, 307, 342, 10.1016/j.jconrel.2019.06.019 · DOI
- Biela AP , Naskalska A , Fatehi F , Twarock R , Heddle JG . Programmable polymorphism of a virus-like particle. Commun Mater 2022; 3: 7. · DOI
- Seitz I , Kumpula E-P , Anaya-Plaza E , Cornelissen JJL , Linko V , Huiskonen JT et al. DNA origami directed virus capsid polymorphism. bioRxiv. 2022;: 2022.11.07.515152. · DOI
- 10.1038/s41594-019-0292-0 · DOI
- 10.1126/sciadv.aba8397 · DOI
- 10.1073/pnas.0803841105 · DOI
- 10.1126/science.1233936 · DOI
- 10.1073/pnas.1706825114 · DOI
- 10.1126/science.abg2822 · DOI
- 10.1073/pnas.041614998 · DOI
- 10.1038/nchem.2107 · DOI
- 10.1021/jacs.5b03593 · DOI
- 10.1126/science.1219351 · DOI
- 10.1073/pnas.2214556120 · DOI
- 2021, Design of multi-scale protein complexes by hierarchical building block fusion, Nat Commun, 12, 2294, 10.1038/s41467-021-22276-z · DOI
- 10.1038/nsb1194-789 · DOI
- 2020, Better together: Elements of successful scientific software development in a distributed collaborative community, PLoS Comput Biol, 16, e1007507, 10.1371/journal.pcbi.1007507 · DOI
- Guo H-B , Perminov A , Bekele S , Kedziora G , Farajollahi S , Varaljay V et al. AlphaFold2 models indicate that protein sequence determines both structure and dynamics. Sci Rep 2022; 12: 10696. · DOI · Paper page
- 10.3390/ijms23094591 · DOI · Paper page
- 2022, High-Resolution Native Mass Spectrometry, Chem Rev, 122, 7269, 10.1021/acs.chemrev.1c00212 · DOI · Paper page
- 2020, Resolving heterogeneous macromolecular assemblies by Orbitrap-based single-particle charge detection mass spectrometry, Nat Methods, 17, 395, 10.1038/s41592-020-0770-7 · DOI · Paper page
- 2023, Orbitrap-Based Mass and Charge Analysis of Single Molecules, Acc Chem Res, 56, 1458, 10.1021/acs.accounts.3c00079 · DOI
- He Y , Mao C . Balancing flexibility and stress in DNA nanostructures. Chem Commun 2006;: 968–969. · DOI
- 2017, Gigadalton-scale shape-programmable DNA assemblies, Nature, 552, 78, 10.1038/nature24651 · DOI
- 10.1016/S0959-440X(00)00189-5 · DOI
- Hamilton JR , Tsuchida CA , Nguyen DN , Shy BR , McGarrigle ER , Sandoval Espinoza CR et al. Targeted delivery of CRISPR-Cas9 and transgenes enables complex immune cell engineering. Cell Rep 2021; 35: 109207. · DOI
- 10.1017/S0033583507004635 · DOI · Paper page
- 10.1038/nmeth.1353 · DOI
- 10.1107/S0021889812048698 · DOI
- 10.1007/978-1-62703-691-7_18 · DOI
- 10.1016/j.bpj.2013.07.020 · DOI
- 10.1093/nar/gkw389 · DOI
- 10.1073/pnas.1404575111 · DOI
- 10.1002/pro.3967 · DOI
- 10.1038/nmeth.4193 · DOI
- 10.1016/j.jsb.2015.11.003 · DOI
- 10.1038/nmeth.4169 · DOI · Paper page
- 10.7554/eLife.42166 · DOI
- 10.1126/science.aar5839 · DOI
- 2020, ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution, J Chem Theory Comput, 16, 528, 10.1021/acs.jctc.9b00591 · DOI
- Roe DR , Brooks BR . A protocol for preparing explicitly solvated systems for stable molecular dynamics simulations. J Chem Phys 2020; 153: 054123. · DOI
- 10.1107/S0907444911049791 · DOI
- 10.1038/nmeth.3286 · DOI
- 10.7554/eLife.17219 · DOI · Paper page
- 2010, CaGe: a virtual environment for studying some special classes of plane graphs: an update, MATCH-COMMUNICATIONS IN MATHEMATICAL AND IN COMPUTER CHEMISTRY, 63, 533
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Sorted by citations
Atomically accurate de novo design of antibodies with RFdiffusion
Bennett, N. R., Watson, J. L., Ragotte, R. J., Borst, A. J., See, D. L., Weidle, C., Biswas, R., Yu, Y., Shrock, E. L., Ault, R., et al. (2024) · doi:10.1101/2024.03.14.585103 · Cited by 324
Self-citation
Metadata
- Authors
- Khmelinskaia, A., Bethel, N. P., Fatehi, F., Antanasijevic, A., Borst, A. J., Lai, S.-H., Wang, J. Y. (., Mallik, B. B., Miranda, M. C., Watkins, A. M., Ogohara, C., Caldwell, S., Wu, M., Heck, A. J. R., Veesler, D., Ward, A. B., Baker, D., Twarock, R., & King, N. P.
- Affiliations
- University of Bonn (DE)
- University of Washington (US)
- University of York (GB)
- Scripps Research Institute (US)
- Utrecht University (NL)
- Genentech (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Khmelinskaia, Alena
- King, Neil P.
- ORCID
- Venue
- Nature Structural & Molecular Biology
- Publisher
- openRxiv
- Published
- 2023-10-19
- Volume
- 32
- Issue
- 6
- Pages
- 1050-1060
- ISSN
- 1545-9985 (ISSN-L)
- PMC
- PMC12170342
- OpenAlex
- W4407988683
- Cited by
- 18
- References
- 2
- Citations by year
- 2026: 9 · 2025: 8 · 2024: 1
- FWCI
- 5.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Nature Structural & Molecular Biology (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- PubMed Central (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Funders
- National Science Foundation (1629214, P30 GM124169)
- Howard Hughes Medical Institute (GT11817)
- U.S. Department of Energy (180009, P30 GM124169, GM124169)
- Bill and Melinda Gates Foundation (INV-002916, INV-010680)
- amfAR, The Foundation for AIDS Research (110182-69-RKVA)
- University of Washington
- Wellcome Trust (110145, 110146, DP1AI158186)
- Open Philanthropy Project
- Australian Government
- Deutsche Forschungsgemeinschaft (SFB1032,)
- École Polytechnique Fédérale de Lausanne
- Bundesministerium für Bildung und Forschung
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (SPI.2017.028, ENPPS.LIFT.019.001)
- Engineering and Physical Sciences Research Council (EP/R023204/1)
- Leibniz-Gemeinschaft
- National Institute of General Medical Sciences (P30GM124169)
- National Institute of Allergy and Infectious Diseases (DP1AI158186, P01AI167966, 75N93022C00036, U54AI170856)
- Basic Energy Sciences
- Biological and Environmental Research (P30 GM124169)
- Lawrence Berkeley National Laboratory
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biochemical and Structural Characterization
- Physical Sciences › Materials Science › Biomaterials › Supramolecular Self-Assembly in Materials
- Keywords
- protein self-assembly, structural flexibility, structural diversity, protein architecture, native mass spectrometry, molecular dynamics simulation, protein design
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