Cited by 15Protein Structure and DynamicsBiochemical and Structural CharacterizationEnzyme Structure and Function

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Hallucination of closed repeat proteins containing central pockets

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Abstract

In pseudocyclic proteins, such as TIM barrels, β barrels, and some helical transmembrane channels, a single subunit is repeated in a cyclic pattern, giving rise to a central cavity that can serve as a pocket for ligand binding or enzymatic activity. Inspired by these proteins, we devised a deep-learning-based approach to broadly exploring the space of closed repeat proteins starting from only a specification of the repeat number and length. Biophysical data for 38 structurally diverse pseudocyclic designs produced in Escherichia coli are consistent with the design models, and the three crystal structures we were able to obtain are very close to the designed structures. Docking studies suggest the diversity of folds and central pockets provide effective starting points for designing small-molecule binders and enzymes.

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Research works printed but not linked: 30

  1. Nagano, N., Orengo, C. A. & Thornton, J. M. One fold with many functions: the evolutionary relationships between TIM barrel families based on their sequences, structures and functions. J. Mol. Biol. 321, 741–765 (2002). · DOI
  2. Park, K. et al. Control of repeat-protein curvature by computational protein design. Nat. Struct. Mol. Biol. 22, 167–174 (2015). · DOI
  3. Brunette, T. et al. Exploring the repeat protein universe through computational protein design. Nature 528, 580–584 (2015). · DOI
  4. Huang, P.-S. et al. De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy. Nat. Chem. Biol. 12, 29–34 (2016). · DOI
  5. Doyle, L. et al. Rational design of α-helical tandem repeat proteins with closed architectures. Nature 528, 585–588 (2015). · DOI
  6. Wicky, B. I. M. et al. Hallucinating symmetric protein assemblies. Science 378, 56–61 (2022). · DOI · Paper page
  7. Hura, G. L. et al. Robust, high-throughput solution structural analyses by small angle X-ray scattering (SAXS). Nat. Methods 6, 606–612 (2009). · DOI
  8. Dou, J. et al. De novo design of a fluorescence-activating β-barrel. Nature 561, 485–491 (2018). · DOI · Paper page
  9. Cao, L. et al. Design of protein-binding proteins from the target structure alone. Nature 605, 551–560 (2022). · DOI · Paper page
  10. Su, M. et al. Comparative assessment of scoring functions: the CASF-2016 update. J. Chem. Inf. Model. 59, 895–913 (2019). · DOI
  11. Basanta, B. et al. An enumerative algorithm for de novo design of proteins with diverse pocket structures. Proc. Natl Acad. Sci. USA 117, 22135–22145 (2020). · DOI
  12. Lipsh‐Sokolik, R., Listov, D. & Fleishman, S. J. The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes. Protein Sci. 30, 151–159 (2021). · DOI
  13. Polizzi, N. F. & DeGrado, W. F. A defined structural unit enables de novo design of small-molecule–binding proteins. Science 369, 1227–1233 (2020). · DOI
  14. Voynov, V., Chennamsetty, N., Kayser, V., Helk, B. & Trout, B. L. Predictive tools for stabilization of therapeutic proteins. mAbs 1, 580–582 (2009). · DOI
  15. Chaudhury, S., Lyskov, S. & Gray, J. J. PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta. Bioinforma. Oxf. Engl. 26, 689–691 (2010). · DOI
  16. Steinegger, M. & Söding, J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. Biotechnol. 35, 1026–1028 (2017). · DOI · Paper page
  17. Dong, R., Pan, S., Peng, Z., Zhang, Y. & Yang, J. mTM-align: a server for fast protein structure database search and multiple protein structure alignment. Nucleic Acids Res. https://doi.org/10.1093/nar/gky430 (2018). · DOI
  18. Groom, C. R., Bruno, I. J., Lightfoot, M. P. & Ward, S. C. The Cambridge Structural Database. Acta Crystallogr. B Struct. Sci. Cryst. Eng. Mater. 72, 171–179 (2016). · DOI · Paper page
  19. O’Boyle, N. M. et al. Open Babel: an open chemical toolbox. J. Cheminformatics 3, 33 (2011). · DOI
  20. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996). · DOI · Paper page
  21. Pettersen, E. F. et al. UCSF ChimeraX: structure visualization for researchers, educators, and developers. Protein Sci. 30, 70–82 (2021). · DOI
  22. Sharp, P. M. & Li, W.-H. The codon adaptation index—a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res. 15, 1281–1295 (1987). · DOI · Paper page
  23. Dang, B. et al. SNAC-tag for sequence-specific chemical protein cleavage. Nat. Methods 16, 319–322 (2019). · DOI
  24. Kabsch, W. XDS. Acta Crystallogr. D Biol. Crystallogr. 66, 125–132 (2010). · DOI · Paper page
  25. Minor, W., Cymborowski, M., Otwinowski, Z. & Chruszcz, M. HKL-3000: the integration of data reduction and structure solution — from diffraction images to an initial model in minutes. Acta Crystallogr. D Biol. Crystallogr. 62, 859–866 (2006). · DOI
  26. Winn, M. D. et al. Overview of the CCP 4 suite and current developments. Acta Crystallogr. D Biol. Crystallogr. 67, 235–242 (2011). · DOI · Paper page
  27. McCoy, A. J. et al. Phaser crystallographic software. J. Appl. Crystallogr. 40, 658–674 (2007). · DOI · Paper page
  28. Adams, P. D. et al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D. Biol. Crystallogr. 66, 213–221 (2010). · DOI · Paper page
  29. Emsley, P. & Cowtan, K. Coot: model-building tools for molecular graphics. Acta Crystallogr. D Biol. Crystallogr. 60, 2126–2132 (2004). · DOI · Paper page
  30. Williams, C. J. et al. MolProbity: More and better reference data for improved all-atom structure validation. Protein Sci. 27, 293–315 (2018). · DOI · Paper page

Metadata

Authors
An, L., Hicks, D. R., Zorine, D., Dauparas, J., Wicky, B. I. M., Milles, L. F., Courbet, A., Bera, A. K., Nguyen, H., Kang, A., Carter, L., & Baker, D.
Affiliations
  • University of Washington (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
An, Linna
Venue
Nature Structural & Molecular Biology
Published
2023-09-28
Volume
30
Issue
11
Pages
1755-1760
ISSN
  • 1545-9985 (ISSN-L)
  • 1545-9993
OpenAlex
W4387130982
Cited by
15
References
6
Citations by year
2026: 4 · 2025: 4 · 2024: 4 · 2023: 3
FWCI
1.34
Type
journal article
Language
en
Open access
Locations
  • Nature Structural & Molecular Biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion, cc-by)
Funders
  • U.S. Department of Defense (DE-AC02-06CH11357, DE-AC02-05CH11231)
  • Howard Hughes Medical Institute (DE-AC02-05CH11231)
  • U.S. Department of Energy (DE‐ AC02‐06CH11357, -AC02-05CH11231, Contract No. DE-AC02-05-CH11231, S10OD018483, AC02‐06CH11357, 05CH11231, P30 GM124169, No. DE-AC02-05-CH11231, P30 GM124165, DE AC02 05CH11231, 06CH11357, GM124169, DE-AC02-)
  • Washington Research Foundation (DE-AC02-06CH11357)
  • Open Philanthropy Project
  • National Energy Research Scientific Computing Center (DE–AC02–05CH11231, 05CH11231, AC02-05CH11231, Contract No. DE-AC02-05CH11231)
  • National Institutes of Health (1s10od018483-01, DE-AC02–05CH11231, DE-AC02–06CH11357, GM124165, GM124169)
  • Office of Science (P30 GM124165, No. DE-AC02- 05-CH11231, P30 GM124169, AC02‐06CH11357, DEAC02–05CH11231, AC02-05CH11231, DE-AC02, 05CH11231, 06CH11357, Contract No. DE-AC02-05CH11231, DE-AC02-06CH11357)
  • National Institute on Aging (U19AG065156)
  • National Institute of General Medical Sciences (DE-AC02-05CH11231, DE-AC02-06CH11357, GM124169, GM124165, S10OD018483, P30GM124169, P30GM124165)
  • Basic Energy Sciences (S10OD018483, DE-AC02, 05CH11231, DE-AC02-05CH11231., DE-AC- 02-06CH11357, AC02‐06CH11357, AC02–05CH11231, 06CH11357)
  • Biological and Environmental Research (05CH11231, DE-AC02 − 05CH11231, P30 GM124169, DEAC0206CH11357, S10OD018483, P30 GM124165, AC02-05CH11231)
  • Argonne National Laboratory (DE- AC02-06-CH11357, DE-AC02, AC02–06CH11357, DE-AC02-05CH11231, 06CH11357, P30 GM124165)
  • Lawrence Berkeley National Laboratory (AC02‐05CH11231, DE-AC02-05CH11231, S10OD018483, DE-AC02-06CH11357, 05CH11231)
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
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
Keywords
protein design, deep learning, TIM barrel, beta-barrel, central cavity, binding pocket, small-molecule binders, enzyme design, Escherichia coli, protein folding
MeSH terms
Hallucinations, Humans, Proteins

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