The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Massively parallel de novo protein design for targeted therapeutics
Open accessAbstract
De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37-43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains a challenge1–5.”
From Design of protein-binding proteins from the target structure alone (2022) · cites this paper as [1]
In the citing paper
“Most current computational methods used to design proteins that bind to a target surface utilize information derived from structures of the native complex on specific side-chain interactions or protein backbone placements optimal for binding1–3.”
From Design of protein-binding proteins from the target structure alone (2022) · cites this paper as [1]
In the citing paper
“Protein1,5, peptide36 and small-molecule inhibitors37 have been designed to bind to the stem region of group 1 HA and neutralize influenza A viruses, but none recognize the group 2 HA.”
From Design of protein-binding proteins from the target structure alone (2022) · cites this paper as [1]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Comparison of simple potential functions for simulating liquid water
Jorgensen, W. L., Chandrasekhar, J., Madura, J., Impey, R., & Klein, M. (1983) · The Journal of Chemical Physics · doi:10.1063/1.445869 · Cited by 38,397
[20] Processing of X-ray diffraction data collected in oscillation mode
Otwinowski, Z., & Minor, W. (1997) · Methods in Enzymology · doi:10.1016/s0076-6879(97)76066-x · Cited by 33,475
Coot : model-building tools for molecular graphics
Emsley, P., & Cowtan, K. (2004) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444904019158 · Cited by 30,571
A smooth particle mesh Ewald method
Essmann, U., Perera, L., Berkowitz, M., Darden, T., Lee, H.-C., & Pedersen, L. (1995) · The Journal of Chemical Physics · doi:10.1063/1.470117 · Cited by 21,378
Phaser crystallographic software
McCoy, A. J., Grosse-Kunstleve, R. W., Adams, P. D., Winn, M. D., Storoni, L. C., & Read, R. J. (2007) · Journal of Applied Crystallography · doi:10.1107/s0021889807021206 · Cited by 20,612
GROMACS: Fast, flexible, and free
van der Spoel, D., Lindahl, E. R., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. C. (2005) · Journal of Computational Chemistry · doi:10.1002/jcc.20291 · Cited by 19,461
Canonical sampling through velocity rescaling
Bussi, G., Donadio, D., & Parrinello, M. (2007) · The Journal of Chemical Physics · doi:10.1063/1.2408420 · Cited by 18,327
LINCS: A linear constraint solver for molecular simulations
Hess, B., Bekker, H., Berendsen, H. J. C., & Fraaije, J. G. E. M. (1997) · Journal of Computational Chemistry · doi:10.1002/(sici)1096-987x(199709)18:12 · Cited by 18,182
Kabsch, W. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909047337 · Cited by 16,463
MolProbity : all-atom structure validation for macromolecular crystallography
Chen, V. B., Arendall, W. B., Headd, J. J., Keedy, D. A., Immormino, R. M., Kapral, G. J., Murray, L. W., Richardson, J. S., & Richardson, D. C. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909042073 · Cited by 14,115
Improved side-chain torsion potentials for the Amber ff99SB protein force field
Lindorff-Larsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J., Dror, R., & Shaw, D. (2010) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.22711 · Cited by 6,056
PEAR: a fast and accurate Illumina Paired-End reAd mergeR
Zhang, J., Kobert, K., Flouri, T., & Stamatakis, A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt593 · Cited by 4,497
Free R value: a novel statistical quantity for assessing the accuracy of crystal structures
Brünger, A. T. (1992) · Nature · doi:10.1038/355472a0 · Cited by 3,877
Constant pressure molecular dynamics for molecular systems
Nosé, S., & Klein, M. L. (1983) · Molecular Physics · doi:10.1080/00268978300102851 · Cited by 3,402
Corti, D., Voss, J., Gamblin, S. J., Codoni, G., Macagno, A., Jarrossay, D., Vachieri, S. G., Pinna, D., Minola, A., Vanzetta, F., et al. (2011) · Science · doi:10.1126/science.1205669 · Cited by 1,203
Waskom, M., Botvinnik, O. B., O'Kane, D., Hobson, P., Ostblom, J., Lukauskas, S., Gemperline, D. C., Augspurger, T., Halchenko, Y., Cole, J. B., et al. (2014) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.592845 · Cited by 1,119
The Phenix software for automated determination of macromolecular structures
Adams, P. D., Afonine, P. V., Bunkòczi, G., Chen, V. B., Echols, N., Headd, J. J., Hung, L., Jain, S., Kapral, G. J., Grosse‐Kunstleve, R. W., et al. (2011) · Methods · doi:10.1016/j.ymeth.2011.07.005 · Cited by 915
Isolating and engineering human antibodies using yeast surface display
Chao, G., Lau, W. L., Hackel, B. J., Sazinsky, S. L., Lippow, S. M., & Wittrup, K. D. (2006) · Nature Protocols · doi:10.1038/nprot.2006.94 · Cited by 913
The Structure and Receptor Binding Properties of the 1918 Influenza Hemagglutinin
Gamblin, S. J., Haire, L. F., Russell, R. J., Stevens, D. J., Xiao, B., Ha, Y., Vasisht, N., Steinhauer, D. A., Daniels, R. S., Elliot, A. J., et al. (2004) · Science · doi:10.1126/science.1093155 · Cited by 710
RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite
Fleishman, S. J., Leaver‐Fay, A., Corn, J. E., Strauch, E., Khare, S. D., Koga, N., Ashworth, J. R., Murphy, P. M., Richter, F. M., Lemmon, G., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020161 · Cited by 659
Self-citationWatson, G. (1988) · Cited by 614
Computational Design of Proteins Targeting the Conserved Stem Region of Influenza Hemagglutinin
Fleishman, S. J., Whitehead, T. A., Ekiert, D. C., Dreyfus, C., Corn, J. E., Strauch, E.-M., Wilson, I. A., & Baker, D. (2011) · Science · doi:10.1126/science.1202617 · Cited by 585
Self-citationPrinciples for designing ideal protein structures
Koga, N., Tatsumi-Koga, R., Liu, G., Xiao, R., Acton, T. B., Montelione, G. T., & Baker, D. (2012) · Nature · doi:10.1038/nature11600 · Cited by 564
Self-citationDNAWorks: an automated method for designing oligonucleotides for PCR-based gene synthesis
Hoover, D. M. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.10.e43 · Cited by 517
Global analysis of protein folding using massively parallel design, synthesis, and testing
Rocklin, G. J., Chidyausiku, T. M., Goreshnik, I., Ford, A., Houliston, S., Lemak, A., Carter, L., Ravichandran, R., Mulligan, V. K., Chevalier, A., et al. (2017) · Science · doi:10.1126/science.aan0693 · Cited by 501
Self-citationAccurate de novo design of hyperstable constrained peptides
Bhardwaj, G., Mulligan, V. K., Bahl, C. D., Gilmore, J. M., Harvey, P. J., Cheneval, O., Buchko, G. W., Pulavarti, S. V. S. R. K., Kaas, Q., Eletsky, A., et al. (2016) · Nature · doi:10.1038/nature19791 · Cited by 445
Self-citationAn improved yeast transformation method for the generation of very large human antibody libraries
Benatuil, L., Perez, J. M., Belk, J., & Hsieh, C.-M. (2010) · Protein Engineering Design and Selection · doi:10.1093/protein/gzq002 · Cited by 435
RosettaRemodel: A Generalized Framework for Flexible Backbone Protein Design
Huang, P., Ban, Y. A., Richter, F. M., André, I., Vernon, R. M., Schief, W. R., & Baker, D. A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024109 · Cited by 371
Self-citationWhitehead, T. A., Chevalier, A. A., Song, Y., Dreyfus, C., Fleishman, S. J., de Mattos, C., Myers, C., Kamisetty, H., Blair, P. J., Wilson, I. A., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2214 · Cited by 367
Self-citationEngineered protein scaffolds as next-generation antibody therapeutics
Gebauer, M., & Skerra, A. (2009) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2009.04.627 · Cited by 339
Zahnd, C., Kawe, M., Stumpp, M. T., de Pasquale, C., Tamaskovic, R., Nagy‐Davidescu, G., Dreier, B., Schibli, R., Binz, H. K., Waibel, R., et al. (2010) · Cancer Research · doi:10.1158/0008-5472.can-09-2724 · Cited by 245
Challenges and opportunities for non-antibody scaffold drugs
Vazquez-Lombardi, R., Phan, T. G., Zimmermann, C., Lowe, D., Jermutus, L., & Christ, D. (2015) · Drug Discovery Today · doi:10.1016/j.drudis.2015.09.004 · Cited by 236
Botulinum neurotoxin B recognizes its protein receptor with high affinity and specificity
Jin, R., Rummel, A., Binz, T., & Brünger, A. T. (2006) · Nature · doi:10.1038/nature05387 · Cited by 235
Self-citationHurt, A. C., Chotpitayasunondh, T., Cox, N. J., Daniels, R. S., Fry, A. M., Gubareva, L. V., Hayden, F. G., Hui, D. S. C., Hungnes, O., Lackenby, A., et al. (2011) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(11)70318-8 · Cited by 229
Cass, L., Efthymiopoulos, C., & Bye, A. (1999) · Clinical Pharmacokinetics · doi:10.2165/00003088-199936001-00001 · Cited by 227
Spasmodic dysphonia and botulinum toxin: experience from the largest treatment series
Blitzer, A. (2010) · European Journal of Neurology · doi:10.1111/j.1468-1331.2010.03047.x · Cited by 138
Control over overall shape and size in de novo designed proteins
Lin, Y., Koga, N., Koga, R., Liu, G., Clouser, A. F., Montelione, G. T., & Baker, D. A. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1509508112 · Cited by 129
Self-citationProcko, E., Berguig, G. Y., Shen, B. W., Song, Y., Frayo, S., Convertine, A. J., Margineantu, D., Booth, G., Correia, B. E., Cheng, Y., et al. (2014) · Cell · doi:10.1016/j.cell.2014.04.034 · Cited by 127
Self-citationRemoving T-cell epitopes with computational protein design
King, C., Garza, E. N., Mazor, R., Linehan, J. L., Pastan, I. H., Pepper, M., & Baker, D. A. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1321126111 · Cited by 121
Self-citationEngineered knottin peptides as diagnostics, therapeutics, and drug delivery vehicles
Kintzing, J. R., & Cochran, J. R. (2016) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2016.08.022 · Cited by 118
Production of complex nucleic acid libraries using highly parallel in situ oligonucleotide synthesis
Cleary, M. A., Kilian, K. A., Wang, Y., Bradshaw, J., Cavet, G., Ge, W., Kulkarni, A., Paddison, P. J., Chang, K., Sheth, N. U., et al. (2004) · Nature Methods · doi:10.1038/nmeth724 · Cited by 108
Berger, S., Procko, E., Margineantu, D. H., Lee, E. F., Shen, B. W., Zelter, A., Silva, D., Chawla, K., Herold, M. J., Garnier, J.-M., et al. (2016) · eLife · doi:10.7554/elife.20352 · Cited by 94
Self-citationPRALINE: A Versatile Multiple Sequence Alignment Toolkit
Bawono, P., & Heringa, J. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-646-7_16 · Cited by 78
SwiftLib: rapid degenerate-codon-library optimization through dynamic programming
Jacobs, T. M., Yumerefendi, H., Kuhlman, B. A., & Leaver‐Fay, A. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1323 · Cited by 65
Motif-Driven Design of Protein–Protein Interfaces
Silva, D., Correia, B. E., & Procko, E. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-3569-7_17 · Cited by 57
Self-citationKoday, M. T., Nelson, J., Chevalier, A. A., Koday, M., Kalinoski, H. M., Stewart, L. J., Carter, L. P., Nieusma, T., Lee, P. S., Ward, A. B., et al. (2016) · PLoS Pathogens · doi:10.1371/journal.ppat.1005409 · Cited by 55
Self-citationWaskom, M., Botvinnik, O. B., drewokane, et al. (2016) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.54844 · Cited by 55
Protein engineering by highly parallel screening of computationally designed variants
Sun, M. G. F., Seo, M.-H., Nim, S., Corbi-Verge, C., & Kim, P. M. (2016) · Science Advances · doi:10.1126/sciadv.1600692 · Cited by 41
Structure of Botulinum neurotoxin B binding domain in complex with both synaptotagmin II and GD1a
Berntsson, R. P. ‐., Peng, L., Dong, M., & Stenmark, P. (2013) · Worldwide Protein Data Bank · doi:10.2210/pdb4kbb/pdb · Cited by 1
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Molecular Dynamics Simulation for All
Hollingsworth, S. A., & Dror, R. O. (2018) · Neuron · doi:10.1016/j.neuron.2018.08.011 · Cited by 3,522
Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2022) · doi:10.1101/2022.12.09.519842 · Cited by 2,369
Self-citationDe novo design of protein structure and function with RFdiffusion
Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2023) · Nature · doi:10.1038/s41586-023-06415-8 · Cited by 2,325
Self-citationAdvances in protein structure prediction and design
Kuhlman, B., & Bradley, P. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0163-x · Cited by 806
De novo design of picomolar SARS-CoV-2 miniprotein inhibitors
Cao, L., Goreshnik, I., Coventry, B., Case, J. B., Miller, L., Kozodoy, L., Chen, R. E., Carter, L., Walls, A. C., Park, Y.-J., et al. (2020) · Science · doi:10.1126/science.abd9909 · Cited by 742
Self-citation
Metadata
- Authors
- Chevalier, A., Silva, D.-A., Rocklin, G. J., Hicks, D. R., Vergara, R., Murapa, P., Bernard, S. M., Zhang, L., Lam, K.-H., Yao, G., Bahl, C. D., Miyashita, S.-I., Goreshnik, I., Fuller, J. T., Koday, M. T., Jenkins, C. M., Colvin, T., Carter, L., Bohn, A., Bryan, C. M., Fernández-Velasco, D. A., Stewart, L., Dong, M., Huang, X., Jin, R., Wilson, I. A., Fuller, D. H., & Baker, D.
- Affiliations
- University of Washington (US)
- Scripps Research Institute (US)
- Chinese Academy of Sciences (CN)
- University of California, Irvine (US)
- Boston Children's Hospital (US)
- Hong Kong University of Science and Technology (HK)
- Corresponding author
- Baker, David
- ORCID
- Chevalier, Aaron
- Silva, Daniel-Adriano
- Hicks, Derrick R.
- Vergara, Renan
- Murapa, Patience
- Bernard, Steffen M.
- Zhang, Lu
- Lam, Kwok-Ho
- Yao, Guorui
- Bahl, Christopher D.
- Miyashita, Shin-Ichiro
- Goreshnik, Inna
- Fuller, James T.
- Jenkins, Cody M.
- Carter, Lauren
- Bryan, Cassie M.
- Stewart, Lance
- Dong, Min
- Huang, Xuhui
- Jin, Rongsheng
- Wilson, Ian A.
- Fuller, Deborah H.
- Baker, David
- Venue
- Nature
- Published
- 2017-09-27
- Volume
- 550
- Issue
- 7674
- Pages
- 74-79
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5802399
- OpenAlex
- W2759860792
- Cited by
- 453
- References
- 48
- Citations by year
- 2026: 28 · 2025: 57 · 2024: 48 · 2023: 42 · 2022: 59 · 2021: 55 · 2020: 57 · 2019: 53 · 2018: 48 · 2017: 6
- FWCI
- 18.31
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology) (submittedVersion)
- Funders
- National Institutes of Health (1s10od021527-01, 5t32ai007354-30)
- National Institute of General Medical Sciences (P41GM103403)
- National Institute of Allergy and Infectious Diseases (R41AI122431, R01AI091823, R56AI127371, R56AI117675, R21AI119258, R33AI119258, R21AI123920, T32-AI007354., R01AI125704)
- National Institute of Neurological Disorders and Stroke (R01NS080833)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
- Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
- Keywords
- de novo protein design, miniproteins, protein binders, influenza haemagglutinin, botulinum neurotoxin B, oligonucleotide synthesis, protein stability, antiviral agents, prophylactic protection, antibody alternatives, immune response
- MeSH terms
- Botulinum Toxins, Computer Simulation, Hot Temperature, Humans, Influenza, Human, Protein Binding, Proteins, Temperature, Drug Design, Protein Engineering, Hemagglutinin Glycoproteins, Influenza Virus, Protein Stability, Molecular Dynamics Simulation, Molecular Targeted Therapy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
