Skip to content
naulon

No retraction, correction or concern found when last checked on Oct 30, 2026.

Design of protein-binding proteins from the target structure alone

Longxing Cao, Brian Coventry, Inna Goreshnik and 32 more

Nature · 2022

doi:10.1038/s41586-022-04654-9

Abstract

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 challenge 1–5 . Here we describe a general solution to this problem that starts with a broad exploration of the vast space of possible binding modes to a selected region of a protein surface, and then intensifies the search in the vicinity of the most promising binding modes. We demonstrate the broad applicability of this approach through the de novo design of binding proteins to 12 diverse protein targets with different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and, following experimental optimization, bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of five of the binder–target complexes, and all five closely match the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein–protein interactions, and should guide improvements of both. Our approach enables the targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.

Shown for reading. Its publisher allows quoting it, not republishing it.

References 89

  1. 1.

    Chevalier A, et al. Massively parallel de novo protein design for targeted therapeutics. Nature. 2017;550:74-79.

    Not in our library10.1038/nature23912

  2. 2.

    Strauch EM, et al. Computational design of trimeric influenza-neutralizing proteins targeting the hemagglutinin receptor binding site. Nat. Biotechnol. 2017;35:667-671.

    Not in our library10.1038/nbt.3907

  3. 3.

    Silva DA, et al. De novo design of potent and selective mimics of IL-2 and IL-15. Nature. 2019;565:186-191.

    Not in our library10.1038/s41586-018-0830-7

  4. 4.

    Baran D, et al. Principles for computational design of binding antibodies. Proc. Natl Acad. Sci. USA. 2017;114:10900-10905.

    Not in our library10.1073/pnas.1707171114

  5. 5.

    Fleishman SJ, et al. Computational design of proteins targeting the conserved stem region of influenza hemagglutinin. Science. 2011;332:816-821.

    Not in our library10.1126/science.1202617

  6. 6.

    Dou J, et al. De novo design of a fluorescence-activating β-barrel. Nature. 2018;561:485-491.

    Not in our library10.1038/s41586-018-0509-0

  7. 7.

    Koga N, et al. Principles for designing ideal protein structures. Nature. 2012;491:222-227.

    Not in our library10.1038/nature11600

  8. 8.

    Linsky, T. et al. Sampling of structure and sequence space of small protein folds. Preprint at bioRxiv10.1101/2021.03.10.434454 (2021).

    Not in our library

  9. 9.

    Maguire JB, et al. Perturbing the energy landscape for improved packing during computational protein design. Proteins. 2021;89:436-449.

    Not in our library10.1002/prot.26030

  10. 10.

    Rocklin GJ, et al. Global analysis of protein folding using massively parallel design, synthesis, and testing. Science. 2017;357:168-175.

    Not in our library10.1126/science.aan0693

  11. 11.

    Schneidman-Duhovny D, Inbar Y, Nussinov R, Wolfson HJ. PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic Acids Res. 2005;33:W363-W367.

    Not in our library10.1093/nar/gki481

  12. 12.

    Brunette TJ, et al. Modular repeat protein sculpting using rigid helical junctions. Proc. Natl Acad. Sci. USA. 2020;117:8870-8875.

    Not in our library10.1073/pnas.1908768117

  13. 13.

    Coventry B, Baker D. Protein sequence optimization with a pairwise decomposable penalty for buried unsatisfied hydrogen bonds. PLoS Comp. Biol. 2021;17:e1008061.

    Not in our library10.1371/journal.pcbi.1008061

  14. 14.

    Mackenzie CO, Zhou J, Grigoryan G. Tertiary alphabet for the observable protein structural universe. Proc. Natl Acad. Sci. USA. 2016;113:E7438-E7447.

    Not in our library10.1073/pnas.1607178113

  15. 15.

    Wiesmann C, Ultsch MH, Bass SH, de Vos AM. Crystal structure of nerve growth factor in complex with the ligand-binding domain of the TrkA receptor. Nature. 1999;401:184-188.

    Not in our library10.1038/43705

  16. 16.

    Plotnikov AN, Hubbard SR, Schlessinger J, Mohammadi M. Crystal structures of two FGF–FGFR complexes reveal the determinants of ligand-receptor specificity. Cell. 2000;101:413-424.

    Not in our library10.1016/s0092-8674(00)80851-x

  17. 17.

    Garrett TP, et al. Crystal structure of a truncated epidermal growth factor receptor extracellular domain bound to transforming growth factor α. Cell. 2002;110:763-773.

    Not in our library10.1016/s0092-8674(02)00940-6

  18. 18.

    Shim AH, et al. Structures of a platelet-derived growth factor/propeptide complex and a platelet-derived growth factor/receptor complex. Proc. Natl Acad. Sci. USA. 2010;107:11307-11312.

    Not in our library10.1073/pnas.1000806107

  19. 19.

    Croll TI, et al. Higher-resolution structure of the human insulin receptor ectodomain: multi-modal inclusion of the insert domain. Structure. 2016;24:469-476.

    Not in our library10.1016/j.str.2015.12.014

  20. 20.
  21. 21.

    Barton WA, et al. Crystal structures of the Tie2 receptor ectodomain and the angiopoietin-2–Tie2 complex. Nat. Struct. Mol. Biol. 2006;13:524-532.

    Not in our library10.1038/nsmb1101

  22. 22.

    McElroy CA, Dohm JA, Walsh ST. Structural and biophysical studies of the human IL-7/IL-7Rα complex. Structure. 2009;17:54-65.

    Not in our library10.1016/j.str.2008.10.019

  23. 23.

    Arnett KL, Harrison SC, Wiley DC. Crystal structure of a human CD3-ε/δ dimer in complex with a UCHT1 single-chain antibody fragment. Proc. Natl Acad. Sci. USA. 2004;101:16268-16273.

    Not in our library10.1073/pnas.0407359101

  24. 24.

    Radaev S, et al. Ternary complex of transforming growth factor-β1 reveals isoform-specific ligand recognition and receptor recruitment in the superfamily. J. Biol. Chem. 2010;285:14806-14814.

    Not in our library10.1074/jbc.m109.079921

  25. 25.

    Ekiert DC, et al. Cross-neutralization of influenza A viruses mediated by a single antibody loop. Nature. 2012;489:526-532.

    Not in our library10.1038/nature11414

  26. 26.

    Gillespie JJ, et al. Structural insight into how bacteria prevent interference between multiple divergent type IV secretion systems. mBio. 2015;6:e01867-15.

    Not in our library10.1128/mbio.01867-15

  27. 27.

    Birtalan S, et al. The intrinsic contributions of tyrosine, serine, glycine and arginine to the affinity and specificity of antibodies. J. Mol. Biol. 2008;377:1518-1528.

    Not in our library10.1016/j.jmb.2008.01.093

  28. 28.

    Lemmon MA, Schlessinger J. Cell signaling by receptor tyrosine kinases. Cell. 2010;141:1117-1134.

    Not in our library10.1016/j.cell.2010.06.011

  29. 29.

    Markovic I, Savvides SN. Modulation of signaling mediated by TSLP and IL-7 in inflammation, autoimmune diseases, and cancer. Front. Immunol. 2020;11:1557.

    Not in our library10.3389/fimmu.2020.01557

  30. 30.

    Webster RG, Bean WJ, Gorman OT, Chambers TM, Kawaoka Y. Evolution and ecology of influenza A viruses. Microbiol. Rev. 1992;56:152-179.

    Not in our library10.1128/mr.56.1.152-179.1992

  31. 31.

    Nobusawa E, et al. Comparison of complete amino acid sequences and receptor-binding properties among 13 serotypes of hemagglutinins of influenza A viruses. Virology. 1991;182:475-485.

    Not in our library10.1016/0042-6822(91)90588-3

  32. 32.

    Bullough PA, Hughson FM, Skehel JJ, Wiley DC. Structure of influenza haemagglutinin at the pH of membrane fusion. Nature. 1994;371:37-43.

    Not in our library10.1038/371037a0

  33. 33.

    Ekiert DC, et al. Antibody recognition of a highly conserved influenza virus epitope. Science. 2009;324:246-251.

    Not in our library10.1126/science.1171491

  34. 34.

    Corti D, et al. A neutralizing antibody selected from plasma cells that binds to group 1 and group 2 influenza A hemagglutinins. Science. 2011;333:850-856.

    Not in our library10.1126/science.1205669

  35. 35.

    Joyce MG, et al. Vaccine-induced antibodies that neutralize group 1 and group 2 influenza A viruses. Cell. 2016;166:609-623.

    Not in our library10.1016/j.cell.2016.06.043

  36. 36.

    Kadam RU, et al. Potent peptidic fusion inhibitors of influenza virus. Science. 2017;358:496-502.

    Not in our library10.1126/science.aan0516

  37. 37.

    van Dongen MJP, et al. A small-molecule fusion inhibitor of influenza virus is orally active in mice. Science. 2019;363:eaar6221.

    Not in our library10.1126/science.aar6221

  38. 38.
  39. 39.

    Case JB, et al. Ultrapotent miniproteins targeting the SARS-CoV-2 receptor-binding domain protect against infection and disease. Cell Host Microbe. 2021;29:1151-1161.

    Not in our library10.1016/j.chom.2021.06.008

  40. 40.

    Quijano-Rubio A, et al. De novo design of modular and tunable protein biosensors. Nature. 2021;591:482-487.

    Not in our library10.1038/s41586-021-03258-z

  41. 41.
  42. 42.

    Lim Y, et al. GC1118, an anti-EGFR antibody with a distinct binding epitope and superior inhibitory activity against high-affinity EGFR ligands. Mol. Cancer Ther. 2016;15:251-263.

    Not in our library10.1158/1535-7163.mct-15-0679

  43. 43.

    Zhang Y, Skolnick J. TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 2005;33:2302-2309.

    Not in our library10.1093/nar/gki524

  44. 44.

    Silva DA, Correia BE, Procko E. Motif-driven design of protein–protein interfaces. Methods Mol. Biol. 2016;1414:285-304.

    Not in our library10.1007/978-1-4939-3569-7_17

  45. 45.

    Leaver-Fay A, et al. ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules. Methods Enzymol. 2011;487:545-574.

    Not in our library10.1016/b978-0-12-381270-4.00019-6

  46. 46.

    Hoover DM, Lubkowski J. DNAWorks: an automated method for designing oligonucleotides for PCR-based gene synthesis. Nucleic Acids Res. 2002;30:e43.

    Not in our library10.1093/nar/30.10.e43

  47. 47.

    Benatuil L, Perez JM, Belk J, Hsieh CM. An improved yeast transformation method for the generation of very large human antibody libraries. Protein Eng.Des. Sel. 2010;23:155-159.

    Not in our library10.1093/protein/gzq002

  48. 48.

    Stevens J, et al. Structure of the uncleaved human H1 hemagglutinin from the extinct 1918 influenza virus. Science. 2004;303:1866-1870.

    Not in our library10.1126/science.1093373

  49. 49.

    Divine R, et al. Designed proteins assemble antibodies into modular nanocages. Science. 2021;372:eabd9994.

    Not in our library10.1126/science.abd9994

  50. 50.

    Xu Y, et al. Addressing polyspecificity of antibodies selected from an in vitro yeast presentation system: a FACS-based, high-throughput selection and analytical tool. Prot. Eng. Des. Sel. 2013;26:663-670.

    Not in our library10.1093/protein/gzt047

  51. 51.

    Otwinowski Z, Minor W. Processing of X-ray diffraction data collected in oscillation mode. Methods Enzymol. 1997;276:307-326.

    Not in our library10.1016/s0076-6879(97)76066-x

  52. 52.
  53. 53.

    McCoy AJ, Grosse-Kunstleve RW, Storoni LC, Read RJ. Likelihood-enhanced fast translation functions. Acta Crystallog. 2005;61:458-464.

    Not in our library10.1107/s0907444905001617

  54. 54.

    Adams PD, et al. PHENIX: building new software for automated crystallographic structure determination. Acta Crystallogr. 2002;58:1948-1954.

    Not in our library10.1107/s0907444902016657

  55. 55.

    Emsley P, Cowtan K. Coot: model-building tools for molecular graphics. Acta Crystallogr. 2004;60:2126-2132.

    Not in our library10.1107/s0907444904019158

  56. 56.
  57. 57.

    Wehrman T, et al. Structural and mechanistic insights into nerve growth factor interactions with the TrkA and p75 receptors. Neuron. 2007;53:25-38.

    Not in our library10.1016/j.neuron.2006.09.034

  58. 58.
    XDS · 2010
    No notice
  59. 59.

    Legrand, P. XDSME: XDS Made Easier. GitHubhttps://github.com/legrandp/xdsme (2017)

    Not in our library

  60. 60.
  61. 61.
  62. 62.
  63. 63.
  64. 64.
  65. 65.
  66. 66.
  67. 67.
  68. 68.

    Painter J, Merritt EA. Optimal description of a protein structure in terms of multiple groups undergoing TLS motion. Acta Crystallogr. 2006;62:439-450.

    Not in our library10.1107/s0907444906005270

  69. 69.

    Headd JJ, et al. Flexible torsion-angle noncrystallographic symmetry restraints for improved macromolecular structure refinement. Acta Crystallogr. 2014;70:1346-1356.

    Not in our library10.1107/s1399004714003277

  70. 70.

    Karplus PA, Diederichs K. Linking crystallographic model and data quality. Science. 2012;336:1030-1033.

    Not in our library10.1126/science.1218231

  71. 71.
  72. 72.

    Plotnikov AN, Schlessinger J, Hubbard SR, Mohammadi M. Structural basis for FGF receptor dimerization and activation. Cell. 1999;98:641-650.

    Not in our library10.1016/s0092-8674(00)80051-3

  73. 73.

    Schlessinger J, et al. Crystal structure of a ternary FGF–FGFR–heparin complex reveals a dual role for heparin in FGFR binding and dimerization. Mol. Cell. 2000;6:743-750.

    Not in our library10.1016/s1097-2765(00)00073-3

  74. 74.
  75. 75.
  76. 76.

    Williams CJ, et al. MolProbity: more and better reference data for improved all-atom structure validation. Protein Sci. 2018;27:293-315.

    Not in our library10.1002/pro.3330

  77. 77.
  78. 78.

    BUSTER v.2.10.2 (Global Phasing Ltd., 2016).

    Not in our library

  79. 79.
  80. 80.

    Evans P. Scaling and assessment of data quality. Acta Crystallogr. 2006;62:72-82.

    Not in our library10.1107/s0907444905036693

  81. 81.
  82. 82.

    Berman HM, et al. The Protein Data Bank. Nucleic Acids Res. 2000;28:235-242.

    Not in our library10.1093/nar/28.1.235

  83. 83.

    Berman H, Henrick K, Nakamura H. Announcing the worldwide Protein Data Bank. Nat. Struct. Biol. 2003;10:980.

    Not in our library10.1038/nsb1203-980

  84. 84.

    Grabowski M, et al. A public database of macromolecular diffraction experiments. Acta Crystallogr. 2016;72:1181-1193.

    Not in our library10.1107/s2059798316014716

  85. 85.

    Grabowski M, et al. The Integrated Resource for Reproducibility in Macromolecular Crystallography: experiences of the first four years. Struct. Dyn. 2019;6:064301.

    Not in our library10.1063/1.5128672

  86. 86.

    Hornakova T, et al. Acute lymphoblastic leukemia-associated JAK1 mutants activate the Janus kinase/STAT pathway via interleukin-9 receptor α homodimers. J. Biol. Chem. 2009;284:6773-6781.

    Not in our library10.1074/jbc.m807531200

  87. 87.
  88. 88.
  89. 89.

    Lauer TM, et al. Developability index: a rapid in silico tool for the screening of antibody aggregation propensity. J. Pharm. Sci. 2012;101:102-115.

    Not in our library10.1002/jps.22758

Cited by papers we hold 16

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.