High thermodynamic stability of parametrically designed helical bundles
Open accessAbstract
We describe a procedure for designing proteins with backbones produced by varying the parameters in the Crick coiled coil-generating equations. Combinatorial design calculations identify low-energy sequences for alternative helix supercoil arrangements, and the helices in the lowest-energy arrangements are connected by loop building. We design an antiparallel monomeric untwisted three-helix bundle with 80-residue helices, an antiparallel monomeric right-handed four-helix bundle, and a pentameric parallel left-handed five-helix bundle. The designed proteins are extremely stable (extrapolated ΔGfold > 60 kilocalories per mole), and their crystal structures are close to those of the design models with nearly identical core packing between the helices. The approach enables the custom design of hyperstable proteins with fine-tuned geometries for a wide range of applications.
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The majority of de novo designed coiled coils are hyperstable, with melting points exceeding 100 °C.
“However, the majority of de novo designed coiled coils are hyperstable, with melting points exceeding 100 °C.11,12”
From Assessment of the Topology and Oligomerisation States of Coiled Coils Using Metadynamics with Conformational Restraints (2025) · cites this paper as [11]
The paper reports a designed helical bundle with no melting transition up to 130°C, supporting the existence of exceptionally stable designs (section labelled Abstract; page unavailable). It does not support the claim that a majority have melting points above 100°C: it identifies only two of nine tested designs as hyperstable, and reports stability only up to 95°C for several others. (LLM, conf=0.87)
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Cites
Features and development of Coot
Emsley, P., Lohkamp, B., Scott, W. G., & Cowtan, K. D. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444910007493 · Cited by 27,510 · see citing works
<i>PHENIX</i> : a comprehensive Python-based system for macromolecular structure solution
Adams, P. D., Afonine, P. V., Bunkóczi, G., Chen, V. B., Davis, I. W., Echols, N., Headd, J. J., Hung, L.-W., Kapral, G. J., Grosse-Kunstleve, R. W., et al. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909052925 · Cited by 23,716 · see citing works
<i>Phaser</i> 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 · see citing works
<i>MolProbity</i> : 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 · see citing works
REFMAC 5 for the refinement of macromolecular crystal structures
Murshudov, G. N., Skubák, P., Lebedev, A. A., Pannu, N. S., Steiner, R. A., Nicholls, R. A., Winn, M., Long, F., & Vagin, A. A. (2011) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444911001314 · Cited by 8,385 · see citing works
[14]Determination and analysis of urea and guanidine hydrochloride denaturation curves
Pace, C. N. (1986) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/0076-6879(86)31045-0 · Cited by 2,267 · see citing works
A Switch Between Two-, Three-, and Four-stranded Coiled Coils in GCN4 Leucine Zipper Mutants
Harbury, P. B., Zhang, T., Kim, P. S., & Alber, T. (1993) · Science · doi:10.1126/science.8248779 · Cited by 1,490 · see citing works
A New Generation of the IMAGIC Image Processing System
van Heel, M., Harauz, G., Orlova, E. V., Schmidt, R., & Schatz, M. X. (1996) · Journal of Structural Biology · doi:10.1006/jsbi.1996.0004 · Cited by 1,229 · see citing works
Macromolecular Modeling with Rosetta
Das, R., & Baker, D. A. (2008) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.77.062906.171838 · Cited by 995 · see citing works
Self-citationToward High-Resolution de Novo Structure Prediction for Small Proteins
Bradley, P. H., Misura, K. M. S., & Baker, D. A. (2005) · Science · doi:10.1126/science.1113801 · Cited by 865 · see citing works
Self-citationRosettaScripts: 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 · see citing works
Self-citationHigh-Resolution Protein Design with Backbone Freedom
Harbury, P. B., Plecs, J. J., Tidor, B., Alber, T., & Kim, P. S. (1998) · Science · doi:10.1126/science.282.5393.1462 · Cited by 458 · see citing works
ProTherm and ProNIT: thermodynamic databases for proteins and protein-nucleic acid interactions
Kumar, M. D. S. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj103 · Cited by 416 · see citing works
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 373 · see citing works
Self-citationThe Fourier transform of a coiled-coil
Crick, F. H. C. (1953) · Acta Crystallographica · doi:10.1107/s0365110x53001952 · Cited by 313 · see citing works
De NovoDesign of Helical Bundles as Models for Understanding Protein Folding and Function
Hill, R. B., Raleigh, D. P., Lombardi, A., & DeGrado, W. F. (2000) · Accounts of Chemical Research · doi:10.1021/ar970004h · Cited by 299 · see citing works
Improved molecular replacement by density- and energy-guided protein structure optimization
DiMaio, F., Terwilliger, T. C., Read, R. J., Wlodawer, A., Oberdorfer, G., Wagner, U. G., Valkov, E., Alon, A., Fass, D., Axelrod, H. L., et al. (2011) · Nature · doi:10.1038/nature09964 · Cited by 246 · see citing works
Self-citationProbing Designability via a Generalized Model of Helical Bundle Geometry
Grigoryan, G., & DeGrado, W. F. (2010) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.08.058 · Cited by 232 · see citing works
Liu, J., Zheng, Q., Deng, Y., Cheng, C.-S., Kallenbach, N. R., & Lu, M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0604871103 · Cited by 227 · see citing works
Computational Design of Virus-Like Protein Assemblies on Carbon Nanotube Surfaces
Grigoryan, G., Kim, Y. H., Acharya, R., Axelrod, K., Jain, R. M., Willis, L. J., Drndić, M., Kikkawa, J. M., & DeGrado, W. F. (2011) · Science · doi:10.1126/science.1198841 · Cited by 204 · see citing works
De novo designed peptides for biological applications
Boyle, A. L., & Woolfson, D. N. (2011) · Chemical Society Reviews · doi:10.1039/c0cs00152j · Cited by 192 · see citing works
A de novo peptide hexamer with a mutable channel
Zaccai, N. R., Chi, B., Thomson, A. R., Boyle, A. L., Bartlett, G. J., Bruning, M., Linden, N., Sessions, R. B., Booth, P. J., Brady, R. L., et al. (2011) · Nature Chemical Biology · doi:10.1038/nchembio.692 · Cited by 192 · see citing works
Improved low-resolution crystallographic refinement with Phenix and Rosetta
DiMaio, F., Echols, N., Headd, J. J., Terwilliger, T. C., Adams, P. D., & Baker, D. A. (2013) · Nature Methods · doi:10.1038/nmeth.2648 · Cited by 179 · see citing works
Self-citationphenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and Rosetta
Terwilliger, T. C., DiMaio, F., Read, R. J., Baker, D. A., Bunkòczi, G., Adams, P. D., Grosse‐Kunstleve, R. W., Afonine, P. V., & Echols, N. (2012) · Journal of Structural and Functional Genomics · doi:10.1007/s10969-012-9129-3 · Cited by 145 · see citing works
Self-citationHistorical review: Another 50th anniversary – new periodicities in coiled coils
Gruber, M. (2003) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2003.10.008 · Cited by 141 · see citing works
Peters, J., Baumeister, W. P., & Lupas, A. N. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0221 · Cited by 115 · see citing works
Sampling Bottlenecks in De novo Protein Structure Prediction
Kim, D. E., Blum, B., Bradley, P. H., & Baker, D. A. (2009) · Journal of Molecular Biology · doi:10.1016/j.jmb.2009.07.063 · Cited by 101 · see citing works
Self-citationBPPred: A Web‐based computational tool for predicting biophysical parameters of proteins
Geierhaas, C. D., Nickson, A. A., Lindorff‐Larsen, K., Clarke, J., & Vendruscolo, M. (2006) · Protein Science · doi:10.1110/ps.062383807 · Cited by 56 · see citing works
Conformational and geometrical properties of idealized β-barrels in proteins
Chou, K., Carlacci, L., & Maggiora, G. M. (1990) · Journal of Molecular Biology · doi:10.1016/s0022-2836(05)80193-7 · Cited by 47 · see citing works
Tyka, M. D., Jung, K., & Baker, D. A. (2012) · Journal of Computational Chemistry · doi:10.1002/jcc.23069 · Cited by 44 · see citing works
Self-citationA modifiedACORNto solve protein structures at resolutions of 1.7 Å or better
Jia-Xing, Y., Woolfson, M. M., Wilson, K. S., & Dodson, E. J. (2005) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s090744490502576x · Cited by 37 · see citing works
Nannenga, B. L., Iadanza, M. G., Vollmar, B. S., & Gonen, T. (2013) · Current Protocols in Protein Science · doi:10.1002/0471140864.ps1715s72 · Cited by 30 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 17
- [1]Boyle AL Woolfson DN Chem. Soc. Rev 2011 40 4295 4306 21373694
- [3]Gruber M Lupas AN Trends Biochem. Sci 2003 28 679 685 14659700
- [4]Hill RB Raleigh DP Lombardi A DeGrado WF Acc. Chem. Res 2000 33 745 754 11087311 PMC3050006
- [5]Harbury PB Zhang T Kim PS Alber T Science 1993 262 1401 1407 8248779
- [6]Liu J Proc. Natl. Acad. Sci. U.S.A 2006 103 15457 15462 17030805 PMC1622844
- [7]Zaccai NR Nat. Chem. Biol 2011 7 935 941 22037471 PMC3223406
- [8]Harbury PB Plecs JJ Tidor B Alber T Kim PS Science 1998 282 1462 1467 9822371
- [9]Grigoryan G Science 2011 332 1071 1076 21617073 PMC3264056
- [10]Das R Baker D Annu. Rev. Biochem 2008 77 363 382 18410248
- [11]Grigoryan G Degrado WF J. Mol. Biol 2011 405 1079 1100 20932976 PMC3052747
- [13]Huang PS PLOS ONE 2011 6 e24109 21909381 PMC3166072
- [14]Bradley P Misura KMS Baker D Science 2005 309 1868 1871 16166519
- [15]Pace CN Methods Enzymol 1986 131 266 280 3773761
- [16]Geierhaas CD Nickson AA Lindorff-Larsen K Clarke J Vendruscolo M Protein Sci 2007 16 125 134 17123959 PMC2222837
- [17]Kumar MD Nucleic Acids Res 2006 34 D204 D206 16381846 PMC1347465
- [18]Peters J Baumeister W Lupas A J. Mol. Biol 1996 257 1031 1041 8632466
- [19]Chou KC Carlacci L Maggiora GM J. Mol. Biol 1990 213 315 326 2342109
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Hsia, Y., Bale, J. B., Gonen, S., Shi, D., Sheffler, W., Fong, K. K., Nattermann, U., Xu, C., Huang, P., Ravichandran, R., et al. (2016) · Nature · doi:10.1038/nature18010 · Cited by 446 · see citing works
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Currin, A., Swainston, N., Day, P. J., & Kell, D. B. (2014) · Chemical Society Reviews · doi:10.1039/c4cs00351a · Cited by 384 · see citing works
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Zhu, J., Avakyan, N., Kakkis, A., Hoffnagle, A. M., Han, K., Li, Y., Zhang, Z., Choi, T. S., Na, Y., Yu, C.-J., et al. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00308 · Cited by 286 · see citing works
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Self-citationDesigned proteins assemble antibodies into modular nanocages
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Yeates, T. O. (2017) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-070816-033928 · Cited by 112 · see citing works
Understanding a protein fold: The physics, chemistry, and biology of α-helical coiled coils
Woolfson, D. N. (2023) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2023.104579 · Cited by 106 · see citing works
“Some allow coiled-coil backbones to be built quickly and accurately (28, 31), and others allow full atomistic modeling of coiled coils including side chains (29, 33, 35, 36).”
Design of stimulus-responsive two-state hinge proteins
Praetorius, F., Leung, P. J. Y., Tessmer, M. H., Broerman, A., Demakis, C., Dishman, A. F., Pillai, A., Idris, A., Juergens, D., Dauparas, J., et al. (2023) · Science · doi:10.1126/science.adg7731 · Cited by 90 · see citing works
Self-citationImmobilizing affinity proteins to nitrocellulose: a toolbox for paper-based assay developers
Holstein, C. A., Chevalier, A. A., Bennett, S. P., Anderson, C. E., Keniston, K., Olsen, C., Li, B., Bales, B., Moore, D. R., Fu, E. S., et al. (2015) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-015-9052-0 · Cited by 92 · see citing works
Self-citationDesign of multi-scale protein complexes by hierarchical building block fusion
Hsia, Y., Mout, R., Sheffler, W., Edman, N. I., Vulovic, I., Park, Y., Redler, R. L., Bick, M. J., Bera, A. K., Courbet, A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22276-z · Cited by 81 · see citing works
Self-citationComputational design of co-assembling protein–DNA nanowires
Mou, K. Y., Yu, J., Wannier, T. M., Guo, C., & Mayo, S. L. (2015) · Nature · doi:10.1038/nature14874 · Cited by 83 · see citing works
Bianchi, E., Capone, B., Ivan Coluzza, B., Rovigatti, L., & van Oostrum, P. D. J. (2017) · Physical Chemistry Chemical Physics · doi:10.1039/c7cp03149a · Cited by 80 · see citing works
The design of symmetric protein nanomaterials comes of age in theory and practice
Yeates, T. O., Liu, Y., & Laniado, J. (2016) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2016.07.003 · Cited by 81 · see citing works
Tertiary alphabet for the observable protein structural universe
Mackenzie, C. O., Zhou, J., & Grigoryan, G. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1607178113 · Cited by 72 · see citing works
Expanding the space of protein geometries by computational design of de novo fold families
Pan, X., Thompson, M. C., Zhang, S., Liu, L., Fraser, J. S., Kelly, M. J. S., & Kortemme, T. (2020) · Science · doi:10.1126/science.abc0881 · Cited by 76 · see citing works
Sun, J., Sun, W., Zhang, G., Lv, B., & Li, C. (2022) · Metabolic Engineering · doi:10.1016/j.ymben.2022.01.011 · Cited by 74 · see citing works
De Novo -Designed α-Helical Barrels as Receptors for Small Molecules
Thomas, F., Dawson, W., Lang, E. J. M., Burton, A. J., Bartlett, G. J., Rhys, G. G., Mulholland, A. J., & Woolfson, D. N. (2018) · ACS Synthetic Biology · doi:10.1021/acssynbio.8b00225 · Cited by 68 · see citing works
Towards functional de novo designed proteins
Dawson, W., Rhys, G. G., & Woolfson, D. N. (2019) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2019.06.011 · Cited by 69 · see citing works
Spatial Multiplexing of Fluorescent Reporters for Imaging Signaling Network Dynamics
Linghu, C., Johnson, S., Valdes, P. A., Shemesh, O. A., Park, W. M., Park, D., Piatkevich, K. D., Wassie, A. T., Liu, Y., An, B., et al. (2020) · Cell · doi:10.1016/j.cell.2020.10.035 · Cited by 69 · see citing works
Self-Assembly of an α-Helical Peptide into a Crystalline Two-Dimensional Nanoporous Framework
Magnotti, E. L., Hughes, S. A., Dillard, R. S., Wang, S., Hough, L., Karumbamkandathil, A., Lian, T. T., Wall, J. S., Zuo, X., Wright, E., et al. (2016) · Journal of the American Chemical Society · doi:10.1021/jacs.6b06592 · Cited by 71 · see citing works
Protein design via deep learning
Ding, W., Nakai, K., & Gong, H. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac102 · Cited by 66 · see citing works
De novo design of covalently constrained mesosize protein scaffolds with unique tertiary structures
Dang, B., Wu, H., Mulligan, V. K., Mravic, M., Wu, Y., Lemmin, T., Ford, A. C., Silva, D., Baker, D. A., & DeGrado, W. F. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1710695114 · Cited by 67 · see citing works
Self-citationBlueprinting extendable nanomaterials with standardized protein blocks
Huddy, T. F., Hsia, Y., Kibler, R. D., Xu, J., Bethel, N. P., Nagarajan, D., Redler, R. L., Leung, P. J. Y., Weidle, C., Courbet, A., et al. (2024) · Nature · doi:10.1038/s41586-024-07188-4 · Cited by 68 · see citing works
Self-citationBent into shape: Folded peptides to mimic protein structure and modulate protein function
Merritt, H. I., Sawyer, N., & Arora, P. S. (2020) · Peptide Science · doi:10.1002/pep2.24145 · Cited by 65 · see citing works
Mascali, F. C., Ching, H. Y. V., Rasia, R. M., Un, S., & Tabares, L. C. (2016) · Angewandte Chemie International Edition · doi:10.1002/anie.201603653 · Cited by 60 · see citing works
ISAMBARD: an open-source computational environment for biomolecular analysis, modelling and design
Wood, C. W., Heal, J. W., Thomson, A. R., Bartlett, G. J., Ibarra, A. Á., Brady, R. L., Sessions, R. B., & Woolfson, D. N. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx352 · Cited by 59 · see citing works
Computational design of protein self-assembly.
Norn, C. H., & André, I. (2016) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2016.04.002 · Cited by 53 · see citing works
Jiang, X., Ho, D. B. T., Mahe, K., Mia, J., Sepulveda, G., Antkowiak, M., Jiang, L., Yamada, S., & Jao, L.-E. (2021) · Journal of Cell Science · doi:10.1242/jcs.258897 · Cited by 57 · see citing works
Kobayashi, N., & Arai, R. (2017) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2017.01.001 · Cited by 56 · see citing works
Essentials of de novo protein design: Methods and applications
Marcos, E., & Silva, D. (2018) · Wiley Interdisciplinary Reviews Computational Molecular Science · doi:10.1002/wcms.1374 · Cited by 54 · see citing works
Computational protein design: a review
Ivan Coluzza, B. (2017) · Journal of Physics Condensed Matter · doi:10.1088/1361-648x/aa5c76 · Cited by 53 · see citing works
Maintaining and breaking symmetry in homomeric coiled-coil assemblies
Rhys, G. G., Wood, C. W., Lang, E. J. M., Mulholland, A., Brady, R. L., Thomson, A. R., & Woolfson, D. (2018) · Nature Communications · doi:10.1038/s41467-018-06391-y · Cited by 49 · see citing works
Unconventional secretion of α-synuclein mediated by palmitoylated DNAJC5 oligomers
Wu, S., Hernandez Villegas, N. C., Sirkis, D. W., Thomas-Wright, I., Wade-Martins, R., & Schekman, R. (2023) · eLife · doi:10.7554/elife.85837 · Cited by 52 · see citing works
Designing repeat proteins: a modular approach to protein design
Parmeggiani, F., & Huang, P. (2017) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2017.02.001 · Cited by 50 · see citing works
Self-citationA robust cosolvent-compatible halohydrin dehalogenase by computational library design
Arabnejad, H., Lago, M. D., Jekel, P. A., Floor, R. J., Thunnissen, A. M. W. H., van Scheltinga, A. C. T., Wijma, H. J., & Janssen, D. B. (2016) · Protein Engineering Design and Selection · doi:10.1093/protein/gzw068 · Cited by 50 · see citing works
Strategies for designing non-natural enzymes and binders
Lechner, H., Ferruz, N., & Höcker, B. (2018) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2018.07.022 · Cited by 49 · see citing works
A De Novo Designed Coiled-Coil Peptide with a Reversible pH-Induced Oligomerization Switch
Lizatović, R., Aurelius, O., Stenström, O., Drakenberg, T., Akke, M., Logan, D. T., & André, I. (2016) · Structure · doi:10.1016/j.str.2016.03.027 · Cited by 48 · see citing works
Navigating the Structural Landscape of De Novo α-Helical Bundles
Rhys, G. G., Wood, C. W., Beesley, J. L., Zaccai, N. R., Burton, A. J., Brady, R. L., Thomson, A. R., & Woolfson, D. N. (2019) · Journal of the American Chemical Society · doi:10.1021/jacs.8b13354 · Cited by 48 · see citing works
Self-Assembling 2D Arrays with de Novo Protein Building Blocks
Chen, Z., Johnson, M. C., Chen, J., Bick, M. J., Boyken, S. E., Lin, B., Yoreo, J. J. D., Kollman, J. M., Baker, D. A., & DiMaio, F. (2019) · Journal of the American Chemical Society · doi:10.1021/jacs.9b01978 · Cited by 48 · see citing works
Self-citationCovalently-assembled single-chain protein nanostructures with ultra-high stability
Bai, W., Sargent, C. J., Choi, J., Pappu, R. V., & Zhang, F. (2019) · Nature Communications · doi:10.1038/s41467-019-11285-8 · Cited by 48 · see citing works
High-resolution structures of a heterochiral coiled coil
Mortenson, D. E., Steinkruger, J. D., Kreitler, D. F., Perroni, D. V., Sorenson, G. P., Huang, L., Mittal, R., Yun, H. G., Travis, B. R., Mahanthappa, M. K., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1507918112 · Cited by 44 · see citing works
De novo design of transmembrane fluorescence-activating proteins
Zhu, J., Liang, M., Sun, K., Yu, W., Guo, R., Zhang, L., Shi, J., Ma, D., Hu, Q., Huang, G., et al. (2025) · Nature · doi:10.1038/s41586-025-08598-8 · Cited by 44 · see citing works
AI-driven de novo enzyme design: Strategies, applications, and future prospects
Cui, X.-C., Zheng, Y., Liu, Y., Yuchi, Z., & Yuan, Y. (2025) · Biotechnology Advances · doi:10.1016/j.biotechadv.2025.108603 · Cited by 44 · see citing works
Deploying synthetic coevolution and machine learning to engineer protein-protein interactions
Yang, A., Jude, K. M., Lai, B., Minot, M., Kocyła, A., Glassman, C. R., Nishimiya, D., Kim, Y. S., Reddy, S. T., Khan, A. A., et al. (2023) · Science · doi:10.1126/science.adh1720 · Cited by 41 · see citing works
Designed protein reveals structural determinants of extreme kinetic stability
Broom, A., Martha, S., Xia, K., Rafalia, H., Trainor, K., Colón, W., Gosavi, S., & Meiering, E. M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510748112 · Cited by 42 · see citing works
Peptide science: A “rule model” for new generations of peptidomimetics
Reese, H. R., Shanahan, C. C., Proulx, C., & Menegatti, S. (2019) · Acta Biomaterialia · doi:10.1016/j.actbio.2019.10.045 · Cited by 41 · see citing works
Ferruz, N., Lobos, F., Lemm, D., Toledo‐Patiño, S., Farías‐Rico, J. A., Schmidt, S., & Höcker, B. (2020) · Journal of Molecular Biology · doi:10.1016/j.jmb.2020.04.013 · Cited by 39 · see citing works
Antigen spacing on protein nanoparticles influences antibody responses to vaccination
Ellis, D., Dosey, A. M., Boyoglu-Barnum, S., Park, Y., Gillespie, R. A., Syeda, H., Hutchinson, G. B., Tsybovsky, Y., Murphy, M., Pettie, D., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113552 · Cited by 42 · see citing works
Metamaterials with magnetism and chirality
Tomita, S., Kurosawa, H., Ueda, T., & Sawada, K. B. (2018) · Journal of Physics D Applied Physics · doi:10.1088/1361-6463/aa9ecb · Cited by 40 · see citing works
Computational design and experimental verification of a symmetric protein homodimer
Mou, K. Y., Huang, P., Hsu, F.-C., Huang, S., & Mayo, S. L. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1505072112 · Cited by 38 · see citing works
Self-citationSynthetic Control of Tertiary Helical Structures in Short Peptides
Wuo, M. G., Hong, S. H., Singh, A., & Arora, P. S. (2018) · Journal of the American Chemical Society · doi:10.1021/jacs.8b10082 · Cited by 38 · see citing works
Robust folding of a de novo designed ideal protein even with most of the core mutated to valine
Koga, R., Yamamoto, M., Kosugi, T., Kobayashi, N., Sugiki, T., Fujiwara, T., & Koga, N. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2002120117 · Cited by 38 · see citing works
A particle size threshold governs diffusion and segregation of PAR-3 during cell polarization
Chang, Y., & Dickinson, D. J. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110652 · Cited by 37 · see citing works
Why reinvent the wheel? Building new proteins based on ready‐made parts
Khersonsky, O., & Fleishman, S. J. (2016) · Protein Science · doi:10.1002/pro.2892 · Cited by 36 · see citing works
N@a and N@d: Oligomer and Partner Specification by Asparagine in Coiled-Coil Interfaces
Fletcher, J. M., Bartlett, G. J., Boyle, A. L., Danon, J. J., Rush, L. E., Lupas, A. N., & Woolfson, D. N. (2016) · ACS Chemical Biology · doi:10.1021/acschembio.6b00935 · Cited by 35 · see citing works
Designing protein structures and complexes with the molecular modeling program Rosetta
Kuhlman, B. A. (2019) · Journal of Biological Chemistry · doi:10.1074/jbc.aw119.008144 · Cited by 36 · see citing works
Design of proteins presenting discontinuous functional sites using deep learningPreprint
Tischer, D., Lisanza, S. L., Wang, J., Dong, R., Anishchenko, I. V., Milles, L. F., Ovchinnikov, S., & Baker, D. A. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.29.402743 · Cited by 36 · see citing works
Self-citation
- Authors
- Huang, P.-S., Oberdorfer, G., Xu, C., Pei, X. Y., Nannenga, B. L., Rogers, J. M., DiMaio, F., Gonen, T., Luisi, B., & Baker, D.
- Affiliations
- University of Washington (US)
- University of Graz (AT)
- University of Cambridge (GB)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Huang, Po-Ssu
- Oberdorfer, Gustav
- Xu, Chunfu
- Baker, David
- ORCID
- Venue
- Science
- Published
- 2014-10-24
- Volume
- 346
- Issue
- 6208
- Pages
- 481-485
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC4612401
- OpenAlex
- W1976603396
- Cited by
- 277
- References
- 32
- Citations by year
- 2026: 17 · 2025: 17 · 2024: 16 · 2023: 22 · 2022: 24 · 2021: 28 · 2020: 23 · 2019: 29 · 2018: 15 · 2017: 30 · 2016: 37 · 2015: 17 · 2014: 2
- FWCI
- 11.76
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- U.S. Department of Energy (-AC02-05CH11231, 05CH11231, DE AC02 05CH11231, DE-AC02-)
- Wellcome Trust (076846)
- Diamond Light Source
- European Commission (332094)
- Directorate for Biological Sciences
- Biotechnology and Biological Sciences Research Council
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chemical Synthesis and Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biochemical and Structural Characterization
- Keywords
- protein design, helical bundle, coiled coil, thermodynamic stability, protein folding free energy, combinatorial designs
- MeSH terms
- Protein Denaturation, Thermodynamics, Protein Engineering, Protein Structure, Secondary, Crystallography, X-Ray, Combinatorial Chemistry Techniques
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