Bottom-up de novo design of functional proteins with complex structural features

Nature Chemical Biology - Tập 17 Số 4 - Trang 492-500 - 2021
Che Yang1, Fabian Sesterhenn1, Jaume Bonet1, Eva A. van Aalen2, Leo Scheller1, Luciano A. Abriata3, Johannes Cramer4, Xiaolin Wen5, Stéphane Rosset3, Sandrine Georgeon1, Theodore S. Jardetzky5, Thomas Krey4, Martin Fussenegger6, Maarten Merkx2, Bruno E. Correia3
1Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
2Laboratory of Chemical Biology and Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
3Swiss Institute of Bioinformatics, Lausanne, Switzerland
4Institute of Virology, Hannover Medical School, Hannover, Germany
5Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
6Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland

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Kuhlman, B. et al. Design of a novel globular protein fold with atomic-level accuracy. Science 302, 1364–1368 (2003).

Brunette, T. J. et al. Exploring the repeat protein universe through computational protein design. Nature 528, 580–584 (2015).

Thomson, A. R. et al. Computational design of water-soluble alpha-helical barrels. Science 346, 485–488 (2014).

Marcos, E. et al. Principles for designing proteins with cavities formed by curved beta sheets. Science 355, 201–206 (2017).

Koga, N. et al. Principles for designing ideal protein structures. Nature 491, 222–227 (2012).

Pan, X. et al. Expanding the space of protein geometries by computational design of de novo fold families. Science 369, 1132–1136 (2020).

Dawson, W. M., Rhys, G. G. & Woolfson, D. N. Towards functional de novo designed proteins. Curr. Opin. Chem. Biol. 52, 102–111 (2019).

Correia, B. E. et al. Proof of principle for epitope-focused vaccine design. Nature 507, 201–206 (2014).

Sesterhenn, F. et al. Boosting subdominant neutralizing antibody responses with a computationally designed epitope-focused immunogen. PLoS Biol. 17, e3000164 (2019).

Sesterhenn, F. et al. De novo protein design enables the precise induction of RSV-neutralizing antibodies. Science 368, eaay5051 (2020).

Silva, D. A. et al. De novo design of potent and selective mimics of IL-2 and IL-15. Nature 565, 186–191 (2019).

Chevalier, A. et al. Massively parallel de novo protein design for targeted therapeutics. Nature 550, 74–79 (2017).

Boyken, S. E. et al. De novo design of tunable, pH-driven conformational changes. Science 364, 658–664 (2019).

Joh, N. H. et al. De novo design of a transmembrane Zn(2)(+)-transporting four-helix bundle. Science 346, 1520–1524 (2014).

Dou, J. et al. De novo design of a fluorescence-activating beta-barrel. Nature 561, 485–491 (2018).

Langan, R. A. et al. De novo design of bioactive protein switches. Nature 572, 205–210 (2019).

Silva, D. A., Correia, B. E. & Procko, E. Motif-driven design of protein–protein interfaces. Methods Mol. Biol. 1414, 285–304 (2016).

Procko, E. et al. A computationally designed inhibitor of an Epstein–Barr viral Bcl-2 protein induces apoptosis in infected cells. Cell 157, 1644–1656 (2014).

Berger, S. et al. Computationally designed high specificity inhibitors delineate the roles of BCL2 family proteins in cancer. eLife 5, 20352 (2016).

Correia, B. E. et al. Computational design of epitope-scaffolds allows induction of antibodies specific for a poorly immunogenic HIV vaccine epitope. Structure 18, 1116–1126 (2010).

Azoitei, M. L. et al. Computation-guided backbone grafting of a discontinuous motif onto a protein scaffold. Science 334, 373–376 (2011).

Holliday, G. L., Fischer, J. D., Mitchell, J. B. & Thornton, J. M. Characterizing the complexity of enzymes on the basis of their mechanisms and structures with a bio-computational analysis. FEBS J. 278, 3835–3845 (2011).

Jones, S. & Thornton, J. M. Principles of protein-protein interactions. Proc. Natl Acad. Sci. USA 93, 13–20 (1996).

Rubinstein, N. D. et al. Computational characterization of B-cell epitopes. Mol. Immunol. 45, 3477–3489 (2008).

Lechner, H., Ferruz, N. & Hocker, B. Strategies for designing non-natural enzymes and binders. Curr. Opin. Chem. Biol. 47, 67–76 (2018).

Burton, A. J., Thomson, A. R., Dawson, W. M., Brady, R. L. & Woolfson, D. N. Installing hydrolytic activity into a completely de novo protein framework. Nat. Chem. 8, 837–844 (2016).

Polizzi, N. F. et al. De novo design of a hyperstable non-natural protein-ligand complex with sub-A accuracy. Nat. Chem. 9, 1157–1164 (2017).

Bonet, J. et al. Rosetta FunFolDes—a general framework for the computational design of functional proteins. PLoS Comput. Biol. 14, e1006623 (2018).

McLellan, J. S. et al. Structure of a major antigenic site on the respiratory syncytial virus fusion glycoprotein in complex with neutralizing antibody 101F. J. Virol. 84, 12236–12244 (2010).

McLellan, J. S. et al. Structure of RSV fusion glycoprotein trimer bound to a prefusion-specific neutralizing antibody. Science 340, 1113–1117 (2013).

McLellan, J. S. et al. Structural basis of respiratory syncytial virus neutralization by motavizumab. Nat. Struct. Mol. Biol. 17, 248–250 (2010).

Fedechkin, S. O., George, N. L., Wolff, J. T., Kauvar, L. M. & DuBois, R. M. Structures of respiratory syncytial virus G antigen bound to broadly neutralizing antibodies. Sci. Immunol. 3, eaar3534 (2018).

Bonet, J., Harteveld, Z., Sesterhenn, F., Scheck, A. & Correia, B. E. rstoolbox – a Python library for large-scale analysis of computational protein design data and structural bioinformatics. BMC Bioinf. 20, 240 (2019).

Tian, D. et al. Structural basis of respiratory syncytial virus subtype-dependent neutralization by an antibody targeting the fusion glycoprotein. Nat. Commun. 8, 1877 (2017).

Ngwuta, J. O. et al. Prefusion F-specific antibodies determine the magnitude of RSV neutralizing activity in human sera. Sci. Transl. Med. 7, 309ra162 (2015).

Widjaja, I. et al. Characterization of epitope-specific anti-respiratory syncytial virus (Anti-RSV) antibody responses after natural infection and after vaccination with formalin-inactivated RSV. J. Virol. 90, 5965–5977 (2016).

Phung, E. et al. Epitope-specific serological assays for RSV: conformation matters. Vaccines 7, 23 (2019).

Graham, B. S., Gilman, M. S. A. & McLellan, J. S. Structure-based vaccine antigen design. Annu. Rev. Med. 70, 91–104 (2019).

Lee, P. S. & Wilson, I. A. Structural characterization of viral epitopes recognized by broadly cross-reactive antibodies. Curr. Top. Microbiol. Immunol. 386, 323–341 (2015).

Sesterhenn, F., Bonet, J. & Correia, B. E. Structure-based immunogen design-leading the way to the new age of precision vaccines. Curr. Opin. Struct. Biol. 51, 163–169 (2018).

Arts, R. et al. Detection of antibodies in blood plasma using bioluminescent sensor proteins and a smartphone. Anal. Chem. 88, 4525–4532 (2016).

Mousa, J. J. et al. Human antibody recognition of antigenic site IV on pneumovirus fusion proteins. PLoS Pathog. 14, 19 (2018).

Santorelli, M., Lam, C. & Morsut, L. Synthetic development: building mammalian multicellular structures with artificial genetic programs. Curr. Opin. Biotechnol. 59, 130–140 (2019).

Giordano-Attianese, G. et al. A computationally designed chimeric antigen receptor provides a small-molecule safety switch for T-cell therapy. Nat. Biotechnol. 38, 426–432 (2020).

Gainza-Cirauqui, P. & Correia, B. E. Computational protein design-the next generation tool to expand synthetic biology applications. Curr. Opin. Biotechnol. 52, 145–152 (2018).

Scheller, L., Strittmatter, T., Fuchs, D., Bojar, D. & Fussenegger, M. Generalized extracellular molecule sensor platform for programming cellular behavior. Nat. Chem. Biol. 14, 723–729 (2018).

Wood, C. W. et al. CCBuilder: an interactive web-based tool for building, designing and assessing coiled-coil protein assemblies. Bioinformatics 30, 3029–3035 (2014).

Crank, M. C. et al. A proof of concept for structure-based vaccine design targeting RSV in humans. Science 365, 505–509 (2019).

Taylor, W. R. A ‘periodic table’ for protein structures. Nature 416, 657–660 (2002).

Huang, P. S. et al. RosettaRemodel: a generalized framework for flexible backbone protein design. PLoS ONE 6, e24109 (2011).

Bhardwaj, G. et al. Accurate de novo design of hyperstable constrained peptides. Nature 538, 329–335 (2016).

Chao, G. et al. Isolating and engineering human antibodies using yeast surface display. Nat. Protoc. 1, 755–768 (2006).

Rohou, A. & Grigorieff, N. CTFFIND4: fast and accurate defocus estimation from electron micrographs. J. Struct. Biol. 192, 216–221 (2015).

de la Rosa-Trevin, J. M. et al. Scipion: a software framework toward integration, reproducibility and validation in 3D electron microscopy. J. Struct. Biol. 195, 93–99 (2016).

Scheres, S. H. RELION: implementation of a Bayesian approach to cryo-EM structure determination. J. Struct. Biol. 180, 519–530 (2012).

Kabsch, W. XDS. Acta Crystallogr. D. 66, 125–132 (2010).

Adams, P. D. et al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D. 66, 213–221 (2010).

Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D. 66, 486–501 (2010).