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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.
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“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]
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MethodDevelopment and Analyses of a Database of Antibody – Antigen Complexes
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Chemical Biology: Here to Stay?
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Discovery of novel helix binding sites at protein-protein interfaces
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“For example, several successful de novo designs of protein binders from Baker’s group use helices as interface motifs, including protein binders targeting hemagglutinin [6], interleukin-2 and interleukin-5 [7], and botulinum neurotoxin B [8].”
BackgroundRosetta-Enabled Structural Prediction of Permissive Loop Insertion Sites in Proteins
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Accelerating therapeutic protein design
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Weidmann, L., Dijkstra, T. M. H., Kohlbacher, O., & Lupas, A. N. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/706119 · Cited by 6
A Complementarity‐Based Approach to De Novo Binder Design
Maksymenko, K., Hatskovska, V., Coles, M. P., Aghaallaei, N., Pashkovskaia, N., Borbarán‐Bravo, N., Pilz, M., Bucher, P., Volz, M., Pereira, J., et al. (2025) · Advanced Science · doi:10.1002/advs.202502015 · Cited by 5
De N ovo -Designed Miniprotein Inhibits the Enzymatic Activity of the SARS-CoV-2 Main Protease
de Lima, T. E., Moreira, E. G., Coêlho, D. F., da Cruz, C. H. B., Dhália, R., Leite, B. H. S., Xavier, L. S. S., Pérez-Illana, M., Wallau, G. L., Viana, I. F. T., et al. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c01708 · Cited by 5
Automated and modular protein binder design with BinderFlow
González-Rodríguez, N., González-Rodríguez, N., Llorca, Ó., & Fernández-Leiro, R. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013747 · Cited by 6
“It includes automatic filtering of suboptimal backbones and real-time monitoring of the process, allowing for stopping the campaign once a suitable number of hits is achieved. https://doi.org/10.1371/journal.pcbi.1013747.g001 from thousands to tens of thousands of candidates [10,12,17,22,30].”
InfluentialComputational design and improvement of a broad influenza virus HA stem targeting antibody
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Advances in protein engineering and its application in synthetic biology
Liu, R., Liang, L., Lacerda, M. P. F., Freed, E. F., & Eckert, C. A. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-824469-2.00013-0 · Cited by 7
Prediction of COMT Inhibitors Using Machine Learning and Molecular Dynamics Methods
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“30,33 Overall, the low efficacy against the ESBL/AmpC E. coli may be explained by the specificity of the phages that were not isolated on the target strains.”
Azar, L. M., Öncel, M. M., Karaman, E., Soysal, L. F., Fatima, A., Choi, S. B., Eyüpoğlu, A. E., Erman, B., Khan, A. M., & Uysal, S. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.07.022 · Cited by 5
“showed that small proteins, designed using computational approaches against influenza A H1 hemagglutinin provided therapeutic protection relative to antibodies due to their small size, high thermal stability, high neutralizing ability, low or no immunizing potential, and ease of heterologous expression for proper fold…”
BackgroundProBID-Net: a deep learning model for protein–protein binding interface design
Chen, Z., Ji, M., Qian, J., Zhang, Z., Zhang, X., Gao, H., Wang, H., Wang, R., & Qi, Y. (2024) · Chemical Science · doi:10.1039/d4sc02233e · Cited by 8
Intracellular delivery of proteins for live cell imaging
Jeong, B.-S., Kim, H. C., Sniezek, C. M., Berger, S., Kollman, J. M., Baker, D. A., Vaughan, J. C., & Gao, X. (2025) · Journal of Controlled Release · doi:10.1016/j.jconrel.2025.113651 · Cited by 5
Self-citationProtein design under competing conditions for the availability of amino acids
Nerattini, F., Tubiana, L., Cardelli, C., Bianco, V., Dellago, C., & Coluzza, I. (2020) · Scientific Reports · doi:10.1038/s41598-020-59401-9 · Cited by 5
Machine learning classifiers aid virtual screening for efficient design of mini-protein therapeutics
Gaur, N., Goyal, V. D., Kulkarni, K. A., & Makde, R. D. (2021) · Bioorganic & Medicinal Chemistry Letters · doi:10.1016/j.bmcl.2021.127852 · Cited by 5
iBRAB: In silico based-designed broad-spectrum Fab against H1N1 influenza A virus
Do, P.-C., Nguyen, T. H., Vo, U., & Le, L. (2020) · PLoS ONE · doi:10.1371/journal.pone.0239112 · Cited by 5
“ANTIGEN-BINDING FRAGMENTS No PDB ID Fab/Ab Heavy chain Light chain length (aa) chain length (aa) Chain 1 3QHZ 2D1 [17] 230 H 217 L 2 4GXV 1F1 [14] 231 I 217 M 3 4HKX CH67 [36] 231 A 214 B 4 4M5Y 5J8 [12] 233 I 214 M 5 4YK4 641 I-9 [35] 236 C 214 B 6 5UG0 H2897 [31] 232 D 216 C 7 5UGY CH65 [38] 227 H 210 L 8 5IBL 6639…”
Vergara, R., Wagner, J., Kamalian, P., Harman, J. L., Lara, N., Fischer, E. S., Bernardes, G. J. L., Quijano‐Rubio, A., & Silva, D. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.21.665742 · Cited by 5
“A total of 12 µg of purified DNA was combined with 4 µg of vector pETCON (pre-digested with NdeI and XhoI restriction enzymes) and transformed into electrocompetent EBY100 yeast cells as previously described [12].”
Self-citationProtein Design Meets Single-Molecule Detection: Towards Programmable Nanopore Sensors
Liu, X., & Xu, C. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms262110561 · Cited by 4
“High-affinity binders have already been successfully designed against highly challenging and clinically relevant targets, such as the neurotoxin and the SARS-CoV-2 receptor-binding domain (RBD), TNF-α , with affinities reaching the picomolar-to-nanomolar range [40,114–116].”
Polypeptides-Based Nanocarriers in Tumor Therapy
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“Chevalier et al. developed a computer modeling platform called “Rosetta” that reduced the total peptide library capacity to 22,660 and designed thousands of non-naturally derived peptides of about 40 amino acids in length [225].”
MethodPredicting protein secondary structure based on ensemble Neural Network
Dada, E. G., Oyewola, D. O., Yakubu, J. H., & Fadele, A. A. (2021) · ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA) · doi:10.5935/jetia.v7i27.732 · Cited by 4
“This method has been used productively to remodel different protein systems [4-8], and has an enormous capacity for the design and implementation of an innovative curative, globular protein and other beneficial proteins.”
Sharma, T., Mohapatra, S., Dash, R., Rath, B., & Sahoo, C. R. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90608-1.00004-6 · Cited by 4
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“With respect to the availability of general development methods, structure-based de novo design has proved useful for identifying the potent miniprotein inhibitors of various target proteins [15–17].”
BackgroundMethodInfluentialEngineered transcription factor-binding diversed functional nucleic acid-based synthetic biosensor
Liu, Y., Zhou, Z., Wu, Y., Wang, L., Cheng, J., Zhu, L., Dong, Y., Zheng, J., & Xu, W. (2024) · Biotechnology Advances · doi:10.1016/j.biotechadv.2024.108463 · Cited by 5
Protein engineering: a driving force toward synthetic immunology
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Computational Design of Miniprotein Binders
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A bottom-up approach for the de novo design of functional proteinsPreprint
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“The design of novel functional proteins is a fundamental test to our understanding of protein structure and function, and has enormous potential in multiple arenas in basic biology and biotechnology (7-15, 17).”
BackgroundResultInfluentialZhao, J., Zhang, C., & Luo, Y. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.11.579859 · Cited by 7
“Evolution has shaped natural proteins to perform vital functions in life science and address pressing applications ranging from developing targeted therapeutics 1 to engineering herbicide-resistant crops 2 and sustainable biocatalysis 3 .”
BackgroundAlpkilic, G. G., Huang, B., Liu, A., Kreuk, L. S. M., Wang, Y., Adebomi, V., Bueso, Y. F., Bera, A. K., Kang, A., Gerben, S., et al. (2025) · Angewandte Chemie · doi:10.1002/ange.202516058 · Cited by 3
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Self-citationAdvancing protein engineering via organic chemistry
Nithun, R. V., Singh, M., Baransi, A., & Jbara, M. (2026) · Communications Chemistry · doi:10.1038/s42004-026-02033-3 · Cited by 3
“The combination of de novo protein design with mirror image display provides a powerful strategy for generating novel D-protein binders for targeting natural proteins 86,87 .”
Saikia, B., & Baruah, A. (2024) · Soft Matter · doi:10.1039/d4sm00171k · Cited by 3
Designing de novo D-protein binders
Liu, H. (2024) · Cell Research · doi:10.1038/s41422-024-01029-9 · Cited by 3
Recombinant production of de novo designed miniprotein using various fusion protein tags
Khakerwala, Z., Gaikwad, S. S., Kumari, S., Gupta, G. D., & Makde, R. D. (2025) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2025.145041 · Cited by 3
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Computational Approaches for Identifying Therapeutic Potential of Phytocompounds
Ibrahim, J. M., Sukumaran, S., & Nair, A. S. (2023) · Sustainable development and biodiversity · doi:10.1007/978-981-19-5841-0_21 · Cited by 3
Tpgen: a language model for stable protein design with a specific topology structure
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“The introduction of multiple chemical functional groups into small proteins is a relatively straightforward process, enabling their potential utilization in therapeutic and diagnostic applications [25].”
BackgroundGenerative β-hairpin design using a residue-based physicochemical property landscape
Satalkar, V. B., Degaga, G. D., Li, W., Pang, Y. T., McShan, A. C., Gumbart, J. C., Mitchell, J. C., & Torres, M. P. (2024) · Biophysical Journal · doi:10.1016/j.bpj.2024.01.029 · Cited by 4
“De novo protein design is now used in an array of synthetic biology and biomedical applications for the creation of biomaterials and bioactive protein switches, in the treatment of viral infections, and in the modulation of im-muno-signaling pathways (3–13).”
Novack, D., Zhang, S., & Voelz, V. A. (2025) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5c00703 · Cited by 4
“[21] Starting from the predicted structural models of A8, A13 and A18 from Rosetta,[4] alchemical hybrid topologies were constructed for all possible single-residue mutations using pmx .”
InfluentialComputationally Designed Nanobinders as Affinity Ligands in Diagnostic and Therapeutic Applications
Jeon, J., Liu, Q. J., Woo, H., Barth, I., Choi, Y., Sang, L. J., & Lee, H. (2025) · Journal of the American Chemical Society · doi:10.1021/jacs.5c11289 · Cited by 3
Binder design for targeting SARS-CoV-2 spike protein: An in silico perspective
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“This previously was thought o to be impossible (Chevalier et al., 2017).”
Tenorio, C. A., Parker, J. B., & Blaber, M. (2022) · Protein Science · doi:10.1002/pro.4301 · Cited by 3
Engineering Antibodies and Alternative Binders for Therapeutic Uses
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Native state of natural proteins optimizes local entropy
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Integrative proteomics reveals exceptional diversity and versatility of mammalian humoral immunityPreprint
Xiang, Y., Sang, Z., Bitton, L., Xu, J., Liu, Y., Schneidman‐Duhovny, D., & Shi, Y. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.21.261917 · Cited by 3
“The development of cutting-edge tools that facilitate high-quality antibody analysis may also help advance novel antibody-based therapeutics and disease diagnostics (Baran et al., 2017 35; Chevalier et al., 2017; Sircar et al., 2011).”
BackgroundExploration of novel αβ-protein folds through de novo designPreprint
Minami, S., Kobayashi, N., Sugiki, T., Nagashima, T., Fujiwara, T., Koga, R., Chikenji, G., & Koga, N. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.06.455475 · Cited by 3
Template-based design of peptides to inhibit SARS-CoV-2 RNA-dependent RNA polymerase complexationPreprint
Chenna, A., Khan, W. H., Dash, R., Rathore, A. S., & Goel, G. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.01.24.477502 · Cited by 3
“To achieve high binding activity, the peptides must 199 fold into states that replicate the binding modes of the defined 200 template(47).”
BackgroundDe novo design of drug-binding proteins with predictable binding energy and specificityPreprint
Lu, L., Gou, X., Tan, S. K., Mann, S. I., Yang, H., Zhong, X., Gazgalis, D., Valdiviezo, J., Jo, H., Wu, Y., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.23.573178 · Cited by 3
“Finally, while MD simulations of de novo proteins ( 14 , 34 – 36 ) can help screen designs ( 14 , 34 – 36 ) , free energy calculations have not previously been applied to designed proteins.”
Majumdar, D., Hann, E., Short, K. R., Schat, K. A., & Challagulla, A. (2025) · Functional & Integrative Genomics · doi:10.1007/s10142-025-01777-w · Cited by 2
“Given that de novo proteins can be genetically encoded for intra-cellular expression, the possibility of transgenic expression remains unexplored (Chevalier et al. 2017; Quijano-Rubio et al. 2021).”
Kadam, R. U., Juraszek, J., Brandenburg, B., Garg, D., Zhu, X., Jongeneelen, M. A. C., Schepens, W. B. G., Stoops, B., Vermond, J., Goutier, W., et al. (2025) · npj Viruses · doi:10.1038/s44298-025-00166-1 · Cited by 2
Self-citationNonspecific Cellular Interactions Are a Key Determinant in the Disposition of Fc-Fused Proteins
Bryniarski, M. A., Wang, S., Chen, A., Coventry, B., Korkmaz, E. N., Tuhin, M. T. H., Ko, E. C., Wakefield, D. L., LaGory, E. L., Wu, H., et al. (2026) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.5c01228 · Cited by 4
Self-citationDe novo protein design: a transformative frontier in clinical protein applications
Gao, J., Zheng, Z., Yu, X., Luo, Y., Yu, Y., & Zhang, C. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-026-07784-0 · Cited by 3
Site-specific labelling of native peptides and proteins: chemical and enzymatic strategies
Luk, L. Y. P., Angelastro, A., Laserna, V., Bargh, J., & Guria, S. (2026) · Beilstein Journal of Organic Chemistry · doi:10.3762/bjoc.22.67 · Cited by 2
Computational Approaches to Investigate and Design Lipid-binding Domains for Membrane Biosensing
Srinivasan, S., & Vanni, S. (2021) · CHIMIA International Journal for Chemistry · doi:10.2533/chimia.2021.1031 · Cited by 2
High-throughput navigation of the sequence space
Choudhury, A. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-824469-2.00011-7 · Cited by 1
A sequence space search engine for computational protein design to modulate molecular functionality
Malik, A., Banerjee, A., Pal, A., & Mitra, P. (2022) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2022.2042386 · Cited by 2
“CPD is one of the most important protein engineering techniques widely used since the last few decades for the construction of biocatalysts (Bommarius & Paye, 2013) and pharmaceuticals (Chevalier et al., 2017; Fischman & Ofran, 2018).”
BackgroundPB-GPT: An innovative GPT-based model for protein backbone generation
Min, X., Liao, Y., Chen, X., Yang, Q., Ying, J., Zou, J., Yang, C., Zhang, J., Ge, S., & Xia, N. (2024) · Structure · doi:10.1016/j.str.2024.07.016 · Cited by 2
Design and characterization of defined alpha-helix mini-proteins with intrinsic cell permeability
Chen, X., Kong, X., Chen, P., Li, Z.-Q., Huang, N. J., Zhao, Z., Yang, J., Zhao, G., Mo, Q., Lu, Y., et al. (2024) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2024.108271 · Cited by 2
Self-citationKarmakar, T. (2025) · Resonance · doi:10.1007/s12045-025-1804-3 · Cited by 2
Ling, X., Cai, C., Kong, D., Wei, Z., Wu, J., Wang, L., & Deng, Z. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c00378 · Cited by 2
Finding a Silver Bullet in a Stack of Proteins
Makhlynets, O. V., & Korendovych, I. V. (2017) · Biochemistry · doi:10.1021/acs.biochem.7b01177 · Cited by 2
“Kalb SR, Santana WI, Geren IN, Garcia-Rodriguez C, Lou J, Smith TJ, Marks JD, Smith LA, Pirkle JL, Barr JR. Extraction and inhibition of enzymatic activity of botulinum neurotoxins /B1, /B2, / B3, /B4, and /B5 by a panel of monoclonal anti-BoNT/B antibodies.”
BackgroundInfluentialLi, R., Zhang, N.-N., Wu, B., OuYang, B., & Shen, H. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.04.046 · Cited by 2
“In our method, the PDB database was built from the RCSB PDB database [18] on the basis of several filter conditions: [1] Proteins are from Homo sapiens , [2] candidate structures are determined by X-ray diffraction, [3] resolution is better than 2.5 Å, [4] sequence identity cut-off is 40%.”
MethodInfluentialComputational Peptide Design for Diverse Structures and Functions
Rettie, S., Juergens, D., & Bhardwaj, G. (2025) · Peptide Science · doi:10.1002/9781119824701.ch05 · Cited by 2
Design of a dual-function agent by fusing a designed anti-VEGF-A binder and CPG-2 enzyme
Etemadi, A., Karimi‐Jafari, M. H., Negahdari, B., Asgari, Y., Khorramizadeh, M. R., Mohammadian, F., & Mazloomi, M. (2023) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2022.2162584 · Cited by 1
“Based on the methods mentioned by Chevalier et al. (2017), EBY100 yeast strain was transformed using 7 m g of the product and 3 m g of linearized pETcon vector (pETcon3).”
MethodInfluentialGeneralizable Metamaterials Design Techniques Inspire Efficient Mycelial Materials Inverse Design
Zavorskas, J., Edwards, H., Marten, M. R., Harris, S. D., & Srivastava, R. (2025) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.4c01986 · Cited by 2
Patat, A. S., & Nalbantoğlu, Ö. U. (2025) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.26810 · Cited by 1
Synthetic protein strategies for modulating ethylene pathways in crops and postharvest systems
Durojaye, O. A., Gonlepa, M. K., Ofuonye, C. G., & Osotuyi, T. B. (2025) · Discover Plants. · doi:10.1007/s44372-025-00449-0 · Cited by 1
“The field of protein engineering has undergone a paradigm shift with the advent of de novo design strategies that depart fundamentally from traditional modification approaches [50, 51].”
Data storage and retrieval with unnatural proteins expressed via E. coli
Zhou, Y., Ng, C. C. A., Liu, C., Tam, W. M., Lau, F. C. M., & Yao, Z. (2026) · Nature Communications · doi:10.1038/s41467-026-70061-7 · Cited by 1
“…based on the basic procedure of de novo design 19 , i.e., backbone sampling, sequence optimization, functional site design and scoring, proteins with designed functions, e.g., self-assembling biomaterials 20,21 , inhibitors for targeted therapeutics 22,23 and enzymes 24 , can be generated.”
Design of binder proteins specific to IL-13
Hu, Y., Weng, J., Chen, Y., Xing, B., Xiang, H., Zhao, W., & Wei, Z. (2026) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2026.151813 · Cited by 1
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De novo grafted coiled-coil peptides as p53/ h DM2 inhibitors
Spain, F., Giménez, D., Acevedo‐Jake, A. M., Mylemans, B., Brooks, N. J., Korona, B., Huang, D. T. C., Edwards, T. A., Leney, A. C., Itzhaki, L. S., et al. (2026) · RSC Chemical Biology · doi:10.1039/d6cb00063k · Cited by 1
Limitations of the ABEGO-based backbone design: ambiguity between αα-corner and αα-hairpin
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Design of stable circular permutants of the GroEL chaperone apical domain
Melnik, T. N., Majorina, M. A., Vorobeva, D. E., Nagibina, G. S., Veselova, V. R., Glukhova, K. A., Pak, M. A., Ivankov, D. N., Uversky, V. N., & Melnik, B. S. (2024) · Cell Communication and Signaling · doi:10.1186/s12964-023-01426-4 · Cited by 1
Synthetic Protein Nanoparticles via Photoreactive Electrohydrodynamic Jetting
Berardi, A. J., Francisco, S. D., Chang, A., Zelaya, J., Raymond, J. E., & Lahann, J. (2024) · Macromolecular Rapid Communications · doi:10.1002/marc.202400349 · Cited by 1
Incremental Inverse Design of Desired Soybean Phenotypes
Zavorskas, J., Edwards, H., Marten, M. R., Harris, S. D., & Srivastava, R. (2024) · ACS Omega · doi:10.1021/acsomega.4c01704 · Cited by 2
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Feature Design for Protein Interface Hotspots Using KFC2 and Rosetta
Seeger, F., Little, A. V., Chen, Y., Woolf, T., Cheng, H., & Mitchell, J. C. (2019) · Association for Women in Mathematics series · doi:10.1007/978-3-030-11566-1_8 · Cited by 1
Protein Nanostructures with Purpose-Designed Properties in Biotechnology and Medicine
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SeBPPI: A Sequence-Based Protein–Protein Binding Predictor
Wang, B., Mao, J. W., Wei, M., Qi, Y., & Zhang, J. Z. H. (2022) · Journal of Computational Biophysics and Chemistry · doi:10.1142/s2737416522500314 · Cited by 1
Wu, N. C., Thompson, A. J., Lee, J. M., Su, W., Arlian, B. M., Xie, J., Lerner, R. A., Yen, H., Bloom, J. D., & Wilson, I. A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.30.891135 · Cited by 1
“proteins, peptides and small molecules against influenza virus (14-18).”
BackgroundSelf-citationHuang, Z., Li, Z., Zhang, X., Dong, R., Kang, S., Sun, L., Fu, X., Vaisar, D., Watanabe, K., & Gu, L. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.09.174003 · Cited by 1
CMA-ES-Rosetta: Blackbox optimization algorithm traverses rugged peptide docking energy landscapesPreprint
Claussen, E. R., Renfrew, P. D., Müller, C. L., & Drew, K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.19.521113 · Cited by 1
“As the field of macromolecular modeling has expanded into a vast array of applications from protein structure prediction 1 to small molecule docking 2 to protein design 3 and more, new protocols have been developed in order to accommodate developers' needs 4 .”
BackgroundChen, F., Liu, Z., Kang, W. C. M., Jiang, F., Yang, X., Yin, F., & Li, Z. (2023) · Research Square · doi:10.21203/rs.3.rs-2969151/v1 · Cited by 1
“David Baker et al. used their Rosetta software to design a variety of proteins with unnatural structures or proteins with high a�nity to speci�c targets [52].”
MethodTopoDiff: Improving Protein Backbone Generation with Topology-aware Latent EncodingPreprint
Zhang, Y., Ma, Z., & Gong, H. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.13.571602 · Cited by 1
“…backbone and the corresponding sequence without involving naturally occurring proteins as starting points [1], which is an intriguing field of research with the potential to venture into unknown structure space, offering limitless opportunities for tailoring proteins to novel applications [2]–[7].”
BackgroundWäneskog, M., Hoch-Schneider, E. E., Garg, S., Cantalapiedra, C. K., Schaefer, E., Jensen, M. K., & Jensen, E. D. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.03.601847 · Cited by 1
Rybakowska, I. (2017)
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
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