The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Computational Design of Proteins Targeting the Conserved Stem Region of Influenza Hemagglutinin
Open accessAbstract
Proteins can be designed that bind to specific patches on target proteins to alter their subsequent interactions.
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?
The cited source says what the claim attributes to it.
In the citing paper
“Binders have been generated starting from several computationally identified hotspot residues, which were then used to guide the positioning of naturally occurring protein scaffolds5.”
From Design of protein-binding proteins from the target structure alone (2022) · cites this paper as [5]
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 [5]
In the citing paper
“The RIF approach improves on previous discrete interaction-sampling approaches5 by reducing the algorithmic complexity from O(N) or O(N2) to O(1) with respect to the number of side-chain–target interactions considered, thereby allowing for billions, rather than thousands, of potential interfaces to be considered.”
From Design of protein-binding proteins from the target structure alone (2022) · cites this paper as [5]
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 [5]
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
PatchDock and SymmDock: servers for rigid and symmetric docking
Schneidman-Duhovny, D., Inbar, Y., Nussinov, R., & Wolfson, H. J. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki481 · Cited by 3,018
A Hot Spot of Binding Energy in a Hormone-Receptor Interface
Clackson, T., & Wells, J. A. (1995) · Science · doi:10.1126/science.7529940 · Cited by 1,987
The atomic structure of protein-protein recognition sites 1 1Edited by A. R. Fersht
Conte, L. L., Chothia, C., & Janin, J. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.2439 · Cited by 1,967
Design of a Novel Globular Protein Fold with Atomic-Level Accuracy
Kuhlman, B. A., Dantas, G. A., Ireton, G. C., Varani, G., Stoddard, B. L., & Baker, D. A. (2003) · Science · doi:10.1126/science.1089427 · Cited by 1,666
Self-citationAntibody Recognition of a Highly Conserved Influenza Virus Epitope
Ekiert, D. C., Bhabha, G., Elsliger, M.-A., Friesen, R. H. E., Jongeneelen, M., Throsby, M., Goudsmit, J., & Wilson, I. A. (2009) · Science · doi:10.1126/science.1171491 · Cited by 1,326
Self-citationGray, J. J., Moughon, S. E., Wang, C., Schueler‐Furman, O., Kuhlman, B. A., Rohl, C. A., & Baker, D. A. (2003) · Journal of Molecular Biology · doi:10.1016/s0022-2836(03)00670-3 · Cited by 1,130
Self-citationSui, J., Hwang, W. C., Perez, S., Ge, W., Aird, D. R., Chen, L., Santelli, E., Stec, B., Cadwell, G., Ali, M., et al. (2009) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1566 · Cited by 1,128
Clinical Aspects of Pandemic 2009 Influenza A (H1N1) Virus Infection
Writing Committee of the WHO Consultation on Clinical Aspects of Pandemic (H1N1) 2009 Influenza (2010) · New England Journal of Medicine · doi:10.1056/nejmra1000449 · Cited by 1,056
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
Self-citationIsolating 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
Cited by
Sorted by citations
The Protein-Folding Problem, 50 Years On
Dill, K. A., & MacCallum, J. L. (2012) · Science · doi:10.1126/science.1219021 · Cited by 1,699
The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design
Alford, R. F., Leaver-Fay, A., Jeliazkov, J. R., O’Meara, M. J., DiMaio, F. P., Park, H., Shapovalov, M. V., Renfrew, P. D., Mulligan, V. K., Kappel, K., et al. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00125 · Cited by 1,532
Self-citationHigh-Resolution Comparative Modeling with RosettaCM
Song, Y., DiMaio, F., Wang, R. Y., Kim, D. E., Miles, C., Brunette, T., Thompson, J., & Baker, D. A. (2013) · Structure · doi:10.1016/j.str.2013.08.005 · Cited by 1,102
Self-citationDeciphering interaction fingerprints from protein molecular surfaces using geometric deep learning
Gaínza, P., Sverrisson, F., Monti, F., Rodolà, E., Boscaini, D., Bronstein, M. M., & Correia, B. E. (2019) · Nature Methods · doi:10.1038/s41592-019-0666-6 · Cited by 839
Advances 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
How good is automated protein docking?
Kozakov, D., Beglov, D., Bohnuud, T., Mottarella, S. E., Xia, B., Hall, D. R., & Vajda, S. (2013) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24403 · Cited by 748
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-citationComputational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy
King, N. P., Sheffler, W., Sawaya, M. R., Vollmar, B. S., Sumida, J. P., André, I., Gonen, T., Yeates, T. O., & Baker, D. A. (2012) · Science · doi:10.1126/science.1219364 · Cited by 655
Self-citationDesign of protein-binding proteins from the target structure alone
Cao, L., Coventry, B., Goreshnik, I., Huang, B., Sheffler, W., Park, J. S., Jude, K. M., Marković, I., Kadam, R. U., Verschueren, K. H. G., et al. (2022) · Nature · doi:10.1038/s41586-022-04654-9 · Cited by 577
Self-citationCatalytic X–H insertion reactions based on carbenoids
Gillingham, D. G., & Fei, N. (2013) · Chemical Society Reviews · doi:10.1039/c3cs35496b · Cited by 594
Goldenzweig, A., Goldsmith, M., Hill, S. E., Gertman, O., Laurino, P., Ashani, Y., Dym, O., Unger, T., Albeck, S., Prilusky, J., et al. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.06.012 · Cited by 593
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-citationAccurate design of co-assembling multi-component protein nanomaterials
King, N. P., Bale, J. B., Sheffler, W., McNamara, D. E., Gonen, S., Gonen, T., Yeates, T. O., & Baker, D. A. (2014) · Nature · doi:10.1038/nature13404 · Cited by 560
Self-citationDe novo design of potent and selective mimics of IL-2 and IL-15
Silva, D.-A., Yu, S., Ulge, U. Y., Spangler, J. B., Jude, K. M., Labão-Almeida, C., Ali, L. R., Quijano-Rubio, A., Ruterbusch, M., Leung, I., et al. (2019) · Nature · doi:10.1038/s41586-018-0830-7 · Cited by 531
Self-citationOn the binding affinity of macromolecular interactions: daring to ask why proteins interact
Kastritis, P. L., & Bonvin, A. M. J. J. (2012) · Journal of The Royal Society Interface · doi:10.1098/rsif.2012.0835 · Cited by 547
Massively parallel de novo protein design for targeted therapeutics
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., et al. (2017) · Nature · doi:10.1038/nature23912 · Cited by 453
Self-citationKiss, G., Çelebi‐Ölçüm, N., Moretti, R., Baker, D. A., & Houk, K. N. (2013) · Angewandte Chemie International Edition · doi:10.1002/anie.201204077 · Cited by 501
Self-citationB-cell–lineage immunogen design in vaccine development with HIV-1 as a case study
Haynes, B. F., Kelsoe, G. H., Harrison, S. C., & Kepler, T. B. (2012) · Nature Biotechnology · doi:10.1038/nbt.2197 · Cited by 481
Cross-neutralization of influenza A viruses mediated by a single antibody loop
Ekiert, D. C., Kashyap, A. K., Steel, J., Rubrum, A. M., Bhabha, G., Khayat, R., Lee, J. H., Dillon, M. A., O’Neil, R. E., Faynboym, A. M., et al. (2012) · Nature · doi:10.1038/nature11414 · Cited by 488
Self-citationStructure-based design of non-natural amino-acid inhibitors of amyloid fibril formation
Sievers, S. A., Karanicolas, J., Chang, H. W., Zhao, A., Jiang, L., Zirafi, O., Stevens, J. T., Münch, J., Baker, D. A., & Eisenberg, D. S. (2011) · Nature · doi:10.1038/nature10154 · Cited by 472
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-citationBurton, D. R., Poignard, P., Stanfield, R. L., & Wilson, I. A. (2012) · Science · doi:10.1126/science.1225416 · Cited by 416
Self-citationImproving de novo protein binder design with deep learning
Bennett, N. R., Coventry, B., Goreshnik, I., Huang, B., Allen, A., Vafeados, D., Peng, Y. P., Dauparas, J., Baek, M., Stewart, L., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-38328-5 · Cited by 402
Self-citationJankauskaitė, J., Jiménez-García, B., Dapkūnas, J., Fernández-Recio, J., & Moal, I. H. (2019) · Bioinformatics · doi:10.1093/bioinformatics/bty635 · Cited by 389
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-citationmCSM-PPI2: predicting the effects of mutations on protein–protein interactions
Rodrigues, C. H. M., Myung, Y., Pires, D. E. V., & Ascher, D. B. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz383 · Cited by 369
Whitehead, 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-citationDe novo protein design—From new structures to programmable functions
Kortemme, T. (2024) · Cell · doi:10.1016/j.cell.2023.12.028 · Cited by 383
BeAtMuSiC: prediction of changes in protein–protein binding affinity on mutations
Dehouck, Y., Kwasigroch, J. M., Rooman, M., & Gilis, D. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt450 · Cited by 338
A protein engineered to bind uranyl selectively and with femtomolar affinity
Zhou, L., Bosscher, M. A., Zhang, C., Özçubukçu, S., Zhang, L., Zhang, W., Li, C. J., Liu, J., Jensen, M. P., Lai, L., et al. (2014) · Nature Chemistry · doi:10.1038/nchem.1856 · Cited by 339
Immune responses to influenza virus infection
Kreijtz, J. H. C. M., Fouchier, R. A. M., & Rimmelzwaan, G. F. (2011) · Virus Research · doi:10.1016/j.virusres.2011.09.022 · Cited by 335
The future of molecular dynamics simulations in drug discovery
Borhani, D. W., & Shaw, D. E. (2012) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-011-9517-y · Cited by 313
“The Rosetta molecular modeling approach, for instance, has proven to be very powerful (see, e.g., [95, 96]).”
MethodA Pareto-Optimal Refinement Method for Protein Design Scaffolds
Nivón, L. G., Moretti, R., & Baker, D. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059004 · Cited by 295
Self-citationDesign of a single-chain polypeptide tetrahedron assembled from coiled-coil segments
Gradišar, H., Abram, S. B., Doles, T., Vengust, D., Hafner‐Bratkovič, I., Mertelj, A., Webb, B., Šali, A., Klavžar, S., & Jerala, R. (2013) · Nature Chemical Biology · doi:10.1038/nchembio.1248 · Cited by 312
De novo design of protein homo-oligomers with modular hydrogen-bond network–mediated specificity
Boyken, S. E., Chen, Z., Groves, B., Langan, R. A., Oberdorfer, G., Ford, A., Gilmore, J. M., Xu, C., DiMaio, F., Pereira, J. H., et al. (2016) · Science · doi:10.1126/science.aad8865 · Cited by 303
Self-citationBarlow, K. A., Conchúir, S. Ó., Thompson, S., Suresh, P., Lucas, J. E., Heinonen, M., & Kortemme, T. (2018) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.7b11367 · Cited by 307
Moal, I. H., & Fernández-Recio, J. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts489 · Cited by 281
Deep learning methods in protein structure prediction
Torrisi, M., Pollastri, G., & Le, Q. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2019.12.011 · Cited by 297
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 288
Principles of Protein Stability and Their Application in Computational Design
Goldenzweig, A., & Fleishman, S. J. (2018) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-062917-012102 · Cited by 291
Self-citationCademartiri, L., & Bishop, K. J. M. (2014) · Nature Materials · doi:10.1038/nmat4184 · Cited by 277
Fletcher, J. M., Boyle, A. L., Bruning, M., Bartlett, G. J., Vincent, T. L., Zaccai, N. R., Armstrong, C. T., Bromley, E. H. C., Booth, P. J., Brady, R. L., et al. (2012) · ACS Synthetic Biology · doi:10.1021/sb300028q · Cited by 262
Defining B cell immunodominance to viruses
Angeletti, D., Gibbs, J. S., Angel, M., Košík, I., Hickman, H. D., Frank, G. M., Das, S. R., Wheatley, A. K., Prabhakaran, M. S., Leggat, D. J., et al. (2017) · Nature Immunology · doi:10.1038/ni.3680 · Cited by 257
Tiller, K. E., & Tessier, P. M. (2015) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071114-040733 · Cited by 270
Influenza Hemagglutinin Structures and Antibody RecognitionPreprint
Wu, N. C., & Wilson, I. A. (2019) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a038778 · Cited by 253
Self-citationDocking, scoring, and affinity prediction in CAPRI
Lensink, M. F., & Wodak, S. J. (2013) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24428 · Cited by 249
Integrative, dynamic structural biology at atomic resolution—it's about time
Bedem, H. V. D., & Fraser, J. S. (2015) · Nature Methods · doi:10.1038/nmeth.3324 · Cited by 246
De novo design of protein interactions with learned surface fingerprints
Gaínza, P., Wehrle, S., Hall‐Beauvais, A. V., Marchand, A., Scheck, A., Harteveld, Z., Buckley, S., Ni, D., Tan, S., Sverrisson, F., et al. (2023) · Nature · doi:10.1038/s41586-023-05993-x · Cited by 266
Stranges, P. B., & Kuhlman, B. A. (2012) · Protein Science · doi:10.1002/pro.2187 · Cited by 233
Combined Covalent-Electrostatic Model of Hydrogen Bonding Improves Structure Prediction with Rosetta
O’Meara, M. J., Leaver‐Fay, A., Tyka, M. D., Stein, A., Houlihan, K., DiMaio, F., Bradley, P. H., Kortemme, T., Baker, D. A., Snoeyink, J. S., et al. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/ct500864r · Cited by 233
Self-citationRey, F. A., & Lok, S. (2018) · Cell · doi:10.1016/j.cell.2018.02.054 · Cited by 234
Analyses of the Effects of All Ubiquitin Point Mutants on Yeast Growth Rate
Roscoe, B. P., Thayer, K. M., Zeldovich, K. B., Fushman, D., & Bolon, D. N. A. (2013) · Journal of Molecular Biology · doi:10.1016/j.jmb.2013.01.032 · Cited by 231
RosettaAntibodyDesign (RAbD): a general framework for computational antibody design
Adolf-Bryfogle, J., Kalyuzhniy, O., Kubitz, M., Weitzner, B. D., Hu, X., Adachi, Y., Schief, W. R., & Dunbrack, R. L. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006112 · Cited by 227
Computation-Guided Backbone Grafting of a Discontinuous Motif onto a Protein Scaffold
Azoitei, M. L., Correia, B. E., Ban, Y.-E. A., Carrico, C., Kalyuzhniy, O., Chen, L., Schroeter, A., Huang, P.-S., McLellan, J. S., Kwong, P. D., et al. (2011) · Science · doi:10.1126/science.1209368 · Cited by 224
Self-citationLee, P. S., Ohshima, N., Stanfield, R. L., Yu, W., Iba, Y., Okuno, Y., Kurosawa, Y., & Wilson, I. A. (2014) · Nature Communications · doi:10.1038/ncomms4614 · Cited by 211
Self-citationDe novo protein design enables the precise induction of RSV-neutralizing antibodies
Sesterhenn, F., Yang, C., Bonet, J., Cramer, J. T., Wen, X., Wang, Y., Chiang, C.-I., Abriata, L. A., Kucharska, I., Castoro, G., et al. (2020) · Science · doi:10.1126/science.aay5051 · Cited by 191
Protocols for Molecular Modeling with Rosetta3 and RosettaScripts
Bender, B. J., Cisneros, A., Duran, A. M., Finn, J. A., Fu, D., Lokits, A. D., Mueller, B. K., Sangha, A. K., Sauer, M. F., Sevy, A. M., et al. (2016) · Biochemistry · doi:10.1021/acs.biochem.6b00444 · Cited by 202
Opportunities and challenges in design and optimization of protein function
Listov, D., Goverde, C. A., Correia, B. E., & Fleishman, S. J. (2024) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-024-00718-y · Cited by 212
Self-citationAssessment of template based protein structure predictions in CASP9
Mariani, V., Kiefer, F., Schmidt, T., Haas, J., & Schwede, T. F. (2011) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.23177 · Cited by 183
Hot spots in protein–protein interfaces: Towards drug discovery
Cukuroglu, E., Engin, H. B., Gürsoy, A., & Keskin, Ö. (2014) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2014.06.003 · Cited by 184
Multiscale methods in drug design bridge chemical and biological complexity in the search for cures
Amaro, R. E., & Mulholland, A. J. (2018) · Nature Reviews Chemistry · doi:10.1038/s41570-018-0148 · Cited by 175
Wu, N. C., & Wilson, I. A. (2017) · Journal of Molecular Biology · doi:10.1016/j.jmb.2017.06.015 · Cited by 176
Self-citationSelf-assembly of genetically encoded DNA-protein hybrid nanoscale shapes
Praetorius, F., & Dietz, H. (2017) · Science · doi:10.1126/science.aam5488 · Cited by 174
Improving carbon fixation pathways
Ducat, D. C., & Silver, P. A. (2012) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2012.05.002 · Cited by 172
Computational design of a protein crystal
Lanci, C. J., MacDermaid, C. M., Kang, S.-G., Acharya, R., North, B., Yang, X., Qiu, X. J., DeGrado, W. F., & Saven, J. G. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1112595109 · Cited by 170
Beigel, J. H., Nam, H. H., Adams, P. L., Krafft, A. E., Ince, W. L., El‐Kamary, S. S., & Sims, A. M. (2019) · Antiviral Research · doi:10.1016/j.antiviral.2019.04.006 · Cited by 168
Potent peptidic fusion inhibitors of influenza virus
Kadam, R. U., Juraszek, J., Brandenburg, B., Buyck, C., Schepens, W. B. G., Kesteleyn, B., Stoops, B., Vreeken, R. J., Vermond, J., Goutier, W., et al. (2017) · Science · doi:10.1126/science.aan0516 · Cited by 165
Self-citationProtein folding and de novo protein design for biotechnological applications
Khoury, G. A., Smadbeck, J. B., Kieslich, C. A., & Floudas, C. A. (2013) · Trends in biotechnology · doi:10.1016/j.tibtech.2013.10.008 · Cited by 162
Broadly neutralizing antibodies against influenza viruses
Laursen, N. S., & Wilson, I. A. (2013) · Antiviral Research · doi:10.1016/j.antiviral.2013.03.021 · Cited by 153
Self-citationAntibody Recognition of the Pandemic H1N1 Influenza Virus Hemagglutinin Receptor Binding Site
Hong, M., Lee, P. S., Hoffman, R. M. B., Zhu, X., Krause, J. C., Laursen, N. S., Yoon, S., Song, L., Tussey, L., Crowe, J. E., et al. (2013) · Journal of Virology · doi:10.1128/jvi.01388-13 · Cited by 152
Self-citationFully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand
DeLuca, S., Khar, K. R., & Meiler, J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0132508 · Cited by 150
Broadly neutralizing antibodies against influenza virus and prospects for universal therapies
Ekiert, D. C., & Wilson, I. A. (2012) · Current Opinion in Virology · doi:10.1016/j.coviro.2012.02.005 · Cited by 150
Self-citationPrinciples for computational design of binding antibodies
Baran, D., Pszolla, M. G., Lapidoth, G. D., Norn, C., Dym, O., Unger, T., Albeck, S., Tyka, M. D., & Fleishman, S. J. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707171114 · Cited by 136
Self-citationThe JAK-STAT pathway: from structural biology to cytokine engineering
Lv, Y., Qi, J., Babon, J. J., Cao, L., Fan, G.-H., Lang, J., Zhang, J., Mi, P., Kobe, B., & Wang, F. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01934-w · Cited by 157
A small-molecule fusion inhibitor of influenza virus is orally active in mice
van Dongen, M. J. P., Kadam, R. U., Juraszek, J., Lawson, E. C., Brandenburg, B., Schmitz, F., Schepens, W. B. G., Stoops, B., van Diepen, H. A., Jongeneelen, M. A. C., et al. (2019) · Science · doi:10.1126/science.aar6221 · Cited by 141
Self-citationStrategies Using Bio-Layer Interferometry Biosensor Technology for Vaccine Research and Development
Petersen, R. (2017) · Biosensors · doi:10.3390/bios7040049 · Cited by 145
Third generation antibody discovery methods: in silico rational design
Sormanni, P., Aprile, F. A., & Vendruscolo, M. (2018) · Chemical Society Reviews · doi:10.1039/c8cs00523k · Cited by 143
Procko, 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-citationControl 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-citationStrauch, E.-M., Bernard, S. M., La, D., Bohn, A. J., Lee, P. S., Anderson, C. E., Nieusma, T., Holstein, C. A., Garcia, N. K., Hooper, K. A., et al. (2017) · Nature Biotechnology · doi:10.1038/nbt.3907 · Cited by 119
Self-citationPrinciples for designing ordered protein assemblies
Lai, Y., King, N. P., & Yeates, T. O. (2012) · Trends in Cell Biology · doi:10.1016/j.tcb.2012.08.004 · Cited by 132
Community-Wide Assessment of Protein-Interface Modeling Suggests Improvements to Design Methodology
Fleishman, S. J., Whitehead, T. A., Strauch, E., Corn, J. E., Qin, S., Zhou, H., Mitchell, J. C., Demerdash, O., Takeda‐Shitaka, M., Terashi, G., et al. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2011.09.031 · Cited by 132
Self-citationRenfrew, P. D., Choi, E. J., Bonneau, R., & Kuhlman, B. A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032637 · Cited by 128
Rational Design of Topographical Helix Mimics as Potent Inhibitors of Protein–Protein Interactions
Lao, B. B., Drew, K., Guarracino, D. A., Brewer, T. F., Heindel, D. W., Bonneau, R., & Arora, P. S. (2014) · Journal of the American Chemical Society · doi:10.1021/ja502310r · Cited by 130
Protein Modeling: What Happened to the “Protein Structure Gap”?
Schwede, T. F. (2013) · Structure · doi:10.1016/j.str.2013.08.007 · Cited by 128
Santner, A. A., Croy, C. H., Vasanwala, F. H., Uversky, V. N., Van, Y.-Y. J., & Dunker, A. K. (2012) · Biochemistry · doi:10.1021/bi300653m · Cited by 123
Computational Design of an α-Gliadin Peptidase
Gordon, S. R., Stanley, E. J., Wolf, S., Toland, A. M. S., Wu, S. J., Hadidi, D. A., Mills, J. H., Baker, D. A., Pultz, I. S., & Siegel, J. B. (2012) · Journal of the American Chemical Society · doi:10.1021/ja3094795 · Cited by 122
Self-citationComputational design of environmental sensors for the potent opioid fentanyl
Bick, M. J., Greisen, P. J., Morey, K. J., Antunes, M. S., La, D., Sankaran, B., Reymond, L., Johnsson, K., Medford, J. I., & Baker, D. A. (2017) · eLife · doi:10.7554/elife.28909 · Cited by 118
Self-citationEmerging Antiviral Strategies to Interfere with Influenza Virus Entry
Vanderlinden, E., & Naesens, L. M. J. (2013) · Medicinal Research Reviews · doi:10.1002/med.21289 · Cited by 119
MutaBind estimates and interprets the effects of sequence variants on protein–protein interactions
Li, M., Simonetti, F. L., Goncearenco, A., & Panchenko, A. R. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw374 · Cited by 118
Targeting protein–protein interactions, a wide open field for drug design
Bakail, M., & Ochsenbein, F. (2016) · Comptes Rendus. Chimie · doi:10.1016/j.crci.2015.12.004 · Cited by 117
A new age in protein design empowered by deep learning
Khakzad, H., Igashov, I., Schneuing, A., Goverde, C. A., Bronstein, M. M., & Correia, B. E. (2023) · Cell Systems · doi:10.1016/j.cels.2023.10.006 · Cited by 121
Protein–protein binding affinity prediction on a diverse set of structures
Moal, I. H., Agius, R., & Bates, P. A. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr513 · Cited by 112
Metal-Mediated Affinity and Orientation Specificity in a Computationally Designed Protein Homodimer
Der, B. S., Machius, M., Miley, M. J., Mills, J., Szyperski, T., & Kuhlman, B. A. (2011) · Journal of the American Chemical Society · doi:10.1021/ja208015j · Cited by 112
Dreyfus, C., Ekiert, D. C., & Wilson, I. A. (2013) · Journal of Virology · doi:10.1128/jvi.02975-12 · Cited by 110
Self-citationLapidoth, G. D., Baran, D., Pszolla, G. M., Norn, C., Alon, A., Tyka, M. D., & Fleishman, S. J. (2015) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24779 · Cited by 107
Self-citationRole of the Biomolecular Energy Gap in Protein Design, Structure, and Evolution
Fleishman, S. J., & Baker, D. A. (2012) · Cell · doi:10.1016/j.cell.2012.03.016 · Cited by 104
Self-citationRapid search for tertiary fragments reveals protein sequence–structure relationships
Zhou, J., & Grigoryan, G. (2014) · Protein Science · doi:10.1002/pro.2610 · Cited by 100
Jost, C., & Plückthun, A. (2014) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2014.05.011 · Cited by 105
Coordination chemistry in the ocean
Lu, Y. (2014) · Nature Chemistry · doi:10.1038/nchem.1880 · Cited by 104
Metadata
- Authors
- Fleishman, S. J., Whitehead, T. A., Ekiert, D. C., Dreyfus, C., Corn, J. E., Strauch, E.-M., Wilson, I. A., & Baker, D.
- Affiliations
- University of Washington (US)
- Scripps Research Institute (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Fleishman, Sarel J.
- Whitehead, Timothy A.
- Ekiert, Damian C.
- Baker, David
- ORCID
- Venue
- Science
- Published
- 2011-05-13
- Volume
- 332
- Issue
- 6031
- Pages
- 816-821
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC3164876
- OpenAlex
- W2049275721
- Cited by
- 585
- References
- 20
- Citations by year
- 2026: 15 · 2025: 23 · 2024: 22 · 2023: 26 · 2022: 21 · 2021: 28 · 2020: 24 · 2019: 41 · 2018: 32 · 2017: 44 · 2016: 42 · 2015: 37 · 2014: 61 · 2013: 87 · 2012: 62
- FWCI
- 29.89
- 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)
- Funders
- Howard Hughes Medical Institute
- National Cancer Institute (Y1-CO-1020)
- National Institute of General Medical Sciences (Y1-GM-1104, GM080209, T32GM080209)
- National Institute of Allergy and Infectious Diseases (U54AI057141, P01AI058113, AI057141, AI058113)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Health Sciences › Medicine › Epidemiology › Influenza Virus Research Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Keywords
- protein design, influenza hemagglutinin, affinity maturation
- MeSH terms
- Algorithms, Amino Acid Sequence, Binding Sites, Computer Simulation, Hydrogen Bonding, Hydrogen-Ion Concentration, Models, Molecular, Molecular Sequence Data, Mutation, Protein Binding, Protein Conformation, Proteins, Software, Protein Engineering, Protein Structure, Secondary, Peptide Library, Hemagglutinin Glycoproteins, Influenza Virus, Computational Biology, Protein Interaction Domains and Motifs, Hydrophobic and Hydrophilic Interactions
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