AbDesign: An algorithm for combinatorial backbone design guided by natural conformations and sequences: Combinatorial Backbone Design in Antibodies
Open accessAbstract
Computational design of protein function has made substantial progress, generating new enzymes, binders, inhibitors, and nanomaterials not previously seen in nature. However, the ability to design new protein backbones for function--essential to exert control over all polypeptide degrees of freedom--remains a critical challenge. Most previous attempts to design new backbones computed the mainchain from scratch. Here, instead, we describe a combinatorial backbone and sequence optimization algorithm called AbDesign, which leverages the large number of sequences and experimentally determined molecular structures of antibodies to construct new antibody models, dock them against target surfaces and optimize their sequence and backbone conformation for high stability and binding affinity. We used the algorithm to produce antibody designs that target the same molecular surfaces as nine natural, high-affinity antibodies; in five cases interface sequence identity is above 30%, and in four of those the backbone conformation at the core of the antibody binding surface is within 1 Å root-mean square deviation from the natural antibodies. Designs recapitulate polar interaction networks observed in natural complexes, and amino acid sidechain rigidity at the designed binding surface, which is likely important for affinity and specificity, is high compared to previous design studies. In designed anti-lysozyme antibodies, complementarity-determining regions (CDRs) at the periphery of the interface, such as L1 and H2, show greater backbone conformation diversity than the CDRs at the core of the interface, and increase the binding surface area compared to the natural antibody, potentially enhancing affinity and specificity.
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Four methods have been made available for computational antibody design: OptCDR, OptMAVEn, AbDesign and RosettaAntibodyDesign.
“Since then, four methods have been made available: OptCDR [139], OptMAVEn[140], AbDesign [143] and RosettaAntibodyDesign [142].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [143]
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BLAST+: architecture and applications
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-421 · Cited by 22,074 · see citing works
The PyMOL Molecular Graphics System
DeLano, W. L. (2002) · Medical Entomology and Zoology · Cited by 18,147 · see citing works
The protein data bank: A computer-based archival file for macromolecular structures
Bernstein, F. C., Koetzle, T. F., Williams, G. J. B., Meyer, E. F., Brice, M. D., Rodgers, J. R., Kennard, O., Shimanouchi, T., & Tasumi, M. (1977) · Journal of Molecular Biology · doi:10.1016/s0022-2836(77)80200-3 · Cited by 8,582 · see citing works
Sequences of proteins of immunological interest
Kabat, B. E. A. (1984) · Analytical Biochemistry · doi:10.1016/0003-2697(84)90805-4 · Cited by 3,387 · see citing works
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 · see citing works
Scott, A. M., Wolchok, J. D., & Old, L. J. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3236 · Cited by 2,167 · see citing works
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 · see citing works
Leaver-Fay (2011) · doi:10.1016/b978-0-12-381270-4.00019-6 · Cited by 1,904 · see citing works
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 · see citing works
Reshaping human antibodies for therapy
Riechmann, L., Clark, M., Waldmann, H., & Winter, G. P. (1988) · Nature · doi:10.1038/332323a0 · Cited by 1,562 · see citing works
Canonical structures for the hypervariable regions of immunoglobulins
Chothia, C., & Lesk, A. M. (1987) · Journal of Molecular Biology · doi:10.1016/0022-2836(87)90412-8 · Cited by 1,406 · see citing works
Replacing the complementarity-determining regions in a human antibody with those from a mouse
Jones, P. T., Dear, P. H., Foote, J., Neuberger, M. S., & Winter, G. (1986) · Nature · doi:10.1038/321522a0 · Cited by 1,406 · see citing works
Wu, T. T., & Kabat, E. A. (1970) · The Journal of Experimental Medicine · doi:10.1084/jem.132.2.211 · Cited by 1,340 · see citing works
Shape Complementarity at Protein/Protein Interfaces
Lawrence, M. C., & Colman, P. M. (1993) · Journal of Molecular Biology · doi:10.1006/jmbi.1993.1648 · Cited by 1,219 · see citing works
Shape complementarity at protein–protein interfaces
Norel, R., Lin, S. L., Wolfson, H. J., & Nussinov, R. (1994) · Biopolymers · doi:10.1002/bip.360340711 · Cited by 1,208 · see citing works
Conformations of immunoglobulin hypervariable regions
Chothia, C., Lesk, A. M., Tramontano, A. L., Levitt, M., Smith‐Gill, S. J., Air, G. M., Sheriff, S., PADLAN, E. A., Davies, D. R., Tulip, W. R., et al. (1989) · Nature · doi:10.1038/342877a0 · Cited by 1,185 · see citing works
Gray, 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 · 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
Winter, G., & Milstein, C. (1991) · Nature · doi:10.1038/349293a0 · Cited by 946 · see citing works
Computational Design of an Enzyme Catalyst for a Stereoselective Bimolecular Diels-Alder Reaction
Siegel, J. B., Zanghellini, A., Lovick, H. M., Kiss, G., Lambert, A. R., St.Clair, J. L., Gallaher, J. L., Hilvert, D., Gelb, M. H., Stoddard, B. L., et al. (2010) · Science · doi:10.1126/science.1190239 · Cited by 921 · see citing works
Structure of RSV Fusion Glycoprotein Trimer Bound to a Prefusion-Specific Neutralizing Antibody
McLellan, J. S., Chen, M., Leung, S., Graepel, K. W., Du, X., Yang, Y., Zhou, T., Baxa, U., Yasuda, E., Beaumont, T., et al. (2013) · Science · doi:10.1126/science.1234914 · Cited by 883 · see citing works
Strategies and challenges for the next generation of therapeutic antibodies
Beck, A., Wurch, T., Bailly, C., & Corvaı̈a, N. (2010) · Nature reviews. Immunology · doi:10.1038/nri2747 · Cited by 851 · see citing works
Native protein sequences are close to optimal for their structures
Kuhlman, B. A., & Baker, D. A. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.19.10383 · Cited by 814 · see citing works
A simple physical model for binding energy hot spots in protein–protein complexes
Kortemme, T., & Baker, D. A. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.202485799 · Cited by 801 · see citing works
Throsby, M., van den Brink, E. N., Jongeneelen, M. A. C., Poon, L. L. M., Alard, P., Cornelissen, L. A. H. M., Bakker, A. Q., Cox, F., van Deventer, E., Guan, Y., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003942 · Cited by 738 · see citing works
Standard conformations for the canonical structures of immunoglobulins 1 1Edited by I. A. Wilson
Al‐Lazikani, B., Lesk, A. M., & Chothia, C. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.1354 · Cited by 707 · see citing works
SAbDab: the structural antibody database
Dunbar, J., Krawczyk, K., Leem, J., Baker, T., Fuchs, A., Georges, G., Shi, J., & Deane, C. M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1043 · Cited by 674 · see citing works
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 · see citing works
Computational 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 651 · see citing works
Computational Design of Proteins Targeting the Conserved Stem Region of Influenza Hemagglutinin
Fleishman, S. J., Whitehead, T. A., Ekiert, D. C., Dreyfus, C., Corn, J. E., Strauch, E.-M., Wilson, I. A., & Baker, D. (2011) · Science · doi:10.1126/science.1202617 · Cited by 585 · see citing works
Self-citationCyclic coordinate descent: A robotics algorithm for protein loop closure
Canutescu, A. A., & Dunbrack, R. L. (2003) · Protein Science · doi:10.1110/ps.0242703 · Cited by 527 · see citing works
Antibody framework residues affecting the conformation of the hypervariable loops
Foote, J., & Winter, G. P. (1992) · Journal of Molecular Biology · doi:10.1016/0022-2836(92)91010-m · Cited by 525 · see citing works
Self-Assembling Cages from Coiled-Coil Peptide Modules
Fletcher, J. M., Harniman, R. L., Barnes, F. R. H., Boyle, A. L., Collins, A., Mantell, J., Sharp, T. H., Antognozzi, M., Booth, P. J., Linden, N., et al. (2013) · Science · doi:10.1126/science.1233936 · Cited by 489 · see citing works
Bound water molecules and conformational stabilization help mediate an antigen-antibody association.
Bhat, T. N., Bentley, G. A., Boulot, G., Greene, M. I., Tello, D., Dall’Acqua, W. F., Souchon, H., Schwarz, F., Mariuzza, R. A., & Poljak, R. J. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.3.1089 · Cited by 479 · see citing works
Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling
Mandell, D. J., Coutsias, E. A., & Kortemme, T. (2009) · Nature Methods · doi:10.1038/nmeth0809-551 · Cited by 458 · see citing works
Assessment of blind predictions of protein–protein interactions: Current status of docking methods
Mendez, R., Leplae, R., Maria, L. D., & Wodak, S. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10393 · Cited by 438 · see citing works
Computational design of ligand-binding proteins with high affinity and selectivity
Tinberg, C. E., Khare, S. D., Dou, J., Doyle, L., Nelson, J., Schena, A., Jankowski, W., Kalodimos, C. G., Johnsson, K., Stoddard, B. L., et al. (2013) · Nature · doi:10.1038/nature12443 · Cited by 432 · see citing works
Burton, D. R., Poignard, P., Stanfield, R. L., & Wilson, I. A. (2012) · Science · doi:10.1126/science.1225416 · Cited by 416 · see citing works
Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping
Tyka, M. D., Keedy, D. A., André, I., DiMaio, F., Song, Y., Richardson, D. C., Richardson, J. S., & Baker, D. A. (2010) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.11.008 · Cited by 410 · see citing works
A new clustering of antibody CDR loop conformations
North, B., Lehmann, A., & Dunbrack, R. L. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.10.030 · Cited by 380 · see citing works
New algorithms and an in silico benchmark for computational enzyme design
Zanghellini, A., Jiang, L., Wollacott, A. M., Cheng, G., Meiler, J., Althoff, E. A., Röthlisberger, D., & Baker, D. A. (2006) · Protein Science · doi:10.1110/ps.062353106 · Cited by 360 · see citing works
Conformational analysis of the backbone-dependent rotamer preferences of protein sidechains
Dunbrack, R. L., & Karplus, M. (1994) · Nature Structural & Molecular Biology · doi:10.1038/nsb0594-334 · Cited by 347 · see citing works
Computational design of antibody-affinity improvement beyond in vivo maturation
Lippow, S. M., Wittrup, K. D., & Tidor, B. (2007) · Nature Biotechnology · doi:10.1038/nbt1336 · Cited by 342 · see citing works
Conformational Abs recognizing a generic amyloid fibril epitope
O’Nuallain, B., & Wetzel, R. B. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.022662599 · Cited by 331 · see citing works
Benchmarking and Analysis of Protein Docking Performance in Rosetta v3.2
Chaudhury, S., Berrondo, M., Weitzner, B. D., Muthu, P., Bergman, H., & Gray, J. J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0022477 · Cited by 326 · see citing works
Smith, C. A., & Kortemme, T. (2008) · Journal of Molecular Biology · doi:10.1016/j.jmb.2008.05.023 · Cited by 314 · see citing works
Design 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 308 · see citing works
Chen, J., Sawyer, N., & Regan, L. (2013) · Protein Science · doi:10.1002/pro.2230 · Cited by 301 · see citing works
Clinical trials of antibody therapy
Glennie, M. J., & Johnson, P. (2000) · Immunology Today · doi:10.1016/s0167-5699(00)01669-8 · Cited by 290 · see citing works
Elicitation of structure-specific antibodies by epitope scaffolds
Ofek, G., Guenaga, F. J., Schief, W. R., Skinner, J., Baker, D., Wyatt, R., & Kwong, P. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1004728107 · Cited by 278 · see citing works
Evolution of proteins formed by β-sheets
Lesk, A. M., & Chothia, C. (1982) · Journal of Molecular Biology · doi:10.1016/0022-2836(82)90179-6 · Cited by 274 · see citing works
Tramontano, A. L., Chothia, C., & Lesk, A. M. (1990) · Journal of Molecular Biology · doi:10.1016/s0022-2836(05)80102-0 · Cited by 236 · see citing works
Stranges, P. B., & Kuhlman, B. A. (2012) · Protein Science · doi:10.1002/pro.2187 · Cited by 233 · see citing works
Structural classification of CDR‐H3 in antibodies
Shirai, H., Kidera, A., & Nakamura, H. (1996) · FEBS Letters · doi:10.1016/s0014-5793(96)01252-5 · Cited by 223 · see citing works
Kabat, E. A., Wu, T. T., & Bilofsky, H. S. (1977) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(17)39891-5 · Cited by 199 · see citing works
Kettleborough, C. A., Saldanha, J. W., Heath, V. J., Morrison, C., & Bendig, M. M. (1991) · Protein Engineering Design and Selection · doi:10.1093/protein/4.7.773 · Cited by 198 · see citing works
The Imprint of Somatic Hypermutation on the Repertoire of Human Germline V Genes
Tomlinson, I. M., Walter, G., Jones, P., Dear, P. H., Sonnhammer, E. L. L., & Winter, G. P. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0127 · Cited by 197 · see citing works
Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement
Leaver‐Fay, A., O’Meara, M. J., Tyka, M., Jacak, R., Song, Y., Kellogg, E. H., Thompson, J., Davis, I., Pache, R. A., Lyskov, S., et al. (2013) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/b978-0-12-394292-0.00006-0 · Cited by 189 · see citing works
Manivel, V., Sahoo, N., Salunke, D. M., & Rao, K. V. S. (2000) · Immunity · doi:10.1016/s1074-7613(00)00061-3 · Cited by 189 · see citing works
Clark, L. A., Boriack‐Sjodin, P. A., Eldredge, J. K., Fitch, C., Friedman, B., Hanf, K. J. M., Jarpe, M. B., Liparoto, S. F., Li, Y., Lugovskoy, A. A., et al. (2006) · Protein Science · doi:10.1110/ps.052030506 · Cited by 173 · see citing works
Alexander, N. S., Woetzel, N., & Meiler, J. (2011) · IEEE International Conference on Computational Advances in Bio and Medical Sciences · doi:10.1109/iccabs.2011.5729867 · Cited by 172 · see citing works
PADLAN, E. A. (1991) · Molecular Immunology · doi:10.1016/0161-5890(91)90163-e · Cited by 169 · see citing works
Computational Design of Catalytic Dyads and Oxyanion Holes for Ester Hydrolysis
Richter, F. M., Blomberg, R., Khare, S. D., Kiss, G., Kuzin, A. P., Smith, A. J. T., Gallaher, J. L., Pianowski, Z., Helgeson, R. C., Grjasnow, A., et al. (2012) · Journal of the American Chemical Society · doi:10.1021/ja3037367 · Cited by 168 · see citing works
Sequence context-specific profiles for homology searching
Biegert, A., & Söding, J. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0810767106 · Cited by 167 · see citing works
H3‐rules: identification of CDR‐H3 structures in antibodies
Shirai, H., Kidera, A., & Nakamura, H. (1999) · FEBS Letters · doi:10.1016/s0014-5793(99)00821-2 · Cited by 166 · see citing works
A De Novo Protein Binding Pair By Computational Design and Directed Evolution
Karanicolas, J., Corn, J. E., Chen, I., Joachimiak, Ł. A., Dym, O., Peck, S. H., Albeck, S., Unger, T., Hu, W., Liu, G., et al. (2011) · Molecular Cell · doi:10.1016/j.molcel.2011.03.010 · Cited by 164 · see citing works
What makes a protein fold amenable to functional innovation? Fold polarity and stability trade-offs.
Dellus-Gur, E., Tóth-Petróczy, Á., Elias, M., & Tawfik, D. S. (2013) · Journal of Molecular Biology · doi:10.1016/j.jmb.2013.03.033 · Cited by 160 · see citing works
Computer-aided design of functional protein interactions
Mandell, D. J., & Kortemme, T. (2009) · Nature Chemical Biology · doi:10.1038/nchembio.251 · Cited by 155 · see citing works
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 · see citing works
Sheffler, W., & Baker, D. A. (2008) · Protein Science · doi:10.1002/pro.8 · Cited by 147 · see citing works
Structure-based design of conformation- and sequence-specific antibodies against amyloid β
Perchiacca, J. M., Ladiwala, A. R. A., Bhattacharya, M., & Tessier, P. M. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1111232108 · Cited by 145 · see citing works
Affinity maturation of antibodies assisted by in silico modeling
Barderas, R., Desmet, J., Timmerman, P., Meloen, R. H., & Casal, J. I. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0801221105 · Cited by 142 · see citing works
Hedgehog Pathway Antagonist 5E1 Binds Hedgehog at the Pseudo-active Site
Maun, H. R., Wen, X., Lingel, A., de Sauvage, F. J., Lazarus, R. A., Scales, S. J., & Hymowitz, S. G. (2010) · Journal of Biological Chemistry · doi:10.1074/jbc.m110.112284 · Cited by 142 · see citing works
Structure-Based Design of Supercharged, Highly Thermoresistant Antibodies
Miklos, A. E., Kluwe, C., Der, B. S., Pai, S., Sircar, A., Hughes, R. A., Berrondo, M., Xu, J., Codrea, V., Buckley, P. E., et al. (2012) · Chemistry & Biology · doi:10.1016/j.chembiol.2012.01.018 · Cited by 142 · see citing works
Positive and Negative Design in Stability and Thermal Adaptation of Natural Proteins
Berezovsky, I. N., Zeldovich, K. B., & Shakhnovich, E. I. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030052 · Cited by 142 · see citing works
Spiegel, P. C., Jacquemin, M. G., Saint-Remy, J.-M., Stoddard, B. L., & Pratt, K. P. (2001) · Blood · doi:10.1182/blood.v98.1.13 · Cited by 140 · see citing works
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 · see citing works
Structural basis for HIV-1 neutralization by a gp41 fusion intermediate–directed antibody
Luftig, M. A., Mattu, M., Giovine, P. D., Geleziunas, R., Hrin, R. C., Barbato, G., Bianchi, E., Miller, M. D., Pessi, A., & Carfı́, A. (2006) · Nature Structural & Molecular Biology · doi:10.1038/nsmb1127 · Cited by 129 · see citing works
Midelfort, K. S., Hernández, H. H., Lippow, S. M., Tidor, B., Drennan, C. L., & Wittrup, K. D. (2004) · Journal of Molecular Biology · doi:10.1016/j.jmb.2004.08.019 · Cited by 128 · see citing works
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 · see citing works
High-resolution design of a protein loop
Hu, X., Wang, H., Ke, H., & Kuhlman, B. A. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0707977104 · Cited by 126 · see citing works
Antibody engineering and modification technologies
Filpula, D. R. (2007) · Biomolecular Engineering · doi:10.1016/j.bioeng.2007.03.004 · Cited by 124 · see citing works
Structural Plasticity and the Evolution of Antibody Affinity and Specificity
Yin, J., Beuscher, A. E., Andryski, S. E., Stevens, R. C., & Schultz, P. G. (2003) · Journal of Molecular Biology · doi:10.1016/s0022-2836(03)00631-4 · Cited by 117 · see citing works
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 · see citing works
Role 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 · see citing works
Pantazes, R. J., & Maranas, C. D. (2010) · Protein Engineering Design and Selection · doi:10.1093/protein/gzq061 · Cited by 97 · see citing works
PADLAN, E. A. (1977) · Quarterly Reviews of Biophysics · doi:10.1017/s0033583500000135 · Cited by 96 · see citing works
Moretti, R., Fleishman, S. J., Agius, R., Torchala, M., Bates, P. A., Kastritis, P. L., Rodrigues, J., Trellet, M. E., Bonvin, A. M. J. J., Cui, M., et al. (2013) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24356 · Cited by 92 · see citing works
Computational design of a pH-sensitive IgG binding protein
Strauch, E., Fleishman, S. J., & Baker, D. A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1313605111 · Cited by 91 · see citing works
A de novo designed protein–protein interface
Huang, P., Love, J. J., & Mayo, S. L. (2007) · Protein Science · doi:10.1110/ps.073125207 · Cited by 90 · see citing works
Computational Design of a Protein-Based Enzyme Inhibitor
Procko, E., Hedman, R., Hamilton, K., Seetharaman, J., Fleishman, S. J., Su, M., Aramini, J. M., Kornhaber, G. J., Hunt, J. F., Tong, L., et al. (2013) · Journal of Molecular Biology · doi:10.1016/j.jmb.2013.06.035 · Cited by 88 · see citing works
Schwarz, M., Röttgen, P., Takada, Y., Gall, F. L., Knackmuss, S. H. J., Bassler, N., Büttner, C., Little, M., Bode, C., & Peter, K. (2004) · The FASEB Journal · doi:10.1096/fj.04-1513fje · Cited by 80 · see citing works
Li, T., Pantazes, R. J., & Maranas, C. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0105954 · Cited by 79 · see citing works
A Comparative Analysis of the Immunological Evolution of Antibody 28B4
Yin, J., Mundorff, E. C., Yang, P. L., Wendt, K. U., Hanway, D., Stevens, R. C., & Schultz, P. G. (2001) · Biochemistry · doi:10.1021/bi010536c · Cited by 73 · see citing works
Computational design of a symmetric homodimer using β-strand assembly
Stranges, P. B., Machius, M., Miley, M. J., Tripathy, A., & Kuhlman, B. A. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1115124108 · Cited by 70 · see citing works
Mylvaganam, S. E., Paterson, Y. Y. W., & Getzoff, E. D. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.1942 · Cited by 69 · see citing works
Computational Design of a PAK1 Binding Protein
Jha, R. K., Leaver‐Fay, A., Yin, S., Wu, Y., Butterfoss, G. L., Szyperski, T., Dokholyan, N. V., & Kuhlman, B. A. (2010) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.05.006 · Cited by 68 · see citing works
Structural mechanism for affinity maturation of an anti-lysozyme antibody
Cauerhff, A., Goldbaum, F. A., & Braden, B. C. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400060101 · Cited by 67 · see citing works
Unraveling the Allosteric Mechanism of Serine Protease Inhibition by an Antibody
Ganesan, R., Eigenbrot, C. W., Wu, Y., Liang, W., Shia, S., Lipari, M. T., & Kirchhofer, D. (2009) · Structure · doi:10.1016/j.str.2009.09.014 · Cited by 64 · see citing works
Thermodynamic and kinetic aspects of antibody evolution during the immune response to hapten
Sagawa, T., Oda, M., Ishimura, M., Furukawa, K., & Azuma, T. (2003) · Molecular Immunology · doi:10.1016/s0161-5890(02)00282-1 · Cited by 63 · see citing works
Restricted sidechain plasticity in the structures of native proteins and complexes
Fleishman, S. J., Khare, S. D., Koga, N., & Baker, D. A. (2011) · Protein Science · doi:10.1002/pro.604 · Cited by 55 · see citing works
Emerging themes in the computational design of novel enzymes and protein–protein interfaces
Khare, S. D., & Fleishman, S. J. (2012) · FEBS Letters · doi:10.1016/j.febslet.2012.12.009 · Cited by 54 · see citing works
Improving the species cross-reactivity of an antibody using computational design
Farady, C. J., Sellers, B. D., Jacobson, M. P., & Craik, C. S. (2009) · Bioorganic & Medicinal Chemistry Letters · doi:10.1016/j.bmcl.2009.05.005 · Cited by 50 · see citing works
Hotspot-Centric De Novo Design of Protein Binders
Fleishman, S. J., Corn, J. E., Strauch, E., Whitehead, T. A., Karanicolas, J., & Baker, D. A. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2011.09.001 · Cited by 50 · see citing works
Structure‐guided forcefield optimization
Song, Y., Tyka, M. D., Leaver‐Fay, A., Thompson, J., & Baker, D. A. (2011) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.23013 · Cited by 49 · see citing works
Singer, I. I., Kawka, D. W., DeMartino, J. A., Daugherty, B. L., Elliston, K. O., Alves, K., Bush, B. L., Cameron, P. M., Cuca, G. C., & Davies, P. (1993) · The Journal of Immunology · doi:10.4049/jimmunol.150.7.2844 · Cited by 45 · see citing works
Submitting antibodies to binding arbitration
Michnick, S. W., & Sidhu, S. S. (2008) · Nature Chemical Biology · doi:10.1038/nchembio0608-326 · Cited by 38 · see citing works
Homologous series of affinity labeling reagents and their use in the study of antibody binding sites
Strausbauch, P. H., Weinstein, Y., Wilchek, M., Shaltiel, S., & Givol, D. (1971) · Biochemistry · doi:10.1021/bi00799a029 · Cited by 34 · see citing works
Computational design of protein-small molecule interfaces
Allison, B., Combs, S. A., DeLuca, S., Lemmon, G., Mizoue, L. S., & Meiler, J. (2013) · Journal of Structural Biology · doi:10.1016/j.jsb.2013.08.003 · Cited by 33 · see citing works
The 2.5 Å resolution structure of the Jel42 Fab fragment/HPr complex 1 1Edited by I. A. Wilson
Prasad, L., Waygood, E. B., Lee, J. S., & Delbaere, L. T. J. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.1888 · Cited by 33 · see citing works
Faelber, K., Kirchhofer, D., Presta, L. G., Kelley, R. F., & Muller, Y. A. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2001.5036 · Cited by 31 · see citing works
A “Fuzzy”-Logic Language for Encoding Multiple Physical Traits in Biomolecules
Warszawski, S., Netzer, R., Tawfik, D. S., & Fleishman, S. J. (2014) · Journal of Molecular Biology · doi:10.1016/j.jmb.2014.10.002 · Cited by 28 · see citing works
Pantazes, R. J., & Maranas, C. D. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-168 · Cited by 24 · see citing works
Pons, J., Stratton, J., & Kirsch, J. F. (2002) · Protein Science · doi:10.1110/ps.0209102 · Cited by 19 · see citing works
An antibody loop replacement design feasibility study and a loop-swapped dimer structure
Clark, L. A., Boriack‐Sjodin, P. A., Day, E. S., Eldredge, J. K., Fitch, C., Jarpe, M. B., Miller, S., Li, Y., Simon, K. J., & van Vlijmen, H. (2008) · Protein Engineering Design and Selection · doi:10.1093/protein/gzn072 · Cited by 14 · see citing works
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Macromolecular modeling and design in Rosetta: recent methods and frameworks
Leman, J. K., Weitzner, B. D., Lewis, S. M., Adolf-Bryfogle, J., Alam, N., Alford, R. F., Aprahamian, M., Baker, D., Barlow, K. A., Barth, P., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0848-2 · Cited by 888 · see citing works
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 · see citing works
Computational approaches to therapeutic antibody design: established methods and emerging trends
Norman, R. A., Ambrosetti, F., Bonvin, A. M. J. J., Colwell, L. J., Kelm, S., Kumar, S., & Krawczyk, K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz095 · Cited by 219 · see citing works
“Since then, four methods have been made available: OptCDR [139], OptMAVEn[140], AbDesign [143] and RosettaAntibodyDesign [142].”
MethodDeciphering the language of antibodies using self-supervised learning
Leem, J., Mitchell, L., Farmery, J. H. R., Barton, J., & Galson, J. D. (2022) · Patterns · doi:10.1016/j.patter.2022.100513 · Cited by 154 · see citing works
Luo, S., Su, Y., Peng, J., Wang, S., Peng, J., & Ma, J. (2022) · neural information processing systems · doi:10.52202/068431-0709 · Cited by 149 · see citing works
Luo, S., Su, Y., Peng, X., Wang, S., Peng, J., & Ma, J. (2022) · doi:10.1101/2022.07.10.499510 · Cited by 151 · see citing works
Principles 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 · see citing works
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 136 · see citing works
Warszawski, S., Katz, A. B., Lipsh‐Sokolik, R., Khmelnitsky, L., Ben‐Nissan, G., Javitt, G., Dym, O., Unger, T., Knop, O., Albeck, S., et al. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007207 · Cited by 111 · see citing works
Computational design of epitope-specific functional antibodies
Nimrod, G., Fischman, S., Austin, M., Herman, A., Keyes, F., Leiderman, O., Hargreaves, D., Strajbl, M., Breed, J., Klompus, S., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.10.081 · Cited by 77 · see citing works
Guarra, F., & Colombo, G. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00513 · Cited by 79 · see citing works
Comparative Analysis of the CDR Loops of Antigen Receptors
Wong, W. K., Leem, J., & Deane, C. M. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.02454 · Cited by 75 · see citing works
Toward Drug-Like Multispecific Antibodies by Design
Sawant, M. S., Streu, C. N., Wu, L., & Tessier, P. M. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21207496 · Cited by 74 · see citing works
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-designPreprint
Jin, W., Wohlwend, J., Barzilay, R., & Jaakkola, T. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.04624 · Cited by 85 · 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 61 · see citing works
Brown, A. J., Snapkov, I., Akbar, R., Pavlović, M., Miho, E., Sandve, G. K., & Greiff, V. (2019) · Molecular Systems Design & Engineering · doi:10.1039/c9me00071b · Cited by 59 · see citing works
Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design
Schoeder, C. T., Schmitz, S., Adolf‐Bryfogle, J., Sevy, A. M., Finn, J. A., Sauer, M. F., Bozhanova, N. G., Mueller, B. K., Sangha, A. K., Bonet, J., et al. (2021) · Biochemistry · doi:10.1021/acs.biochem.0c00912 · Cited by 57 · see citing works
Computational design of antibodies
Fischman, S., & Ofran, Y. (2018) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2018.04.007 · Cited by 56 · see citing works
Highly active enzymes by automated combinatorial backbone assembly and sequence design
Lapidoth, G. D., Khersonsky, O., Lipsh‐Sokolik, R., Dym, O., Albeck, S., Hamer-Rogotner, S., & Fleishman, S. J. (2018) · Nature Communications · doi:10.1038/s41467-018-05205-5 · Cited by 56 · see citing works
Dewaker, V., Morya, V. K., Kim, Y. H., Park, S. T., Kim, H. S., & Koh, Y. H. (2025) · Biomarker Research · doi:10.1186/s40364-025-00764-4 · Cited by 59 · see citing works
Length-independent structural similarities enrich the antibody CDR canonical class model
Nowak, J., BAKER, T. S., Georges, G. J., Kelm, S., Klostermann, S., Shi, J., Sridharan, S., & Deane, C. M. (2016) · mAbs · doi:10.1080/19420862.2016.1158370 · Cited by 54 · see citing works
OptMAVEn-2.0: De novo Design of Variable Antibody Regions against Targeted Antigen Epitopes
Chowdhury, R., Allan, M. F., & Maranas, C. D. (2018) · Antibodies · doi:10.3390/antib7030023 · Cited by 55 · see citing works
Ultrahigh specificity in a network of computationally designed protein-interaction pairs
Netzer, R., Listov, D., Lipsh‐Sokolik, R., Dym, O., Albeck, S., Knop, O., Kleanthous, C., & Fleishman, S. J. (2018) · Nature Communications · doi:10.1038/s41467-018-07722-9 · Cited by 53 · see citing works
Antibody design using deep learning: from sequence and structure design to affinity maturation
Joubbi, S., Micheli, A., Milazzo, P., Maccari, G., Ciano, G., Cardamone, D., & Medini, D. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae307 · Cited by 54 · see citing works
Harmalkar, A., Rao, R., Xie, Y. R., Honer, J., Deisting, W., Anlahr, J., Hoenig, A., Czwikla, J., Sienz-Widmann, E., Rau, D., et al. (2023) · mAbs · doi:10.1080/19420862.2022.2163584 · Cited by 48 · see citing works
Protein structural motifs in prediction and design
Mackenzie, C. O., & Grigoryan, G. (2017) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2017.03.012 · Cited by 42 · see citing works
Biomedical Science to Tackle the COVID-19 Pandemic: Current Status and Future Perspectives
Zamora‐Ledezma, C., Clavijo-Calderón, D., Medina, E. A., Sinche, F. L., Vispo, N. S., Dahoumane, S. A., & Alexis, F. (2020) · Molecules · doi:10.3390/molecules25204620 · Cited by 39 · see citing works
Liu, X., Taylor, R. D., Griffin, L., Coker, S.-F., Adams, R., Ceska, T., Shi, J., Lawson, A. D. G., & Baker, T. (2017) · Scientific Reports · doi:10.1038/srep41306 · Cited by 39 · see citing works
Applications of Machine and Deep Learning in Adaptive Immunity
Pertseva, M., Gao, B., Neumeier, D., Yermanos, A., & Reddy, S. T. (2021) · Annual Review of Chemical and Biomolecular Engineering · doi:10.1146/annurev-chembioeng-101420-125021 · Cited by 38 · 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
Computational design of structured loops for new protein functions
Kundert, K., & Kortemme, T. (2019) · Biological Chemistry · doi:10.1515/hsz-2018-0348 · Cited by 36 · see citing works
A consensus protocol for the in silico optimisation of antibody fragments
Soler, M. A., Medagli, B., Semrau, M. S., Storici, P., Bajc, G., de Marco, A., Laio, A., & Fortuna, S. (2019) · Chemical Communications · doi:10.1039/c9cc06182g · Cited by 35 · see citing works
Protein sequence design by explicit energy landscape optimizationPreprint
Norn, C., Wicky, B. I. M., Juergens, D., Liu, S., Kim, D. E., Koepnick, B., Anishchenko, I. V., Players, F., Baker, D. A., & Ovchinnikov, S. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.23.218917 · Cited by 33 · see citing works
Yang, Y. X., Wang, P., & Zhu, B. T. (2022) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2022.108364 · Cited by 30 · see citing works
Multistate design of influenza antibodies improves affinity and breadth against seasonal viruses
Sevy, A. M., Wu, N. C., Gilchuk, I. M., Parrish, E. H., Burger, S., Yousif, D., Nagel, M., Schey, K. L., Wilson, I. A., Crowe, J. E., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1806004116 · Cited by 29 · see citing works
ProPOSE: Direct Exhaustive Protein–Protein Docking with Side Chain Flexibility
Hogues, H., Gaudreault, F., Corbeil, C. R., Deprez, C., Sulea, T. I., & Purisima, E. O. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00225 · Cited by 27 · see citing works
Antibody affinity maturation by computational design
Kuroda, D., & Tsumoto, K. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8648-4_2 · Cited by 26 · see citing works
Determinants of the assembly and function of antibody variable domains
Herold, E. M., John, C., Weber, B., Kremser, S., Eras, J., Berner, C., Deubler, S., Zacharias, M., & Büchner, J. (2017) · Scientific Reports · doi:10.1038/s41598-017-12519-9 · Cited by 26 · see citing works
Computational tools for aiding rational antibody design
Krawczyk, K., Dunbar, J., & Deane, C. M. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6637-0_21 · Cited by 26 · see citing works
IgGM: A Generative Model for Functional Antibody and Nanobody DesignPreprint
Wang, R., Wu, F., Gao, X., Wu, J., Zhao, P., & Yao, J. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.19.613838 · Cited by 26 · see citing works
Assessing and enhancing foldability in designed proteins
Listov, D., Lipsh‐Sokolik, R., Rosset, S., Yang, C., Correia, B. E., & Fleishman, S. J. (2022) · Protein Science · doi:10.1002/pro.4400 · Cited by 24 · see citing works
Computational protein design for given backbone: recent progresses in general method-related aspects
Liu, H., & Chen, Q. (2016) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2016.06.013 · Cited by 23 · see citing works
Amon, R., Grant, O. C., Ben‐Arye, S. L., Makeneni, S., Nivedha, A. K., Marshanski, T., Norn, C., Yu, H., Glushka, J., Fleishman, S. J., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-29209-9 · Cited by 23 · see citing works
Computationally designed hyperactive Cas9 enzymes
Vos, P. D., Rossetti, G., Mantegna, J. L., Siira, S. J., Gandadireja, A. P., Bruce, M., Raven, S. A., Khersonsky, O., Fleishman, S. J., Filipovska, A., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30598-9 · Cited by 22 · see citing works
Neamțu, A., Mocci, F., Laaksonen, A., & da Silva, F. L. B. (2022) · Colloids and Surfaces B Biointerfaces · doi:10.1016/j.colsurfb.2022.112986 · Cited by 22 · see citing works
Meehl, M. M., Immadisetty, K., Trivedi, V. D., Głowacki, P., Prinzing, B. L., Anido, A. A., Ibañez-Vega, J., Leslie, B. J., Babu, M. M., & Krenciute, G. (2025) · Molecular Therapy · doi:10.1016/j.ymthe.2025.07.044 · Cited by 21 · see citing works
What Have We Learned from Design of Function in Large Proteins?
Khersonsky, O., & Fleishman, S. J. (2022) · BioDesign Research · doi:10.34133/2022/9787581 · Cited by 20 · see citing works
Norn, C., Lapidoth, G. D., & Fleishman, S. J. (2016) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25185 · Cited by 21 · see citing works
The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes
Lipsh‐Sokolik, R., Listov, D., & Fleishman, S. J. (2020) · Protein Science · doi:10.1002/pro.3970 · Cited by 21 · see citing works
Hallucinating structure-conditioned antibody libraries for target-specific binders
Mahajan, S. P., Ruffolo, J. A., Frick, R., & Gray, J. J. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.999034 · Cited by 20 · see citing works
Zimmerman, L., Alon, N., Levin, I., Koganitsky, A., Shpigel, N., Brestel, C., & Lapidoth, G. D. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2313809121 · Cited by 20 · see citing works
AbPredict 2: a server for accurate and unstrained structure prediction of antibody variable domains
Lapidoth, G. D., Parker, J., Prilusky, J., & Fleishman, S. J. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty822 · Cited by 20 · see citing works
Rosenfeld, R., Alcalay, R., Mechaly, A., Lapidoth, G. D., Epstein, E., Kronman, C., Fleishman, S. J., & Mazor, O. (2017) · Protein Engineering Design and Selection · doi:10.1093/protein/gzx028 · Cited by 19 · see citing works
Adaption of human antibody λ and κ light chain architectures to CDR repertoires
van der Kant, R., Bauer, J., Karow‐Zwick, A. R., Kube, S., Garidel, P., Blech, M., Rousseau, F., & Schymkowitz, J. W. H. (2019) · Protein Engineering Design and Selection · doi:10.1093/protein/gzz012 · Cited by 21 · see citing works
IsAb: a computational protocol for antibody design
Liang, T., Chen, H., Yuan, J., Jiang, C., Hao, Y., Wang, Y., Feng, Z., & Xie, X. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab143 · Cited by 17 · see citing works
IPRO+/−: Computational Protein Design Tool Allowing for Insertions and Deletions
Chowdhury, R., Grisewood, M. J., Boorla, V. S., Yan, Q., Pfleger, B. F., & Maranas, C. D. (2020) · Structure · doi:10.1016/j.str.2020.08.003 · Cited by 17 · see citing works
De novo design of epitope-specific antibodies via a structure-driven computational workflow
Wu, F., Zhao, Y. S., Wu, J., Jiang, B., He, B., Huang, L.-K., Qin, C., Xiao, Y., Yang, F., Wang, R., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-67361-9 · Cited by 18 · see citing works
High-Throughput Antibody Structure Modeling and Design Using ABodyBuilder
Leem, J., & Deane, C. M. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8736-8_21 · Cited by 15 · see citing works
Bonadio, A., Wenig, B., Hockla, A., Radisky, E. S., & Shifman, J. M. (2022) · Journal of Molecular Biology · doi:10.1016/j.jmb.2023.168095 · Cited by 14 · see citing works
Bielska, W., Jaszczyszyn, I., Dudzic, P., Janusz, B., Chomicz, D., Wrobel, S., Greiff, V., Feehan, R., Adolf‐Bryfogle, J., & Krawczyk, K. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1571371 · Cited by 16 · see citing works
Lauro, A. D., Rienzo, L. D., Miotto, M., Olimpieri, P. P., Milanetti, E., & Ruocco, G. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.874296 · Cited by 15 · see citing works
Improved HIV-1 neutralization breadth and potency of V2-apex antibodies by in silico design
Holt, G. T., Gorman, J., Wang, S., Lowegard, A. U., Zhang, B., Liu, T. W. B., Lin, B. C., Louder, M. K., Frenkel, M. S., McKee, K., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112711 · Cited by 13 · see citing works
Gallo, E. (2024) · Molecular Biotechnology · doi:10.1007/s12033-024-01064-2 · Cited by 16 · see citing works
Incorporating an allosteric regulatory site in an antibody through backbone design
Khersonsky, O., & Fleishman, S. J. (2017) · Protein Science · doi:10.1002/pro.3126 · Cited by 13 · see citing works
Bonadio, A., & Shifman, J. M. (2021) · Protein Engineering Design and Selection · doi:10.1093/protein/gzab020 · Cited by 12 · see citing works
Incorporating Pre-training Paradigm for Antibody Sequence-Structure Co-designPreprint
Gao, K., Wu, L., Zhu, J., Peng, T., Xia, Y., He, L., Xie, S., Qin, T., Liu, H., He, K., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.14.516404 · Cited by 12 · see citing works
FlowDesign: Improved design of antibody CDRs through flow matching and better prior distributions
Wu, J., Kong, X., Sun, N., Wei, J., Shan, S., Feng, F., Wu, F., Peng, J., Zhang, L., Liu, Y., et al. (2025) · Cell Systems · doi:10.1016/j.cels.2025.101270 · Cited by 11 · see citing works
Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design
Gao, K., Wu, L., Zhu, J., Peng, T., Xia, Y., He, L., Xie, S., Qin, T., Liu, H., He, K., et al. (2023) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3580305.3599468 · Cited by 11 · see citing works
De Novo Protein Design Using the Blueprint Builder in Rosetta
An, L., & Lee, G. R. (2020) · Current Protocols in Protein Science · doi:10.1002/cpps.116 · Cited by 11 · see citing works
RosettaAntibodyDesign (RAbD): A General Framework for Computational Antibody DesignPreprint
Adolf-Bryfogle, J., Kalyuzhniy, O., Kubitz, M., Weitzner, B. D., Hu, X., Adachi, Y., Schief, W. R., & Dunbrack, R. L. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/183350 · Cited by 11 · see citing works
Challenges in Detection of Serum Oncoprotein: Relevance to Breast Cancer Diagnostics
Lengfeld, J. E., Zhang, H., Stoesz, S. P., Murali, R., Pass, F., Greene, M. I., Goel, P. N., & Grover, P. (2021) · Breast Cancer Targets and Therapy · doi:10.2147/bctt.s331844 · Cited by 10 · see citing works
Lee, D. C. P., Raman, R., Ghafar, N. A., & Budigi, Y. (2021) · Antiviral Research · doi:10.1016/j.antiviral.2021.105105 · Cited by 8 · see citing works
Artificial intelligence in protein-based detection and inhibition of AMR pathways
Sadhukhan, S., Bhattacharya, R., Bhattcharya, D., Sahana, S., Pradhan, B., Pandit, S., Gill, H. S., Rajeev, M., Nag, M., & Lahiri, D. (2025) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-025-00710-4 · Cited by 8 · see citing works
Key aspects of the past 30 years of protein design
Meconi, G. M., Sasselli, I. R., Bianco, V., Onuchic, J. N., & Coluzza, I. (2022) · Reports on Progress in Physics · doi:10.1088/1361-6633/ac78ef · Cited by 8 · see citing works
MutDock: A computational docking approach for fixed-backbone protein scaffold design
Chauhan, V. M., & Pantazes, R. J. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.933400 · Cited by 8 · see citing works
Abduljaleel, Z., Shahzad, N., Aziz, S. A., & Malik, S. M. (2022) · Molecular Diversity · doi:10.1007/s11030-022-10449-x · Cited by 7 · see citing works
Shah, M., & Woo, H. G. (2022) · Molecular Therapy · doi:10.1016/j.ymthe.2022.08.020 · Cited by 7 · see citing works
Force-Field Benchmarking by Alternatives: A Systematic Study of Ten Small α- and β-ProteinsPreprint
Jana, K., & Kepp, K. P. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.03.974477 · Cited by 7 · see citing works
In silico design of stable single-domain antibodies with high affinityPreprint
Zhang, Z., van der Kant, R., Marković, I., Vizarraga, D., Garcia, T., Maragkou, K., Delgado, J., Cianferoni, D., Orlando, G., Cia, G., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.22.589762 · Cited by 7 · see citing works
AntiBMPNN: Structure‐Guided Graph Neural Networks for Precision Antibody Engineering
Sun, Z., Yuan, J., Jaiswal, D., Ge, J., Liang, T., Wei, J., Cao, J., Li, Y., Chu, X., Chen, Y., et al. (2025) · Advanced Science · doi:10.1002/advs.202504278 · Cited by 7 · see citing works
Nanodesigner: resolving the complex-CDR interdependency with iterative refinement
Zertuche, M. M. R., Kafkas, Ş., Renn, D., Rueping, M., & Hoehndorf, R. (2025) · Journal of Cheminformatics · doi:10.1186/s13321-025-01069-2 · Cited by 6 · see citing works
Corbeil, C. R., Manenda, M. S., Sulea, T. I., Baardsnes, J., Picard, M.-È., Hogues, H., Gaudreault, F., Deprez, C., Shi, R., & Purisima, E. O. (2021) · Scientific Reports · doi:10.1038/s41598-021-00669-w · Cited by 6 · see citing works
GNN-based Antibody Structure Prediction using Quaternion and Euler Angle Combined Representation
Son, Y.-H., Shin, D.-H., Han, J.-W., Won, S.-H., & Kam, T. (2022) · IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia) · doi:10.1109/icce-asia57006.2022.9954877 · Cited by 6 · see citing works
Progress toward new function and design of extracellular G protein-coupled receptor nanobodies
Schlimgen, R. R., & Volkman, B. F. (2025) · Molecular Pharmacology · doi:10.1016/j.molpha.2025.100054 · Cited by 5 · see citing works
Zhu, Y., Shi, X., Zhang, J., Sun, W., & Wang, L. (2025) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5c00990 · Cited by 4 · see citing works
Higher Affinity Antibodies Bind With Lower Hydration and Flexibility in Large Scale Simulations
Wong, M. T. Y., Kelm, S., Liu, X., Taylor, R. D., BAKER, T. S., & Essex, J. W. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.884110 · Cited by 4 · see citing works
Shah, M., Shin, J.-Y., & Woo, H. G. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1113175 · Cited by 4 · see citing works
Wang, Z., Li, X.-G., Xie, Y., Wen, Z., Jin, R., Takada, H., & Nagatomi, R. (2024) · IEEE Access · doi:10.1109/access.2024.3416461 · Cited by 3 · see citing works
In silico design of stable single-domain antibodies with high affinity
Zhang, Z., van der Kant, R., Marković, I., Vizarraga, D., Garcia, T., Maragkou, K., Blanco, J. D., Cianferoni, D., Orlando, G., Cia, G., et al. (2026) · Structure · doi:10.1016/j.str.2025.12.010 · Cited by 10 · see citing works
RosettaCM for antibodies with very long HCDR3s and low template availability
Kodali, P., Schoeder, C. T., Schmitz, S., Crowe, J. E., & Meiler, J. (2021) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.26166 · Cited by 2 · see citing works
GeoAB: Towards Realistic Antibody Design and Reliable Affinity MaturationPreprint
Lin, H., Wu, L., Huang, Y., Liu, Y., Zhang, O., Zhou, Y., Sun, R., & Li, S. Z. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.15.594274 · Cited by 2 · see citing works
A synergistic strategy for E2E+ESM2-driven protein a design and wet lab validation
Song, H., Zhang, S., He, Q. Z., Zhang, H., Fang, C., & Lin, X. (2025) · Methods · doi:10.1016/j.ymeth.2025.03.008 · Cited by 1 · see citing works
Bioinformatics Resources, Tools, and Strategies in Designing Therapeutic Proteins
Sudhan, M., Roshni, J., Janakiraman, V., Sivakumar, M., & Ahmed, S. F. (2022) · Springer eBooks · doi:10.1007/978-981-16-7897-4_7 · Cited by 1 · see citing works
Antibody Modeling, Engineering, and Design
Fischman, S., & Ofran, Y. (2018) · Springer eBooks · doi:10.1007/978-3-642-35943-9_10083-1
Bonadio, A., Wenig, B. L., Hockla, A., Radisky, E. S., & Shifman, J. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.29.522231
Virtual Screening of Synthetic Proteins Based on ESM2 ModelPreprint
Song, H., Lin, X., Zhao, L., & Wen, Z. (2024) · Research Square · doi:10.21203/rs.3.rs-3890441/v1
Artificial intelligence design of ProteinA-like peptides
Zhao, L., Song, H., Lin, Z., Wen, Z., & Lin, X. (2024) · International Conference on Bioinformatics and Intelligent Computing (BIC) · doi:10.1145/3665689.3665753
Jamialahmadi, B., Chamankhah, M., Kohandel, M., & Ghodsi, A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.16.603820
Bauer, J., Kube, S., Gupta, P. K., & Kumar, S. (2024) · Springer eBooks · doi:10.1007/978-3-031-62007-2_14
DiffNB: Aligning a Nanobody Diffusion Model with Direct Preference Optimization
Wu, Y., JiaShu, Wu, D., Qin, Y., Plötz, T., Hrovatin, K., Linker, S. M., Hopp, A. V., Winkel, M., Harbach, P. H. P., et al. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356690
- Authors
- Lapidoth, G. D., Baran, D., Pszolla, G. M., Norn, C., Alon, A., Tyka, M. D., & Fleishman, S. J.
- Affiliations
- Weizmann Institute of Science (IL)
- Google (United States) (US)
- Corresponding author
- Fleishman, Sarel J.
- Venue
- Proteins Structure Function and Bioinformatics
- Publisher
- Wiley
- Published
- 2015-06-06
- Volume
- 83
- Issue
- 8
- Pages
- 1385-1406
- ISSN
- 0887-3585 (ISSN-L)
- PMC
- PMC4881815
- OpenAlex
- W1956208665
- Cited by
- 107
- References
- 115
- Citations by year
- 2026: 8 · 2025: 12 · 2024: 11 · 2023: 6 · 2022: 18 · 2021: 10 · 2020: 8 · 2019: 8 · 2018: 13 · 2017: 8 · 2016: 5
- FWCI
- 3.76
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proteins Structure Function and Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- European Research Council (ERC-2013-StG-335439)
- Israel Science Foundation (1224/12)
- Israeli Centers for Research Excellence (1775/12)
- Human Frontier Science Program (CDA 34/2012)
- Marie Curie Cancer Care (PCIG11-GA-2012-320388)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chemical Synthesis and Analysis
- Keywords
- antibody design, sequence optimization, combinatorial designs, hypervariable region, lysozyme, binding affinity, protein-protein docking
- MeSH terms
- Algorithms, Amino Acid Sequence, Humans, Molecular Sequence Data, Protein Conformation, Protein Engineering, Fuzzy Logic, Computational Biology, Sequence Analysis, Protein, Complementarity Determining Regions
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