Computational tools for aiding rational antibody design
Abstract
Antibodies are a group of proteins responsible for mediating immune reactions in vertebrates. They are able to bind a variety of structural motifs on noxious molecules tagging them for elimination from the organism. As a result of their versatile binding properties, antibodies are currently one of the most important classes of biopharmaceuticals. In this chapter, we discuss how knowledge-based computational methods can aid experimentalists in the development of potent antibodies. When using common experimental methods for antibody development, we often know the sequence of an antibody that binds to our molecule, antigen, of interest. We may also have a structure or model of the antigen. In these cases, computational methods can help by both modeling the antibody and identifying the antibody-antigen contact residues. This information can then play a key role in the rational design of more potent antibodies.
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Computational approaches hold promise in advancing the field by providing faster results than arduous experimental approaches that are the current standard in antibody discovery.
“Computational approaches hold promise in advancing the field by providing faster results than arduous experimental approaches that are the current standard in antibody discovery [5].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [5]
Routine bioinformatics methods such as homology modelling and protein-protein docking can be harnessed to guide the engineering of therapeutic antibodies.
“Routine bioinformatics methods such as homology modelling and protein–protein docking can be harnessed to guide the engineering of therapeutic antibodies [5].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [5]
Cites
Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196 · 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
ZDOCK: An initial‐stage protein‐docking algorithm
Chen, R., Li, L., & Weng, Z. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10389 · Cited by 1,393 · 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
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
IgBLAST: an immunoglobulin variable domain sequence analysis tool
Ye, J., Ma, N., Madden, T., & Ostell, J. M. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt382 · Cited by 1,161 · see citing works
Lefranc, M., Pommie, C., Ruíz, M., Giudicelli, V., Foulquier, E., Truong, L., Contet, V., & Lefranc, G. (2002) · Developmental & Comparative Immunology · doi:10.1016/s0145-305x(02)00039-3 · Cited by 823 · see citing works
Lefranc, M., Pommie, C., Kaas, Q., Duprat, É., Bosc, N., Guiraudou, D., Jean, C., Ruíz, M., da Piedade, I., Rouard, M., et al. (2004) · Developmental & Comparative Immunology · doi:10.1016/j.dci.2004.07.003 · Cited by 808 · 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
Reliable B cell epitope predictions: impacts of method development and improved benchmarking
Kringelum, J. V., Lundegaard, C., Lund, O., & Nielsen, M. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002829 · Cited by 697 · 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
Self-citationAntibody 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
Immune epitope database analysis resource
Kim, Y., Ponomarenko, J. V., Zhu, Z., Tamang, D., Wang, P., Greenbaum, J., Lundegaard, C., Sette, A., Lund, O., Bourne, P. E., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks438 · Cited by 511 · see citing works
Antibody-antigen Interactions: Contact Analysis and Binding Site Topography
MacCallum, R. M., Martin, A. C. R., & Thornton, J. M. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0548 · Cited by 473 · 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
Three-dimensional structure of an intact human immunoglobulin.
Silverton, E. W., Navia, M. A., & Davies, D. R. (1977) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.74.11.5140 · Cited by 375 · 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
Morea, V., Tramontano, A. L., Rustici, M., Chothia, C., & Lesk, A. M. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.1442 · Cited by 327 · see citing works
Prediction of protein conformational freedom from distance constraints
de Groot, B. L., van Aalten, D. M. F., Scheek, R. M., Amadei, A., Vriend, G., & Berendsen, H. J. C. (1997) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(199710)29:2 · Cited by 269 · see citing works
Ehrenmann, F., Kaas, Q., & Lefranc, M. (2009) · Nucleic Acids Res. · doi:10.1093/nar/gkp946 · Cited by 261 · see citing works
Honegger, A., & Plückthun, A. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2001.4662 · Cited by 249 · see citing works
Analysis and improvements to Kabat and structurally correct numbering of antibody variable domains
Abhinandan, K. R., & Martin, A. C. R. (2008) · Molecular Immunology · doi:10.1016/j.molimm.2008.05.022 · Cited by 234 · see citing works
Antibody-protein interactions: benchmark datasets and prediction tools evaluation
Ponomarenko, J. V., & Bourne, P. E. (2007) · BMC Structural Biology · doi:10.1186/1472-6807-7-64 · Cited by 226 · see citing works
Computer-aided antibody design
Kuroda, D., Shirai, H., Jacobson, M. P., & Nakamura, H. (2012) · Protein Engineering Design and Selection · doi:10.1093/protein/gzs024 · Cited by 222 · see citing works
Application of asymmetric statistical potentials to antibody-protein docking
Brenke, R., Hall, D., Chuang, G., Comeau, S. R., Bohnuud, T., Beglov, D., Schueler-Furman, O., Vajda, S., & Kozakov, D. (2012) · Bioinform. · doi:10.1093/bioinformatics/bts493 · Cited by 205 · see citing works
Sivasubramanian, A., Sircar, A., Chaudhury, S., & Gray, J. J. (2008) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22309 · Cited by 185 · see citing works
PIGS: automatic prediction of antibody structures
Marcatili, P., Rosi, A., & Tramontano, A. L. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn341 · Cited by 174 · see citing works
Improving B-cell epitope prediction and its application to global antibody–antigen docking
Krawczyk, K., Liu, X., Baker, T., Shi, J., & Deane, C. M. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu190 · Cited by 174 · see citing works
Sequencing the functional antibody repertoire—diagnostic and therapeutic discovery
Robinson, W. H. (2014) · Nature Reviews Rheumatology · doi:10.1038/nrrheum.2014.220 · Cited by 171 · see citing works
Antibody Engineering for the Development of Therapeutic Antibodies
Kim, S. J., Park, Y.-W., & Hong, H. J. (2005) · Molecules and Cells · doi:10.1016/s1016-8478(23)25245-0 · Cited by 167 · see citing works
Sircar, A., & Gray, J. J. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000644 · Cited by 166 · see citing works
FREAD revisited: accurate loop structure prediction using a database search algorithm
Choi, Y., & Deane, C. M. (2010) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22658 · Cited by 161 · see citing works
Self-citationRosettaAntibody: antibody variable region homology modeling server
Sircar, A., Kim, E. T., & Gray, J. J. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp387 · Cited by 161 · see citing works
WAM: an improved algorithm for modelling antibodies on the WEB
Whitelegg, N., & Rees, A. R. (2000) · Protein Engineering Design and Selection · doi:10.1093/protein/13.12.819 · Cited by 159 · see citing works
Antibody humanization methods – a review and update
Safdari, Y., Farajnia, S., Asgharzadeh, M., & Khalili, M. (2013) · Biotechnology and Genetic Engineering Reviews · doi:10.1080/02648725.2013.801235 · Cited by 157 · see citing works
Second antibody modeling assessment (AMA-II)
Almagro, J. C., Teplyakov, A., Luo, J., Sweet, R. W., Kodangattil, S., Hernandez‐Guzman, F., & Gilliland, G. L. (2014) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24567 · Cited by 144 · see citing works
CED: a conformational epitope database.
Huang, J. H., & Honda, W. (2006) · BMC Immunology · doi:10.1186/1471-2172-7-7 · Cited by 140 · see citing works
Antibody discovery: phage display
Kretzschmar, T., & von Rüden, T. (2002) · Current Opinion in Biotechnology · doi:10.1016/s0958-1669(02)00380-4 · Cited by 138 · see citing works
Kunik, V., Ashkenazi, S., & Ofran, Y. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks480 · Cited by 132 · see citing works
Which are the antibodies to watch in 2013?
Reichert, J. M. (2013) · mAbs · doi:10.4161/mabs.22976 · Cited by 128 · see citing works
Structural classification of CDR‐H3 revisited: A lesson in antibody modeling
Kuroda, D., Shirai, H., Kobori, M., & Nakamura, H. (2008) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22087 · Cited by 127 · see citing works
ABangle: characterising the VH-VL orientation in antibodies
Dunbar, J., Fuchs, A., Shi, J., & Deane, C. M. (2013) · Protein Engineering Design and Selection · doi:10.1093/protein/gzt020 · Cited by 125 · see citing works
PyIgClassify: a database of antibody CDR structural classifications
Adolf‐Bryfogle, J., Xu, Q., North, B., Lehmann, A., & Dunbrack, R. L. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1106 · Cited by 120 · see citing works
Concepts in antibody phage display
Carmen, S. (2002) · Briefings in Functional Genomics and Proteomics · doi:10.1093/bfgp/1.2.189 · Cited by 119 · see citing works
Structural consensus among antibodies defines the antigen binding site
Kunik, V., Peters, B., & Ofran, Y. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002388 · Cited by 117 · see citing works
Lapidoth, 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 · see citing works
Lefranc, M. (2011) · Cold Spring Harbor Protocols · doi:10.1101/pdb.ip85 · Cited by 105 · 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
Kunik, V., & Ofran, Y. (2013) · Protein Engineering Design and Selection · doi:10.1093/protein/gzt027 · Cited by 96 · see citing works
Reichert, J. M. (2010) · mAbs · doi:10.4161/mabs.2.1.10677 · Cited by 91 · see citing works
Prediction of site-specific interactions in antibody–antigen complexes: the proABC method and server
Olimpieri, P. P., Chailyan, A., Tramontano, A., & Marcatili, P. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt369 · Cited by 90 · see citing works
Analysis and prediction of VH/VL packing in antibodies
Abhinandan, K. R., & Martin, A. C. R. (2010) · Protein Engineering Design and Selection · doi:10.1093/protein/gzq043 · Cited by 88 · see citing works
Krawczyk, K., Baker, T., Shi, J., & Deane, C. M. (2013) · Protein Engineering Design and Selection · doi:10.1093/protein/gzt043 · Cited by 87 · see citing works
Self-citationOliva, B., Bates, P. A., Querol, E., Avilés, F. X., & Sternberg, M. J. E. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.1847 · Cited by 83 · see citing works
Structural determinants of the conformations of medium‐sized loops in proteins
Tramontano, A. L., Chothia, C., & Lesk, A. M. (1989) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340060405 · Cited by 77 · see citing works
Antibody informatics for drug discovery
Shirai, H., Prades, C., Vita, R., Marcatili, P., Popovic, B., Xu, J., Overington, J. P., Hirayama, K., Soga, S., Tsunoyama, K., et al. (2014) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2014.07.006 · Cited by 73 · see citing works
Fera, D., Schmidt, A. G., Haynes, B. F., Gao, F., Liao, H., Kepler, T. B., & Harrison, S. C. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1409954111 · Cited by 71 · see citing works
Using a combined computational-experimental approach to predict antibody-specific B cell epitopes
Sela-Culang, I., Benhnia, M. R.-E.-I., Matho, M. H., Kaever, T., Maybeno, M., Schlossman, A., Nimrod, G., Li, S., Xiang, Y., Zajonc, D., et al. (2014) · Structure · doi:10.1016/j.str.2014.02.003 · Cited by 69 · see citing works
Prediction of VH-VL domain orientation for antibody variable domain modeling
Bujotzek, A., Dunbar, J., Lipsmeier, F., Schäfer, W., Antes, I., Deane, C. M., & Georges, G. (2015) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24756 · Cited by 56 · see citing works
Functional Mapping of Conserved Residues Located at the VL and VH Domain Interface of a Fab
Chatellier, J., Regenmortel, M. H. V. V., Vernet, T., et al. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0618 · Cited by 53 · see citing works
Shirai, H., Ikeda, K., Yamashita, K., Tsuchiya, Y., Sarmiento, J., Liang, S., Morokata, T., Mizuguchi, K., Higo, J., Standley, D. M., et al. (2014) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24591 · Cited by 51 · see citing works
Nakanishi, T., Tsumoto, K., Yokota, A., et al. (2008) · Protein Science · doi:10.1110/ps.073156708 · Cited by 50 · see citing works
Reichert, J. M. (2014) · mAbs · doi:10.4161/mabs.29282 · Cited by 47 · see citing works
Hasegawa, K., Kubota, M., & Matsuura, Y. (1999) · Protein Engineering Design and Selection · doi:10.1093/protein/12.10.819 · Cited by 46 · see citing works
Predicting antibody complementarity determining region structures without classification
Choi, Y., & Deane, C. M. (2011) · Molecular BioSystems · doi:10.1039/c1mb05223c · Cited by 44 · see citing works
Self-citationThe three-dimensional structure ofEscherichia coliporphobilinogen deaminase at 1.76-Å resolution
Louie, G. V., Brownlie, P. D., Lambert, R., Cooper, J. B., Blundell, T. L., Wood, S., Malashkevich, V. N., Hädener, A., Warren, M. J., & Shoolingin‐Jordan, P. M. (1996) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(199605)25:1 · Cited by 43 · see citing works
Narayanan, A., Sellers, B. D., & Jacobson, M. P. (2009) · Journal of Molecular Biology · doi:10.1016/j.jmb.2009.03.043 · Cited by 41 · see citing works
Protein Sequence and Structure Analysis of Antibody Variable Domains
Martin, A. C. R. (2010) · Springer eBooks · doi:10.1007/978-3-642-01147-4_3 · Cited by 27 · see citing works
Murad, J. P., Lin, O., Espinosa, E. V. P., & Khasawneh, F. T. (2012) · Current Molecular Medicine · doi:10.2174/156652413804486322 · Cited by 13 · see citing works
A complete, multi-level conformational clustering of antibody complementarity-determining regions
Nikoloudis, D., Pitts, J. E., & Saldanha, J. W. (2014) · PeerJ · doi:10.7717/peerj.456 · Cited by 9 · see citing works
Murad, J. P., Lin, O. A., Espinosa, E. V. P., & Khasawneh, F. T. (2012) · Current Molecular Medicine · doi:10.2174/1566524011307010165 · Cited by 2 · see citing works
Nagl, S., Das, S., & Smith, T. (2000) · Journal of Molecular Recognition · doi:10.1002/1099-1352(200005/06)13:3
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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
“Routine bioinformatics methods such as homology modelling and protein–protein docking can be harnessed to guide the engineering of therapeutic antibodies [5].”
BackgroundMethodSelf-citationLooking for therapeutic antibodies in next generation sequencing repositories
Krawczyk, K., Raybould, M., Kovaltsuk, A., & Deane, C. M. (2019) · doi:10.1101/572958 · Cited by 29 · see citing works
Self-citationAntibody 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
- Authors
- Krawczyk, K., Dunbar, J., & Deane, C. M.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Deane, Charlotte M.
- Venue
- Methods in molecular biology
- Publisher
- Springer New York
- Published
- 2016-12-03
- Volume
- 1529
- Pages
- 399-416
- ISSN
- 1064-3745 (ISSN-L)
- 1940-6029
- OpenAlex
- W2558637998
- Cited by
- 26
- References
- 73
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2023: 4 · 2022: 4 · 2021: 3 · 2019: 3 · 2018: 4 · 2017: 3
- FWCI
- 15.41
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Methods in molecular biology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- antibody design, rational antibody design, antibody-antigen binding, antigenic structure, biopharmaceuticals, computational antibody design
- MeSH terms
- Amino Acid Sequence, Animals, Antibodies, Epitopes, Antigens, Binding Sites, Humans, Immunoglobulin Heavy Chains, Immunoglobulin Light Chains, Models, Molecular, Protein Binding, Protein Conformation, Software, Structure-Activity Relationship, Protein Engineering, Computational Biology, Complementarity Determining Regions, Databases, Genetic, Mice, Molecular Dynamics Simulation, Molecular Docking Simulation, Web Browser
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