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Looking for Therapeutic Antibodies in Next Generation Sequencing Repositories
Open accessAbstract
Recently it has become possible to query the great diversity of natural antibody repertoires using Next Generation Sequencing (NGS). These methods are capable of producing millions of sequences in a single experiment. Here we compare Clinical Stage Therapeutic antibodies to the ∼1b sequences from 60 independent sequencing studies in the Observed Antibody Space Database. Of the 242 post Phase I antibodies, we find 16 with sequence identity matches of 95% or better for both heavy and light chains. There are also 54 perfect matches to therapeutic CDR-H3 regions in the NGS outputs, suggesting a nontrivial amount of convergence between naturally observed sequences and those developed artificially. This has potential implications for both the discovery of antibody therapeutics and the legal protection of commercial antibodies.
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“Furthermore, many therapeutic CDRH3 loops can be found in naturally sourced NGS datasets, indicating a certain degree of convergence between antibodies raised experimentally and naturally occurring ones [225].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [225]
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Cites
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
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
Knappik, A., Ge, L., Honegger, A., Pack, P., Fischer, M., Wellnhofer, G., Hoess, A., Wölle, J., Plückthun, A., & Virnekäs, B. (2000) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.3444 · Cited by 728
The promise and challenge of high-throughput sequencing of the antibody repertoire
Georgiou, G., Ippolito, G. C., Beausang, J., Busse, C. E., Wardemann, H., & Quake, S. R. (2014) · Nature Biotechnology · doi:10.1038/nbt.2782 · Cited by 652
Biophysical properties of the clinical-stage antibody landscape
Jain, T., Sun, T., Durand, S., Hall, A., Houston, N. R., Nett, J. H., Sharkey, B., Bobrowicz, B., Caffry, I., Yu, Y., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1616408114 · Cited by 629 · cited 1×
“reflect the myriad antibody types, including fully human, humanized, chimeric or fully mouse.(19) The individual identities of the CSTs with respect to the best match from OAS are”
BackgroundCommonality despite exceptional diversity in the baseline human antibody repertoire
Briney, B., Inderbitzin, A., Joyce, C., & Burton, D. R. (2019) · Nature · doi:10.1038/s41586-019-0879-y · Cited by 544
The structural basis of antibody–antigen recognition
Sela-Culang, I., Kunik, V., & Ofran, Y. (2013) · Frontiers in Immunology · doi:10.3389/fimmu.2013.00302 · Cited by 530
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
Glanville, J., Zhai, W., Berka, J., Telman, D., Huerta, G., Mehta, G. R., Ni, I., Mei, L., Sundar, P. D., Day, G. M. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0909775106 · Cited by 440
ANARCI: antigen receptor numbering and receptor classification
Dunbar, J., & Deane, C. M. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv552 · Cited by 421
Self-citationHigh-throughput sequencing of the paired human immunoglobulin heavy and light chain repertoire
DeKosky, B. J., Ippolito, G. C., Deschner, R. P., Lavinder, J. J., Wine, Y., Rawlings, B. M., Varadarajan, N., Giesecke, C., Dörner, T., Andrews, S. F., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2492 · Cited by 410 · cited 1×
“a more comprehensive view of the convergence between naturally sourced and artificially developed sequences.(2,30,31) Thirdly, artificial nucleotide mutations can be introduced at random to antibody sequences by NGS techniques as well as during DNA sample preparation.”
BackgroundFive computational developability guidelines for therapeutic antibody profiling
Raybould, M. I. J., Marks, C., Krawczyk, K., Taddese, B., Nowak, J., Lewis, A. P., Bujotzek, A., Shi, J., & Deane, C. M. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1810576116 · Cited by 357
Self-citationMorea, 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
Kovaltsuk, A., Leem, J., Kelm, S., Snowden, J., Deane, C. M., & Krawczyk, K. (2018) · The Journal of Immunology · doi:10.4049/jimmunol.1800708 · Cited by 247
Self-citationDeKosky, B. J., Lungu, O. I., Park, D., Johnson, E. L., Charab, W., Chrysostomou, C., Kuroda, D., Ellington, A. D., Ippolito, G. C., Gray, J. J., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1525510113 · Cited by 189
Miho, E., Yermanos, A., Weber, C. R., Berger, C. T., Reddy, S. T., & Greiff, V. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00224 · Cited by 189
Community, T. A., Rubelt, F., Busse, C. E., Bukhari, S. A. C., Bürckert, J.-P., Mariotti-Ferrandiz, E., Cowell, L. G., Watson, C. T., Marthandan, N., Faison, W. J., et al. (2017) · Nature Immunology · doi:10.1038/ni.3873 · Cited by 178
de Kruif, J., Boel, E., & Logtenberg, T. (1995) · Journal of Molecular Biology · doi:10.1006/jmbi.1995.0204 · Cited by 173
Greiff, V., Menzel, U., Miho, E., Weber, C. R., Riedel, R., Cook, S. C., Valai, A., Lopes, T., Radbruch, A., Winkler, T., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.04.054 · Cited by 167
Large-scale network analysis reveals the sequence space architecture of antibody repertoires
Miho, E., Roškar, R., Greiff, V., & Reddy, S. T. (2019) · Nature Communications · doi:10.1038/s41467-019-09278-8 · Cited by 138
Reproducibility and Reuse of Adaptive Immune Receptor Repertoire Data
Breden, F. J., Prak, E. T. L., Peters, B., Rubelt, F., Schramm, C. A., Busse, C. E., Heiden, J. A. V., Christley, S., Bukhari, S. A. C., Thorogood, A., et al. (2017) · Frontiers in Immunology · doi:10.3389/fimmu.2017.01418 · Cited by 107
Analyzing the ‘Degree of Humanness’ of antibody sequences
Abhinandan, K. R., & Martin, A. C. R. (2007) · Journal of Molecular Biology · doi:10.1016/j.jmb.2007.02.100 · Cited by 99
The diversity of H 3 loops determines the antigen‐binding tendencies of antibody CDR loops
Tsuchiya, Y., & Mizuguchi, K. (2016) · Protein Science · doi:10.1002/pro.2874 · Cited by 86
Antibody humanization by structure-based computational protein design
Choi, Y., Hua, C. K., Sentman, C. L., Ackerman, M. E., & Bailey‐Kellogg, C. (2015) · mAbs · doi:10.1080/19420862.2015.1076600 · Cited by 85
Christley, S., Scarborough, W., Salinas, E., Rounds, W. H., Toby, I. T., Fonner, J. M., Levin, M. K., Kim, M., Mock, S. A., Jordan, C., et al. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00976 · Cited by 72
The INNs and outs of antibody nonproprietary names
Jones, T. D., Carter, P. J., Plückthun, A., Vásquez, M., Holgate, R., Hötzel, I., Popplewell, A. G., Parren, P. W. H. I., Enzelberger, M. M., Rademaker, H. J., et al. (2015) · mAbs · doi:10.1080/19420862.2015.1114320 · Cited by 60
Mason, D. M., Friedensohn, S., Weber, C. R., Jordi, C., Wagner, B., Meng, S. M., Gaínza, P., Correia, B. E., & Reddy, S. T. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/617860 · Cited by 50
The Pipeline Repertoire for Ig-Seq Analysis
López-Santibáñez-Jácome, L., Avendaño-Vázquez, S. E., & Flores-Jasso, C. F. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.00899 · Cited by 46
Structurally mapping antibody repertoires
Krawczyk, K., Kelm, S., Kovaltsuk, A., Galson, J. D., Kelly, D., Trück, J., Regep, C., Leem, J., Wong, W. K., Nowak, J., et al. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01698 · Cited by 42
Self-citationComputational 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
Self-citationAntibody–antigen complex modelling in the era of immunoglobulin repertoire sequencing
Raybould, M. I. J., Wong, W. K., & Deane, C. M. (2019) · Molecular Systems Design & Engineering · doi:10.1039/c9me00034h · Cited by 14
Self-citationKovaltsuk, A., Krawczyk, K., Kelm, S., Snowden, J., & Deane, C. M. (2018) · The Journal of Immunology · doi:10.4049/jimmunol.1800669 · Cited by 12
Self-citationWas the Myriad decision a 'surgical strike' on isolated DNA patents, or does it have wider impacts?
Aboy, M., Crespo, C., Liddell, K., Liddicoat, J., & Jordan, M. (2018) · Nature Biotechnology · doi:10.1038/nbt.4308 · Cited by 12
(2013) · Biotechnology Law Report · doi:10.1089/blr.2013.9877 · Cited by 12
Harrison, C. (2012) · Nature Reviews Drug Discovery · doi:10.1038/nrd3641 · Cited by 9
Isolated DNA patent ban creates muddy waters for biomarkers and natural products
Harrison, C. (2013) · Nature Reviews Drug Discovery · doi:10.1038/nrd4084 · Cited by 6
Patentability of antibodies for therapeutic use in Europe
Germinario, C., Bertoli, S., Rampinelli, P., & Cini, M. (2018) · Nature Biotechnology · doi:10.1038/nbt.4134 · Cited by 6
The pipeline repertoire of Ig-Seq analysisPreprint
López-Santibáñez-Jácome, L., Avendaño-Vázquez, S. E., & Flores-Jasso, C. F. (2018) · doi:10.7287/peerj.preprints.27444v1 · Cited by 3
Next-generation sequencing may challenge antibody patent claims
Prabakaran, P. (2018) · Nature · doi:10.1038/d41586-018-05065-5 · Cited by 2
Harrison, C. (2012) · Nature Reviews Drug Discovery · doi:10.1038/nrd3735 · Cited by 2
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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
“Furthermore, many therapeutic CDRH3 loops can be found in naturally sourced NGS datasets, indicating a certain degree of convergence between antibodies raised experimentally and naturally occurring ones [225].”
BackgroundSelf-citationPrihoda, D., Maamary, J., Waight, A., Juan, V., Fayadat-Dilman, L., Svozil, D., & Bitton, D. A. (2022) · mAbs · doi:10.1080/19420862.2021.2020203 · Cited by 190
Advances in computational structure-based antibody design
Hummer, A. M., Abanades, B., & Deane, C. M. (2022) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2022.102379 · Cited by 109
Self-citationKhetan, R., Curtis, R., Deane, C. M., Hadsund, J. T., Kar, U., Krawczyk, K., Kuroda, D., Robinson, S. A., Sormanni, P., Tsumoto, K., et al. (2022) · mAbs · doi:10.1080/19420862.2021.2020082 · Cited by 93
Self-citationWilman, W., Wróbel, S., Bielska, W., Deszyński, P., Dudzic, P., Jaszczyszyn, I., Kaniewski, J., Młokosiewicz, J., Rouyan, A., Satława, T., et al. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac267 · Cited by 86
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Metadata
- Authors
- Krawczyk, K., Raybould, M., Kovaltsuk, A., & Deane, C. M.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Krawczyk, Konrad
- Venue
- mAbs
- Publisher
- openRxiv
- Published
- 2019-03-09
- Volume
- 11
- Issue
- 7
- Pages
- 1197-1205
- ISSN
- 1942-0862 (ISSN-L)
- PMC
- PMC6748601
- OpenAlex
- W2950135969
- Cited by
- 29
- References
- 40
- Citations by year
- 2025: 3 · 2024: 2 · 2023: 3 · 2022: 9 · 2021: 5 · 2020: 5 · 2019: 2
- FWCI
- 3.47
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- mAbs (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Engineering and Physical Sciences Research Council (1795796)
- Biotechnology and Biological Sciences Research Council (1801486, BB/M011224/1)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Life Sciences › Immunology and Microbiology › Immunology › Biosimilars and Bioanalytical Methods
- Keywords
- therapeutic antibodies, immunoglobulin gene repertoire
- MeSH terms
- Humans, Immunoglobulins, Immunotherapy, Complementarity Determining Regions, Databases, Genetic, Immunity, Humoral, Data Mining, High-Throughput Nucleotide Sequencing
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