Data-Driven Antibody Engineering Using Genedata Biologics™

  • Maria WendtEmail author
  • Guido Cappuccilli
Part of the Methods in Molecular Biology book series (MIMB, volume 1575)


Genedata Biologics is a novel informatics platform specifically designed for biologics R&D. Here, we discuss the main principles employed in designing such a platform, focusing on antibody engineering. To illustrate, we present a case study of how the platform effectively supports an antibody optimization workflow and ensures the successful integration and analysis of all relevant sequence, expression, assay, and analytics data.

Key words

Antibody engineering Antibody library design Bioinformatics Biologics database Data visualization Mutagenesis 


  1. 1.
    Schlinkmann KM, Hillenbrand M, Rittner A, Künz M, Strohner R, Plückthun A (2012) Maximizing detergent stability and functional expression of a GPCR by exhaustive recombination and evolution. J Mol Biol 422(3):414–428. doi: 10.1016/j.jmb.2012.05.039 Epub 2012 Jun 6. PubMed PMID: 22683350CrossRefPubMedGoogle Scholar
  2. 2.
    Dokarry M, Laurendon C, O'Maille PE (2012) Automating gene library synthesis by structure-based combinatorial protein engineering: examples from plant sesquiterpene synthases. Methods Enzymol 515:21–42. doi: 10.1016/B978-0-12-394290-6.00002-1 PubMed PMID: 22999168CrossRefPubMedGoogle Scholar
  3. 3.
    Debaene F, Wagner-Rousset E, Colas O, Ayoub D, Corvaïa N, Van Dorsselaer A, Beck A, Cianférani S (2013) Time resolved native ion-mobility mass spectrometry to monitor dynamics of IgG4 Fab arm exchange and "bispecific" monoclonal antibody formation. Anal Chem 85(20):9785–9792. doi: 10.1021/ac402237v Epub 2013 Sep 26 . PubMed PMID: 24007193CrossRefPubMedGoogle Scholar
  4. 4.
    Birdsall RE, Shion H, Kotch FW, Xu A, Porter TJ, Chen W (2015) A rapid on-line method for mass spectrometric confirmation of a cysteine-conjugated antibody-drug-conjugate structure using multidimensional chromatography. MAbs 7(6):1036–1044. doi: 10.1080/19420862.2015.1083665 Epub 2015 Aug 25. PubMed PMID: 26305867; PubMed Central PMCID: PMC4966495CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Zambrano R, Jamroz M, Szczasiuk A, Pujols J, Kmiecik S, Ventura S (2015) AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures. Nucleic Acids Res 43(W1):W306–W313. doi: 10.1093/nar/gkv359 Epub 2015 Apr 16. PubMed PMID: 25883144; PubMed Central PMCID: PMC4489226.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Chaparro-Riggers JF, Polizzi KM, Bommarius AS (2007) Better library design: data-driven protein engineering. Biotechnol J 2(2):180–191 Review PubMed PMID: 17183506CrossRefPubMedGoogle Scholar
  7. 7.
    Rajpal A, Beyaz N, Haber L, Cappuccilli G, Yee H, Bhatt RR, Takeuchi T, Lerner RA, Crea R (2005) A general method for greatly improving the affinity of antibodies by using combinatorial libraries. Proc Natl Acad Sci U S A 102(24):8466–8471 Epub 2005 Jun 6. PubMed PMID: 15939870; PubMed Central PMCID: PMC1143585CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Kempeni J (1999) Preliminary results of early clinical trials with the fully human anti-TNFalpha monoclonal antibody D2E7. Ann Rheum Dis 58(Suppl 1):I70–I72 Review. PubMed PMID: 10577977; PubMed Central PMCID: PMC1766582CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Genedata AGBaselSwitzerland

Personalised recommendations