Abstract
Affinity maturation is an important stage in biologic drug discovery as is the natural process of generating an immune response inside the human body. In this chapter, we describe in silico approaches to affinity maturation via a worked example. Both advantages and limitations of the computational methods used are critically examined. Furthermore, construction of affinity maturation libraries and how their outputs might be implemented in an experimental setting are also described. It should be noted that structure-based design of biologic drugs is an emerging field and the tools currently available require further development. Furthermore, there are no standardized structure-based strategies yet for antibody affinity maturation as this research relies heavily on scientific logic as well as creative intuition.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kirkham PM, Schroeder HW Jr (1994) Antibody structure and the evolution of immunoglobulin V gene segments. Semin Immunol 6(6):347–360
Fanning LJ, Connor AM, Wu GE (1996) Development of the immunoglobulin repertoire. Clin Immunol Immunopathol 79(1):1–14
French DL, Laskov R, Scharff MD (1989) The role of somatic hypermutation in the generation of antibody diversity. Science 244(4909):1152–1157
Hoet RM et al (2005) Generation of high-affinity human antibodies by combining donor-derived and synthetic complementarity-determining-region diversity. Nat Biotechnol 23(3):344–348
Winter G et al (1994) Making antibodies by phage display technology. Annu Rev Immunol 12:433–455
Feldhaus MJ, Siegel RW (2004) Yeast display of antibody fragments: a discovery and characterization platform. J Immunol Methods 290(1–2):69–80
Hoogenboom HR et al (1998) Antibody phage display technology and its applications. Immunotechnology 4(1):1–20
Briney B et al (2019) Commonality despite exceptional diversity in the baseline human antibody repertoire. Nature 566(7744):393–397
Hsiao YC et al (2019) Immune repertoire mining for rapid affinity optimization of mouse monoclonal antibodies. MAbs 11(4):735–746
Schroeder HW Jr (2006) Similarity and divergence in the development and expression of the mouse and human antibody repertoires. Dev Comp Immunol 30(1–2):119–135
Berman HM et al (2000) The protein data bank. Nucleic Acids Res 28(1):235–242
Nimrod G et al (2018) Computational design of epitope-specific functional antibodies. Cell Rep 25(8):2121–2131 e5
Sormanni P, Aprile FA, Vendruscolo M (2018) Third generation antibody discovery methods: in silico rational design. Chem Soc Rev 47(24):9137–9157
Nishigami H, Kamiya N, Nakamura H (2016) Revisiting antibody modeling assessment for CDR-H3 loop. Protein Eng Des Sel 29(11):477–484
Kuhlman B, Bradley P (2019) Advances in protein structure prediction and design. Nat Rev Mol Cell Biol 20(11):681–697
Kenniston JA et al (2014) Inhibition of plasma kallikrein by a highly specific active site blocking antibody. J Biol Chem 289(34):23596–23608
Banerji A et al (2017) Inhibiting plasma kallikrein for hereditary angioedema prophylaxis. N Engl J Med 376(8):717–728
Norman RA et al (2019) Computational approaches to therapeutic antibody design: established methods and emerging trends. Brief Bioinform 21(5):1549–1567
http://www.chemcomp.com, Molecular Operating Environment (MOE), 2019.01; Chemical Computing Group ULC, 1010 Sherbrooke St. West, Suite #910, Montreal, QC, Canada, H3A 2R7, 2019
Labute P (2010) LowModeMD–implicit low-mode velocity filtering applied to conformational search of macrocycles and protein loops. J Chem Inf Model 50(5):792–800
Amimeur TS, Shaver JM, Ketchem RR, Taylor JA, Clark RH, Smith J, Van Citters D, Siska CC, Smidt P, Sprague M, Kerwin BA, Pettit D (2020) Designing feature-controlled humanoid antibody discovery libraries using generative adversarial networks. bioRxiv. https://doi.org/10.1101/2020.04.12.024844
Hughes RA, Ellington AD (2017) Synthetic DNA synthesis and assembly: putting the synthetic in synthetic biology. Cold Spring Harb Perspect Biol 9(1):a023812
Lim CC, Choong YS, Lim TS (2019) Cognizance of molecular methods for the generation of mutagenic phage display antibody libraries for affinity maturation. Int J Mol Sci 20(8):1861
Kumar S et al (2018) Biopharmaceutical informatics: supporting biologic drug development via molecular modelling and informatics. J Pharm Pharmacol 70(5):595–608
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Comeau, S.R., Thorsteinson, N., Kumar, S. (2023). Structural Considerations in Affinity Maturation of Antibody-Based Biotherapeutic Candidates. In: Tsumoto, K., Kuroda, D. (eds) Computer-Aided Antibody Design. Methods in Molecular Biology, vol 2552. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2609-2_17
Download citation
DOI: https://doi.org/10.1007/978-1-0716-2609-2_17
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-2608-5
Online ISBN: 978-1-0716-2609-2
eBook Packages: Springer Protocols