Literature DB >> 34747330

Differences in human IgG1 and IgG4 S228P monoclonal antibodies viscosity and self-interactions: Experimental assessment and computational predictions of domain interactions.

Pin-Kuang Lai1,2, Gaurav Ghag3, Yao Yu3, Veronica Juan3, Laurence Fayadat-Dilman3, Bernhardt L Trout1.   

Abstract

Human/humanized IgG4 antibodies have reduced effector function relative to IgG1 antibodies, which is desirable for certain therapeutic purposes. However, the developability and biophysical properties for IgG4 antibodies are not well understood. This work focuses on the head-to-head comparison of key biophysical properties, such as self-interaction and viscosity, for 14 human/humanized, and chimeric IgG1 and IgG4 S228P monoclonal antibody pairs that contain the identical variable regions. Experimental measurements showed that the IgG4 S228P antibodies have similar or higher self-interaction and viscosity than that of IgG1 antibodies in 20 mM sodium acetate, pH 5.5. We report sequence and structural drivers for the increased viscosity and self-interaction detected in IgG4 S228P antibodies through a combination of experimental data and computational models. Further, we applied and extended a previously established computational model for IgG1 antibodies to predict the self-interaction and viscosity behavior for each antibody pair, providing insight into the structural characteristics and differences of these two isotypes. Interestingly, we observed that the IgG4 S228P swapped variants, where the CH3 domain was swapped for that of an IgG1, showed reduced self-interaction behavior. These domain swapped IgG4 S228P molecules also showed reduced viscosity from experiment and coarse-grained simulations. We also observed that experimental diffusion interaction parameter (kD) values have a high correlation with computational diffusivity prediction for both IgG1 and IgG4 S228P isotypes.Abbreviations: AHc, constant region Hamaker constant; AHv, variable region Hamaker constant; CDRs, Complementarity-determining regions; CG, Coarse-grained model; CH1, Constant heavy chain 1; CH2 Constant heavy chain 2; CH3 Constant heavy chain 3; chgCH3 Effective charge on the CH3 region; CL Constant light chain; cP, Centipoise; DLS, Dynamic light scattering; Fab, Fragment antigen-binding; Fc, Fragment crystallizable; Fv, Variable domaing; (r) Radial distribution function; H1 CDR1 of Heavy Chain; H2 CDR2 of Heavy Chain; H3 CDR3 of Heavy Chain; HVI, High viscosity index; IgG1 human immunoglobulin of IgG1 subclass; IgG4 human immunoglobulin of IgG4 subclass; kD, Diffusion interaction parameter; L1 CDR1 of Light Chain; L2 CDR2 of Light Chain; L3 CDR3 of Light Chain; mAb, Monoclonal antibody; MD, Molecular dynamics; PPI Protein-protein interactions; SCM, Spatial charge map; UP-SEC, Ultra-high-performance size-exclusion chromatography; VH, Variable domain of Heavy Chain; VL, Variable domain of Light Chain.

Entities:  

Keywords:  IgG1; IgG4 S228P; IgG4P; Monoclonal antibody self-interaction; computational models; developability; diffusion interaction parameter; monoclonal antibody viscosity

Mesh:

Substances:

Year:  2021        PMID: 34747330      PMCID: PMC8583000          DOI: 10.1080/19420862.2021.1991256

Source DB:  PubMed          Journal:  MAbs        ISSN: 1942-0862            Impact factor:   5.857


  46 in total

1.  Relative stabilities of IgG1 and IgG4 Fab domains: influence of the light-heavy interchain disulfide bond architecture.

Authors:  James T Heads; Ralph Adams; Lena E D'Hooghe; Matt J T Page; David P Humphreys; Andrew G Popplewell; Alastair D Lawson; Alistair J Henry
Journal:  Protein Sci       Date:  2012-08-09       Impact factor: 6.725

Review 2.  Molecular basis of high viscosity in concentrated antibody solutions: Strategies for high concentration drug product development.

Authors:  Dheeraj S Tomar; Sandeep Kumar; Satish K Singh; Sumit Goswami; Li Li
Journal:  MAbs       Date:  2016-01-06       Impact factor: 5.857

3.  Mechanism of immunoglobulin G4 Fab-arm exchange.

Authors:  Theo Rispens; Pleuni Ooijevaar-de Heer; Onno Bende; Rob C Aalberse
Journal:  J Am Chem Soc       Date:  2011-06-15       Impact factor: 15.419

4.  How Well Do Low- and High-Concentration Protein Interactions Predict Solution Viscosities of Monoclonal Antibodies?

Authors:  Mahlet A Woldeyes; Wei Qi; Vladimir I Razinkov; Eric M Furst; Christopher J Roberts
Journal:  J Pharm Sci       Date:  2018-07-12       Impact factor: 3.534

5.  The S228P mutation prevents in vivo and in vitro IgG4 Fab-arm exchange as demonstrated using a combination of novel quantitative immunoassays and physiological matrix preparation.

Authors:  John-Paul Silva; Olivia Vetterlein; Joby Jose; Shirley Peters; Hishani Kirby
Journal:  J Biol Chem       Date:  2015-01-07       Impact factor: 5.157

6.  Concentration dependent viscosity of monoclonal antibody solutions: explaining experimental behavior in terms of molecular properties.

Authors:  Li Li; Sandeep Kumar; Patrick M Buck; Christopher Burns; Janelle Lavoie; Satish K Singh; Nicholas W Warne; Pilarin Nichols; Nicholas Luksha; Davin Boardman
Journal:  Pharm Res       Date:  2014-06-07       Impact factor: 4.200

7.  Structure and Relaxation in Solutions of Monoclonal Antibodies.

Authors:  Gang Wang; Zsigmond Varga; Jennifer Hofmann; Isidro E Zarraga; James W Swan
Journal:  J Phys Chem B       Date:  2018-03-08       Impact factor: 2.991

8.  Multiscale Coarse-Grained Approach to Investigate Self-Association of Antibodies.

Authors:  Saeed Izadi; Thomas W Patapoff; Benjamin T Walters
Journal:  Biophys J       Date:  2020-04-29       Impact factor: 4.033

9.  A single amino acid substitution abolishes the heterogeneity of chimeric mouse/human (IgG4) antibody.

Authors:  S Angal; D J King; M W Bodmer; A Turner; A D Lawson; G Roberts; B Pedley; J R Adair
Journal:  Mol Immunol       Date:  1993-01       Impact factor: 4.407

10.  Structural determinants of unique properties of human IgG4-Fc.

Authors:  Anna M Davies; Theo Rispens; Pleuni Ooijevaar-de Heer; Hannah J Gould; Roy Jefferis; Rob C Aalberse; Brian J Sutton
Journal:  J Mol Biol       Date:  2013-11-06       Impact factor: 5.469

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  2 in total

1.  DeepSCM: An efficient convolutional neural network surrogate model for the screening of therapeutic antibody viscosity.

Authors:  Pin-Kuang Lai
Journal:  Comput Struct Biotechnol J       Date:  2022-04-29       Impact factor: 6.155

2.  Understanding the Stabilizing Effect of Histidine on mAb Aggregation: A Molecular Dynamics Study.

Authors:  Suman Saurabh; Cavan Kalonia; Zongyi Li; Peter Hollowell; Thomas Waigh; Peixun Li; John Webster; John M Seddon; Jian R Lu; Fernando Bresme
Journal:  Mol Pharm       Date:  2022-08-10       Impact factor: 5.364

  2 in total

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