Surface Plasmon Resonance for Therapeutic Antibody Characterization

Davidoff, Sherry N.; Ditto, Noah T; Brooks, Amanda E.; Eckman, Josh; Brooks, Benjamin D.

doi:10.1007/978-1-4939-2617-6_3

Cited by 11 publications

(11 citation statements)

References 153 publications

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“…The flow cytometry-based epitope binning assay using competitive binding profiles described herein can be useful in early antibody discovery, especially when discriminating functional assays that are not robust enough to screen large antibody panels. Due to the correlation of an antibody's function and its epitope, 5,6 it can be useful to cluster antibodies by epitope bins and then advance diverse subsets to functional assays. Utility of this binning assay can also be applied to therapeutic modalities, such as ADC or BiTE molecules where a functional epitope is not critical but breadth of epitope diversity is.…”

Section: Discussionmentioning

confidence: 99%

“…These techniques can be used to profile a panel of antibodies and effectively classify or “bin” the samples relative to each other on epitope diversity and similarities. Antibodies that bind to similar target epitopes often share similar function; 5,6 hence, identifying epitope bins with functional activity can provide several sequence-diverse lead candidates to choose from. A panel of antigen-specific antibodies may also contain more than one functional epitope bin.…”

Section: Introductionmentioning

confidence: 99%

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Flow Cytometry-Based Epitope Binning Using Competitive Binding Profiles for the Characterization of Monoclonal Antibodies against Cellular and Soluble Protein Targets

et al. 2018

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A key step in the therapeutic antibody drug discovery process is early identification of diverse candidate molecules. Information comparing antibody binding epitopes can be used to classify antibodies within a large panel, guiding rational lead molecule selection. We describe a novel epitope binning method utilizing high-throughput flow cytometry (HTFC) that leverages cellular barcoding or spectrally distinct beads to multiplex samples to characterize antibodies raised against cell membrane receptor or soluble protein targets. With no requirement for sample purification or direct labeling, the method is suited for early characterization of antibody candidates. This method generates competitive binding profiles of each antibody against a defined set of known or unknown reference antibodies for binding to epitopes of an antigen. Antibodies with closely related competitive binding profiles indicate similar epitopes and are classified in the same bin. These large, high-throughput, multiplexed experiments can yield epitope bins or clusters for the entire antibody panel, from which a conceptual map of the epitope space for each antibody can be created. Combining this valuable epitope information with other data, such as functional activity, sequence, and selectivity of binding to orthologs and paralogs, enables us to advance the best epitope-diverse candidates for further development.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Flow Cytometry-Based Epitope Binning Using Competitive Binding Profiles for the Characterization of Monoclonal Antibodies against Cellular and Soluble Protein Targets

et al. 2018

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“…Epitope characterization has made significant progress in recent years as the throughput of biosensors has improved [ 5 , 31 ]. Foremost amongst emerging techniques for high-throughput epitope characterization is epitope binning, as it merges the speed and functional-site identification capabilities demanded by the biopharmaceutical industry [ 3 , 4 , 5 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

Characterizing Epitope Binding Regions of Entire Antibody Panels by Combining Experimental and Computational Analysis of Antibody: Antigen Binding Competition

et al. 2020

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Vaccines and immunotherapies depend on the ability of antibodies to sensitively and specifically recognize particular antigens and specific epitopes on those antigens. As such, detailed characterization of antibody–antigen binding provides important information to guide development. Due to the time and expense required, high-resolution structural characterization techniques are typically used sparingly and late in a development process. Here, we show that antibody–antigen binding can be characterized early in a process for whole panels of antibodies by combining experimental and computational analyses of competition between monoclonal antibodies for binding to an antigen. Experimental “epitope binning” of monoclonal antibodies uses high-throughput surface plasmon resonance to reveal which antibodies compete, while a new complementary computational analysis that we call “dock binning” evaluates antibody–antigen docking models to identify why and where they might compete, in terms of possible binding sites on the antigen. Experimental and computational characterization of the identified antigenic hotspots then enables the refinement of the competitors and their associated epitope binding regions on the antigen. While not performed at atomic resolution, this approach allows for the group-level identification of functionally related monoclonal antibodies (i.e., communities) and identification of their general binding regions on the antigen. By leveraging extensive epitope characterization data that can be readily generated both experimentally and computationally, researchers can gain broad insights into the basis for antibody–antigen recognition in wide-ranging vaccine and immunotherapy discovery and development programs.

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“…To date, a ligand‐binding assay (LBA) is used as the standard method to measure the bDMARDs in biological samples . LBAs include radio immunoassay, enzyme‐linked immunosorbent assay, time‐resolved fluorescence immunoassay, surface plasmon resonance and electrochemiluminescence immunoassay, and these are widely used, from fundamental researches to clinical inspection. However, LBAs have some disadvantages, such as complicated and time‐consuming procedures, influence of the matrix on the assay, and requirement of high affinity antibodies .…”

Section: Introductionmentioning

confidence: 99%

Simple and rapid analysis of tocilizumab using HPLC‐fluorescence detection method

et al. 2019

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We developed a novel assay using high‐performance liquid chromatography (HPLC) with fluorescence detection for the determination of tocilizumab (TCZ), after it has undergone a facile and rapid pretreatment. TCZ belongs to the same subclass as IgG1 (Immunoglobulin G subclass 1), and we could separate TCZ from IgG1 without antigen–antibody reactions, with the novel detection method. The separation of these antibodies was achieved by pretreatment with an organic solvent containing a base, such as trimethylamine and triethylamine. The effect of these bases on the separation of TCZ is related to the hydrophobicity of the base rather than the electrostatic charge. The results indicated that the surface charge of antibodies changed because of the structural change, even though the difference in the amino acid sequences of the antibodies was very low. Our method is available for the separation of the antibody subclasses, and it would be useful to assay TCZ in blood.

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Surface Plasmon Resonance for Therapeutic Antibody Characterization

Cited by 11 publications

References 153 publications

Flow Cytometry-Based Epitope Binning Using Competitive Binding Profiles for the Characterization of Monoclonal Antibodies against Cellular and Soluble Protein Targets

Flow Cytometry-Based Epitope Binning Using Competitive Binding Profiles for the Characterization of Monoclonal Antibodies against Cellular and Soluble Protein Targets

Characterizing Epitope Binding Regions of Entire Antibody Panels by Combining Experimental and Computational Analysis of Antibody: Antigen Binding Competition

Simple and rapid analysis of tocilizumab using HPLC‐fluorescence detection method

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