Automated Intact Mass Analysis for the Characterization of Antibodies

March 20, 2019

Presented at CASSS-AT Europe 2019, Dublin, Ireland

Selecting the best possible drug candidate requires extensive molecular characterization to mitigate the risk of failing in late stages of drug development. Here we present an innovative and unique deconvolution method to leverage intact mass analysis for automated screening and in-depth characterization of antibodies. 

An IgG-type antibody preparation was treated with the protease IdeS, which cleaves IgG molecules in the hinge region with a high degree of specificity. This treatment and the subsequent reduction of interchain disulfide bonds reduced the size of the ~150 kDa antibody to fragments of ~25 kDa. MS raw data was processed and analyzed using Genedata Expressionist® (Genedata AG, Basel, Switzerland).

Two intact mass analysis deconvolution strategies were applied to the identification and quantification of IgG-type antibody fragments and their modifications.  First, in a conventional approach, deconvolution was performed on LC-MS spectra averaged over a defined elution time range. Inspection of the UV chromatogram of the Fd' fragment’s LC elution profile indicated the presence of eight peaks; therefore, deconvolution was applied over the corresponding eight manually-selected time ranges. This approach was found to have several drawbacks, including inaccurate quantification due to overlapping peaks, a loss of inter-peak relationships, and being extremely time-consuming. In addition—because selection of time-ranges is a manual process—this approach may introduce significant bias to the analysis. To address these issues, we developed an automated two-dimensional time-resolved deconvolution algorithm that allows identification and accurate quantification of even trace amounts of large molecules in a single plot. For example, automated deconvolution of the LC-MS spectrum over the Fd' fragment’s elution range using this algorithm enabled identification and accurate relative quantification of all major and multiple low-abundance species. This approach can be applied to efficiently characterize complex mixtures of proteins that are only partially resolved using chromatographic methods.

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