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Characterizing monoclonal antibody structure by carbodiimide/GEE footprinting.

ABSTRACT: Amino acid-specific covalent labeling is well suited to probe protein structure and macromolecular interactions, especially for macromolecules and their complexes that are difficult to examine by alternative means, due to size, complexity, or instability. Here we present a detailed account of carbodiimide-based covalent labeling (with GEE tagging) applied to a glycosylated monoclonal antibody therapeutic, which represents an important class of biologic drugs. Characterization of such proteins and their antigen complexes is essential to development of new biologic-based medicines. In this study, the experiments were optimized to preserve the structural integrity of the protein, and experimental conditions were varied and replicated to establish the reproducibility and precision of the technique. Homology-based models were generated and used to compare the solvent accessibility of the labeled residues, which include D, E, and the C-terminus, against the experimental surface accessibility data in order to understand the accuracy of the approach in providing an unbiased assessment of structure. Data from the protein were also compared to reactivity measures of several model peptides to explain sequence or structure-based variations in reactivity. The results highlight several advantages of this approach. These include: the ease of use at the bench top, the linearity of the dose response plots at high levels of labeling (indicating that the label does not significantly perturb the structure of the protein), the high reproducibility of replicate experiments (<2 % variation in modification extent), the similar reactivity of the 3 target probe residues (as suggested by analysis of model peptides), and the overall positive and significant correlation of reactivity and solvent accessible surface area (the latter values predicted by the homology modeling). Attenuation of reactivity, in otherwise solvent accessible probes, is documented as arising from the effects of positive charge or bond formation between adjacent amine and carboxyl groups, the latter accompanied by observed water loss. The results are also compared with data from hydroxyl radical-mediated oxidative footprinting on the same protein, showing that complementary information is gained from the 2 approaches, although the number of target residues in carbodiimide/GEE labeling is fewer. Overall, this approach is an accurate and precise method for assessing protein structure of biologic drugs.

SUBMITTER: Kaur P

PROVIDER: S-EPMC4622050 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Characterizing monoclonal antibody structure by carbodiimide/GEE footprinting.

Kaur Parminder P Tomechko Sara S Kiselar Janna J Shi Wuxian W Deperalta Galahad G Wecksler Aaron T AT Gokulrangan Giridharan G Ling Victor V Chance Mark R MR

mAbs 20140101 6

Amino acid-specific covalent labeling is well suited to probe protein structure and macromolecular interactions, especially for macromolecules and their complexes that are difficult to examine by alternative means, due to size, complexity, or instability. Here we present a detailed account of carbodiimide-based covalent labeling (with GEE tagging) applied to a glycosylated monoclonal antibody therapeutic, which represents an important class of biologic drugs. Characterization of such proteins an ...[more]

PMID: 25484052

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Project description:Structural characterization of proteins and their antigen complexes is essential to the development of new biologic-based medicines. Amino acid-specific covalent labeling (CL) is well suited to probe such structures, especially for cases that are difficult to examine by alternative means due to size, complexity, or instability. We present here a detailed account of carboxyl group labeling (with glycine ethyl ester (GEE) tagging) applied to a glycosylated monoclonal antibody therapeutic (mAb). The experiments were optimized to preserve the structural integrity of the mAb, and experimental conditions were varied and replicated to establish the reproducibility of the technique. Homology-based models were generated and used to compare the solvent accessibility of the labeled residues, which include aspartic acid (D), glutamic acid (E), and the C-terminus (i.e., the target probes), with the experimental data in order to understand the accuracy of the approach. Data from the mAb were compared to reactivity measures of several model peptides to explain observed variations in reactivity. Attenuation of reactivity in otherwise solvent accessible probes is documented as arising from the effects of positive charge or bond formation between adjacent amine and carboxyl groups, the latter accompanied by observed water loss. A comparison of results with previously published data by Deperalta et al using hydroxyl radical footprinting showed that 55% (32/58) of target residues were GEE labeled in this study whereas the previous study reported 21% of the targets were labeled. Although the number of target residues in GEE labeling is fewer, the two approaches provide complementary information. The results highlight advantages of this approach, such as the ease of use at the bench top, the linearity of the dose response plots at high levels of labeling, reproducibility of replicate experiments (<2% variation in modification extent), the similar reactivity of the three target probes, and significant correlation of reactivity and solvent accessible surface area.

Project description:BackgroundIn the era of personalized cancer medicine, identifying techniques for effectively matching patients to efficacious treatments is a critical step in the treatment process. The advent of anti-cancer immunotherapies necessitates novel approaches to biomarker identification beyond traditional genomic profiling. One promising approach is incorporation of nomograms into treatment decisions. Nomograms are prediction tools, based on statistical modeling, designed to predict treatment outcomes. As a first step toward developing a nomogram, we conducted analyses to predict CD137 expression of natural killer cells after monoclonal antibody (mAb) treatment.Patients and methodsPatient, tumor and immune characteristics were collected from 199 patients with breast cancer (N?=?62), head/neck cancers (N?=?46) and non-Hodgkin's lymphoma (NHL) (N?=?91), who were receiving mAb therapy as part of clinical trials. The difference in CD137 expression before and after mAb therapy was assessed by flow cytometry. To evaluate those who respond to mAb therapy via increased CD137 expression, we applied classification and regression trees (CART), multivariable lasso regression tools and Random Forest.ResultsThe CD137 expression was significantly different for each cancer type [mean (SD): Breast: 6.6 (6.5); Head/Neck: 11.0 (7.0); NHL: 7.5 (7.1), P?<?0.0001]. For breast cancer and NHL, FcR polymorphism and baseline CD137 expression were significant predictors of increased CD137 expression; for head/neck cancer, FcR polymorphism and age were significant predictors of increased expression.ConclusionsOur preliminary results suggest that FcR polymorphism, pre-treatment CD137 expression and age are significant predictors of CD137 upregulation in patients. This study demonstrates that the development of a nomogram for therapy response is feasible. Further work validating our models in an independent cohort will provide the next steps in developing a nomogram that may be used to individualize this therapeutic approach for patients (NCT01114256).

Project description:We have developed a monoclonal antibody (mAb) C7 that reacts with Als3p and enolase present in Candida albicans cell wall and exerts three anti-Candida activities: candidacidal activity and inhibition of both adhesion and filamentation. To investigate the mode of action of mAb C7 on fungal viability, we examined changes in the genome-wide gene expression profile of C. albicans grown in presence of a subinhibitory concentration of mAb C7 (12.5 µg/ml) by using microarrays. A total of 49 genes were found to be differentially expressed upon treatment with mAb C7. Of these, 28 were found to be up-regulated and 21 down-regulated. The categories of up-regulated genes with the largest number of variations were those involved in iron uptake or related to iron homeostasis (42.86%), while the energy-related group accounted for 38.10% of the down-regulated genes (8/21). Results were validated by real Time PCR. Since these effects resembled those found under iron-limited conditions, the activity of mAb C7 on C. albicans mutants with deletions in key genes implicated in the three iron acquisition systems described in this yeast was also assessed. Only mutants lacking TPK1 and TPK2 genes were less sensitive to the candidacidal effect of mAb C7. FeCl3 or hemin at concentrations ≥ 7.8µM reversed the candidacidal effect of mAb C7 on C. albicans, on a concentration dependent manner. The results presented in this study provide evidence that the candidacidal effect of mAb C7 is related to the blockage of the reductive iron uptake pathway of C. albicans. A saturated culture of C. albicans grown overnight was diluted to an optical density at 600 nm of approximately 0.1 and divided in two aliquots. One of them was used untreated as control and the second one was treated with a subinhibitory concentration (12.5 µg/ml) of monoclonal antibody C7 . Both cultures were incubated for 18 h at 37ºC before harvesting cells. Antibody added and control samples were obtained each time. The experiment was repeated once. Dye-swap technique was used for hybridization and four arrays were analyzed to compare the expresion of over six thousands genes in response to antibody C7.

Dataset Information

Characterizing monoclonal antibody structure by carbodiimide/GEE footprinting.

Publications

Characterizing monoclonal antibody structure by carbodiimide/GEE footprinting.

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