Dissecting the Dissociation Patterns of Fucosylated Glycopeptides Undergoing CID: A Case Study in Improving Automated Glycopeptide Analysis Scoring Algorithms.

The need to investigate the fragmentation of fucosylated glycopeptides is driven by recent work showing that at least one, and perhaps many, glycopeptide analysis scoring algorithms are less effective at identifying fucosylated glycopeptides than non-fucosylated glycopeptides. Herein, we study the CID fragmentation characteristics of fucosylated glycopeptides and the scoring rules of the glycopeptide analysis software, GlycoPep Grader, in an effort to improve automated assignments of these important glycopeptides. We identified some prominent product ions from a common fragmentation pathway of fucosylated glycopeptides that were not accounted for in the scoring rules. Based on this finding, we propose new scoring rules for fucosylated glycopeptides that can be incorporated into GlycoPep Grader and other similar analysis software tools to more accurately identify these species. The approach used here, to improve one particular scoring algorithm, could henceforth be used to improve any other algorithm that assigns glycopeptides based on their MS/MS data.

Recent mass spectrometry-based techniques and considerations for disulfide bond characterization in proteins.

Disulfide bonds are important structural moieties of proteins: they ensure proper folding, provide stability, and ensure proper function. With the increasing use of proteins for biotherapeutics, particularly monoclonal antibodies, which are highly disulfide bonded, it is now important to confirm the correct disulfide bond connectivity and to verify the presence, or absence, of disulfide bond variants in the protein therapeutics. These studies help to ensure safety and efficacy. Hence, disulfide bonds are among the critical quality attributes of proteins that have to be monitored closely during the development of biotherapeutics. However, disulfide bond analysis is challenging because of the complexity of the biomolecules. Mass spectrometry (MS) has been the go-to analytical tool for the characterization of such complex biomolecules, and several methods have been reported to meet the challenging task of mapping disulfide bonds in proteins. In this review, we describe the relevant, recent MS-based techniques and provide important considerations needed for efficient disulfide bond analysis in proteins. The review focuses on methods for proper sample preparation, fragmentation techniques for disulfide bond analysis, recent disulfide bond mapping methods based on the fragmentation techniques, and automated algorithms designed for rapid analysis of disulfide bonds from liquid chromatography-MS/MS data. Researchers involved in method development for protein characterization can use the information herein to facilitate development of new MS-based methods for protein disulfide bond analysis. In addition, individuals characterizing biotherapeutics, especially by disulfide bond mapping in antibodies, can use this review to choose the best strategies for disulfide bond assignment of their biologic products. Graphical Abstract This review, describing characterization methods for disulfide bonds in proteins, focuses on three critical components: sample preparation, mass spectrometry data, and software tools.

Rapid LC-MS Based High-Throughput Screening Method, Affording No False Positives or False Negatives, Identifies a New Inhibitor for Carbonic Anhydrase.

Developing effective high-throughput screening (HTS) methods is of paramount importance in the early stage of drug discovery. While rugged and robust assays may be easily developed for certain enzymes, HTS assays designed to identify ligands that block protein binding are much more challenging to develop; attenuating the number of false positives and false negatives under high-throughput screening conditions is particularly difficult. We describe an MS-based HTS workflow that addresses these challenges. The assay mitigates false positives by selectively identifying positive hits exclusively when a ligand at the binding site of interest is displaced; it mitigates false negatives by detecting a reporter compound that ionizes well, not by detecting the ligand binder, which may not ionize. The method was validated by detecting known binders of three proteins, pepsin, maltose binding protein (MBP), and carbonic anhydrase (CA) in the presence of hundreds of non-binders. We also identified a novel CA binder, pifithrin-µ, which could not have been identified by any other MS-based assay because of its poor ionization efficiency. This new method addresses many of the challenges that are currently encountered during high-throughput screening.

Two New Tools for Glycopeptide Analysis Researchers: A Glycopeptide Decoy Generator and a Large Data Set of Assigned CID Spectra of Glycopeptides.

The glycopeptide analysis field is tightly constrained by a lack of effective tools that translate mass spectrometry data into meaningful chemical information, and perhaps the most challenging aspect of building effective glycopeptide analysis software is designing an accurate scoring algorithm for MS/MS data. We provide the glycoproteomics community with two tools to address this challenge. The first tool, a curated set of 100 expert-assigned CID spectra of glycopeptides, contains a diverse set of spectra from a variety of glycan types; the second tool, Glycopeptide Decoy Generator, is a new software application that generates glycopeptide decoys de novo. We developed these tools so that emerging methods of assigning glycopeptides' CID spectra could be rigorously tested. Software developers or those interested in developing skills in expert (manual) analysis can use these tools to facilitate their work. We demonstrate the tools' utility in assessing the quality of one particular glycopeptide software package, GlycoPep Grader, which assigns glycopeptides to CID spectra. We first acquired the set of 100 expert assigned CID spectra; then, we used the Decoy Generator (described herein) to generate 20 decoys per target glycopeptide. The assigned spectra and decoys were used to test the accuracy of GlycoPep Grader's scoring algorithm; new strengths and weaknesses were identified in the algorithm using this approach. Both newly developed tools are freely available. The software can be downloaded at http://glycopro.chem.ku.edu/GPJ.jar.

State-of-the-art technologies for rapid and high-throughput sample preparation and analysis of N-glycans from antibodies.

Glycosylation is a PTM that occurs during production of many protein-based biologic drugs and can have a profound impact on their biological, clinical, and pharmacological properties. Quality by design, process optimization, and advance in manufacturing technology create a demand for robust, sensitive, and accurate profiling and quantification of antibody glycosylation. Potential drawbacks in antibody glycosylation profiling include the high hands-on time required for sample preparation and several hours for data acquisition and analysis. Rapid and high-throughput (HTP) N-glycan profiling and characterization along with automation for sample preparation and analysis are essential for extensive antibody glycosylation analysis due to the substantial improvement of turnaround time. The first part of this review article will focus on the recent progress in rapid and HTP sample preparation and analysis of antibody glycosylation. Subsequently, the article will cover a brief overview of various separation and mass spectrometric methods for the rapid and HTP analysis of N-glycans in antibodies. Finally, we will discuss the recent developments in process analytical technologies for the screening and quantification of N-glycans in antibodies.

An Integrated Solution-Based Rapid Sample Preparation Procedure for the Analysis of N-Glycans From Therapeutic Monoclonal Antibodies.

Consistent glycosylation in therapeutic monoclonal antibodies is a major concern in the biopharmaceutical industry as it impacts the drug's safety and efficacy and manufacturing processes. Large numbers of samples are created for the analysis of glycans during various stages of recombinant proteins drug development. Profiling and quantifying protein N-glycosylation is important but extremely challenging due to its microheterogeneity and more importantly the limitations of existing time-consuming sample preparation methods. Thus, a quantitative method with fast sample preparation is crucial for understanding, controlling, and modifying the glycoform variance in therapeutic monoclonal antibody development. Presented here is a rapid and highly quantitative method for the analysis of N-glycans from monoclonal antibodies. The method comprises a simple and fast solution-based sample preparation method that uses nontoxic reducing reagents for direct labeling of N-glycans. The complete work flow for the preparation of fluorescently labeled N-glycans takes a total of 3 h with less than 30 min needed for the release of N-glycans from monoclonal antibody samples.

Disulfide Bond Characterization of Endogenous IgG3 Monoclonal Antibodies Using LC-MS: An Investigation of IgG3 Disulfide-mediated Isoforms.

The use of monoclonal antibodies (mAbs) for the manufacture of innovator and biosimilar biotherapeutics has increased tremendously in recent years. From a structural perspective, mAbs have high disulfide bond content, and the correct disulfide connectivity is required for proper folding and to maintain their biological activity. Therefore, disulfide linkage mapping is an important component of mAB characterization for ensuring drug safety and efficacy. The native disulfide linkage patterns of all four subclasses of IgG antibodies have been well established since the late 1960s. Among these IgG subtypes, disulfide mediated isoforms have been identified for IgG2 and IgG4, and to a lesser extent in IgG1, which is the most studied IgG subclass. However, no studies have been carried out so far to investigate whether different IgG3 isoforms exist due to alternative disulfide connectivity. In an effort to investigate the presence of disulfide-mediated isoforms in IgG3, we employed a bottom-up mass spectrometry approach to accurately determine the disulfide bond linkages in endogenous human IgG3 monoclonal antibody and our results show that no such alternative disulfide bonds exist. While many antibody-based drugs are developed around IgG1, IgG3 represents a new, and in some cases, more desirable drug candidate. Our data represent the first demonstration that alternative disulfide bond arrangements are not present in endogenous IgG3; and therefore, they should not be present in recombinant forms used as antibody-based therapeutics.