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.

In this paper, the electrochemical behaviors of a single gold nanoparticle attached on a nanometer sized electrode have been studied. The single nanoparticle was characterized by using electrochemical methods. Since there is only one nanoparticle on the electrode, unarguable information for that sized particle could be obtained. Our preliminary results show that it becomes more difficult to oxidize gold nanoparticle or reduce gold nanoparticle oxide as the radius of the particle becomes smaller. Also, the peak potential of the reduction of gold nanoparticle oxide is proportional to the reciprocal of the radius of the particle. Theoretical and experimental evidence shows that the physical properties of metal nanoparticles differ from those of bulk metal, and these properties depend on particles size [1][2][3][4][5][6][7][8]. Due to the fact that the size of metal nanoparticles with a diameter in the range of 1-10 nm is between a free diffusion molecule and a bulk metal, the study of such nanoparticles is especially interesting [4]. Electrochemistry has been used to study metal nanoparticles long time ago [1]. Electrochemical studies of metalnanoparticles are mainly focused on electrochemical sensing, electrocatalysis [5,7], single electron charging [2] etc.[4] Both theoretically and experimentally important results have been obtained from these studies. Electrochemical stability of nanoparticles is one of its fundamental aspects. From electrochemical point of view, an electrochemically stable metal nanoparticle means that the oxidation potential of the metal particle is more positive than its bulk metal or the reduction potential of the particle is more negative than its bulk materials if the particle is a metal oxide. However, contradictory conclusions on the electrochemical stability of nanoparticles could be found from previous electrochemical studies. For example, results from several groups show that the electrochemical stability of nanoparticles is increased when the size of the nanoparticles is decreased [3,4]. However, opposite conclusion can also be found [1,8,9].

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.

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.

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.