Hydrogen deuterium exchange mass spectrometry in biopharmaceutical discovery and development – A review

Analytica Chimica Acta 940 (2016) 8e20

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Review

Hydrogen deuterium exchange mass spectrometry in biopharmaceutical discovery and development e A review Bin Deng a, b, Cristina Lento a, b, Derek J. Wilson a, b, * a b

Chemistry Department, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada The Centre for Research in Mass Spectrometry, York University, Toronto, ON, M3J1P3, Canada

h i g h l i g h t s

g r a p h i c a l a b s t r a c t


The pharmaceuticals industry is increasingly shifting to protein therapeutics.
Hydrogen deuterium exchange mass spectrometry is uniquely well suited to support biopharmaceutical development.
Applications for hydrogen deuterium exchange span drug discovery, development and manufacturing.
Future developments will allow improved sensitivity, structural resolution and a broader range of dynamics to be monitored.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 20 May 2016 Received in revised form 25 July 2016 Accepted 7 August 2016 Available online 9 August 2016

Protein therapeutics have emerged as a major class of biopharmaceuticals over the past several decades, a trend that has motivated the advancement of bioanalytical technologies for protein therapeutic characterization. Hydrogen deuterium exchange mass spectrometry (HDX-MS) is a powerful and sensitive technique that can probe the higher order structure of proteins and has been used in the assessment and development of monoclonal antibodies (mAbs), antibody-drug conjugates (ADCs) and biosimilar antibodies. It has also been used to quantify protein-ligand, protein-receptor and other protein-protein interactions involved in signaling pathways. In manufacturing and development, HDXMS can validate storage formulations and manufacturing processes for various biotherapeutics. Currently, HDX-MS is being refined to provide additional coverage, sensitivity and structural specificity and implemented on the millisecond timescale to reveal residual structure and dynamics in disordered domains and intrinsically disordered proteins. © 2016 Elsevier B.V. All rights reserved.

Keywords: Hydrogen deuterium exchange Mass spectrometry Drug discovery and development Protein therapeutics Biosimilar Biopharmaceutical industry

Contents 1.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.1. Pharmaceutical industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

* Corresponding author. Present address: Department of Chemistry, York University, 4700 Keele Street, Toronto, Ontario, M3J 1P3, Canada. E-mail addresses: [email protected] (B. Deng), [email protected] (C. Lento), [email protected] (D.J. Wilson). http://dx.doi.org/10.1016/j.aca.2016.08.006 0003-2670/© 2016 Elsevier B.V. All rights reserved.

B. Deng et al. / Analytica Chimica Acta 940 (2016) 8e20

2.

3.

4. 5. 6.

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1.2. 1.3. Drug 2.1.

HDX-MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Applications of HDX-MS for pharmaceuticals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Protein structure-function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.1.1. Target mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.1.2. Protein therapeutics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.1.3. Antibody-drug conjugates (ADCs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2. Protein-ligand interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3. Protein-protein interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Drug development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.1. Biosimilar antibodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.2. Structural modification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.3. Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.4. Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Emerging techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4.1. Time-resolved HDX-MS (TRHDX-MS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Challenges and future direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

1. Introduction 1.1. Pharmaceutical industry By 2015, worldwide pharmaceutical sales reached a milestone of $1 trillion with a minimum growth rate of 3% within the preceding decade (Fig. 1) [1]. At the same time, the cost of bringing a typical new drug to market is increasingly high, currently in the range of $1.3 billion over an average development period of 12e15 years [2]. This cost also incorporates a relatively high rate of failure that has been a long-term feature of the drug approval process. The rate of approval for new drugs has been at a relatively stable average of 15%e25% for decades [3]. The global pharmaceutical industry is also seeing a rapid growth in applications (and approvals) for biological macromolecules, such as monoclonal antibodies (mAbs) [4,5]. In contrast to small molecules, protein higher order structure and conformational dynamics are intimately linked to their efficacy as therapeutic agents [6,7]. The rise of protein therapeutics therefore brings about unique challenges that motivate the development of new analytical tools capable of characterizing protein structure, dynamics, and interactions in the context of a robust drug discovery

and development environment [8]. For instance, X-ray crystallography [9] and nuclear magnetic resonance (NMR) spectroscopy [10] provide high-resolution measurements of protein structure. However, some limitations to X-ray crystallography include extensive optimization of crystallization conditions, and ultimately a ‘static’ (albeit high resolution) structure of the protein. On the other hand, NMR can provide dynamic data in the solution phase but suffers from sensitivity issues and inherent analyte size limitations well below that of a typical antibody. While surface plasmon resonance (SPR) [11] and bio-layer interferometry (BLI) [12] allows sensitive detection of structural changes and binding kinetics of protein interactions, they can only provide a ‘global’ structural picture, without detailed and localized information. 1.2. HDX-MS Among the many different separation-based or spectroscopybased strategies [13], hydrogen-deuterium exchange mass spectrometry (HDX-MS) is one of the most robust and promising analytical methods for the study of protein conformation and dynamics [14e16]. The use of HDX as a ‘gentle’ structure-dependent

Fig. 1. Global Pharmaceutical Sales, 2002e2014, from 2015 CMR International Pharmaceutical R&D Factbook [1]. Bars represent annual total sales, filled gray circles represent the annual change in sales. Reproduced with permission from Thomson Reuters© 2015.

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labeling technique combined with the sensitivity of MS detection offers considerable analytical power. Particular advantages include small sample consumption (mg), no protein size limitation, bypassing the optimization required to obtain crystals for X-ray studies [13,14], and in some cases near-amino acid resolution [17]. In a typical HDX-MS experiment, protein samples are labeled with deuterium at different time points, with or without binding partners. The exchange is quenched by lowering the pH to 2.5 and the deuterated samples are kept at 0  C to limit back-exchange. After protease digestion, peptides are separated by HPLC/UPLC, and detected by MS. Since deuterium is heavier than hydrogen, the exchange of protein amide, hydroxyl, or thiol hydrogens with a deuterium from solvent generates a mass shift that can be detected by MS (Fig. 2) [18], although due to rapid back-exchange of sidechain and N-terminal hydrogens during the quench step, only backbone amide hydrogen exchange is typically used for analysis. By comparison of HDX-MS data before and after the reaction, peptide regions with different HDX profiles can highlight potential interaction surfaces in protein-small molecule interactions or protein-protein interactions. Peptide backbone amides exhibit exchange relaxation times ranging from ms to hours at physiological pH, depending on the extent to which they are involved in hydrogen bonding (i.e., for maintaining secondary structure in proteins) or sequestered from the solvent. Exchange at these sites is therefore an ideal probe for protein structure and dynamics. The overall exchange mechanism can be described by Eq. (1) [15]: kop

kop

ƒ! ƒ! N  Hclosed ƒƒƒƒƒ ƒƒƒƒƒ ƒ N  Hopen ƒƒƒƒƒ! N  Dopen ƒƒƒƒƒ ƒƒƒƒƒ ƒN kcl

kch

D2 O

kcl

 Dclosed (1)

where kop is the rate constant for ‘opening’ of the amide to exchange, kcl is the rate constant for ‘closing’ of the amide to exchange and kch is the ‘chemical’ exchange rate constant for the amide, corresponding to the primary sequence-dependent rate of exchange in the absence of structure or sequestration [19]. The observed exchange rate kex can be described as Eq. (2) [13e16]: kex ¼ (kopkch)/(kcl þ kch).

(2)

When kch [ kcl, kex ¼ kop,

(3)

HDX goes to completion with each opening event of the protein, which is described as EX1 kinetics. In MS-based analysis, EX1 exchange is characterized by the simultaneous appearance of two populations with different deuterium uptakes, corresponding to a protein population that has undergone the EX1 conformational transition and a population that has not. When kch ≪ kcl, kex ¼ kch(kop/kcl) ¼ kchKop,

(4)

brief conformational ‘opening’ events provide a probability of exchange, which is described as EX2 kinetics. In this scenario, the exchange process is measured by MS as a gradual shift of a single peak (or isotopic distribution) to the heavier masses. Under native conditions, EX2 is much more prevalent than EX1 exchange, however it should be noted that there is a significant EX2/EX1 ‘overlap’ regime in which a more complex framework is required to correctly interpret the data [20]. EX2 exchange is more informative than pure EX1, since the observed rate of exchange kex is linked to the ‘open/closed’ equilibrium which can be interpreted as a semiquantitative measure of local structural stability.

Fig. 2. Basic principle and methodology of HDX-MS. Reproduced from Ref. [18] with permission of Springer© 2015.

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1.3. Applications of HDX-MS for pharmaceuticals Over the past two decades, the HDX-MS technique has rapidly evolved with advances in HDX methodology and MS instrumentation. The use of HDX-MS in academia has been growing rapidly since the 1990s (Fig. 3), with initial adoption by the pharmaceuticals industry following in the early 2000's with a number of important industrial academic collaborations [21] and the release of Waters' commercial HDX-MS system. A search using the Thomson Web of Science engine indicates that 1120 HDX-MS related articles have been published in the period from January 2010 to April 2016. Academia is the largest sector contributing to published HDX-MS applications, along with research from government laboratories and industry, although it is difficult to gauge the latter category, since a substantial fraction of industrial research goes unreported [22]. The main application fields of HDX-MS include protein structure [13e15,21], interactions [16,21], and biopharmaceuticals [14,22,23]. In this review, we examine publications across academia and industry and summarize existing and future applications of HDXMS in the biopharmaceutical industry (Fig. 4) in two main parts: I. Drug discovery including protein structure-function study, protein-ligand interactions, and protein-protein interactions; II. Drug development including product and process development, in the following categories: biosimilar antibodies, structural modification, formulation, and manufacturing. 2. Drug discovery 2.1. Protein structure-function 2.1.1. Target mining The human genome is estimated to contain about 8000 targets of pharmacological interest, with ~400 current effect-mediating drug targets [24]. The majority of these targets correspond to receptors and enzymes [25]. Therefore, it is essential to obtain indepth knowledge of the higher order structure and conformational dynamics of these protein targets for drug discovery. In this respect, HDX-MS has proved to be a very useful tool for probing protein targets [26].

Fig. 4. HDX-MS applications in the stages of drug discovery and development. Adapted from a presentation at 2015 American Association of Pharmaceutical Scientists (AAPS) Annual Meeting and Exposition, with permission from AAPS© 2015.

For example, G protein-coupled receptors (GPCRs) comprise the largest family of protein targets that account for almost 40% of all prescription pharmaceuticals currently on the market [27]. Therefore, GPCRs are of great interest in drug discovery. However, GPCRs are membrane proteins which bring challenges such as insolubility, instability, and in the case of HDX studies, low sequence coverage. The Griffin group presented the methodology of HDX-MS to analyze b2 adrenergic receptor (b2AR) as a GPCR by using carazolol as a stabilizing ligand [28]. With optimization of detergent, reductant, LC and MS settings, the sequence coverage including dynamic regions was significantly improved. A number of dynamic regions of b2AR were observed in relatively small extra- or intracellular loops. Duc et al. further improved the sequence coverage by replacing detergents with bicelles in HDX-MS analysis of GPCRs [29]. Similarly, the conformal changes of GPCRs upon binding to different interacting molecules have been determined using HDX-MS [30e33]. These studies demonstrate the advantages of HDX-MS in studying highly dynamic regions of membrane protein targets, which are unresolved in crystal structures but are likely important for ligand recognition and receptor signaling. Comparison of different ligands such as agonists, antagonists, and inverse agonists by differential HDX-MS analysis of dynamic changes can also reveal different functional states of GPCRs. The knowledge of structure and regulation of kinases is essential for many disease-related signaling pathways. HDX-MS has revealed important dynamic properties of protein kinases and provided insight into the mechanisms of drug binding [34]. For instance,

Fig. 3. Number of publications listed from the PubMed search “hydrogen deuterium exchange mass spectrometry” between 1990 and 2015. The full URL of the search date can be accessed at: http://www.ncbi.nlm.nih.gov/pubmed/?term¼hydrogenþdeuteriumþexchangeþmassþspectrometry.

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AMP-activated protein kinase (AMPK) is widely accepted as a critical metabolic regulator and hence is an attractive target for the treatment of metabolic diseases, inflammation, and cancer [35]. AMPK is in part regulated by allosteric binding of small molecules that induce conformational changes. The Griffin group presented a study of the activation of AMPK and its conformational mobility by HDX-MS [35]. HDX-MS results showed that the binding of AMP induces primarily conformational changes in the g subunit with subtle effects on the a and b subunits, localizing the binding domain for this critical interaction. They also found the binding site of a synthetic small molecule activator, as well as the long distance conformational changes (allosteric effects) induced by binding of AMP and the activator. These data provide a potential foundation for the design and discovery of AMPK activators for the treatment of metabolic diseases. Other HDX-MS studies on kinases, such as conformational dynamics of shikimate kinase [36], static structure models and the dynamic equilibrium of the KIT tyrosine kinase [37], and screening a series of noncompetitive inhibitors of the lymphoid tyrosine phosphatase (LYP) [38], provide clear evidence for the usefulness of HDX-MS in target identification and drug discovery. 2.1.2. Protein therapeutics Protein therapeutics are proteins that are used as drugs [39]. It is the major product category after vaccines in the biopharmaceuticals industry. Among protein therapeutics, monoclonal antibodies (mAbs) are the largest and fastest-growing class of drugs with more than 40 mAbs approved by the FDA to date, along with over 300 mAb candidates currently in development [40]. In 2014, mAbs made up half of the top 10 selling drugs worldwide with total sales of $43 billion [41]. Unlike small molecule drugs, it's critically important that protein therapeutics maintain their higher order structure and conformation to ensure efficacy and stability. HDX-MS is uniquely well suited as an analytical tool to investigate conformation and dynamics of protein therapeutics, which in the context of drug development is aimed at linking specific structural features to functional properties of the protein therapeutic [6,7,13,14,42]. Immunoglobulin gamma (IgG) is the most common type of antibody found in human blood and the most commonly used Igtype for protein therapeutics. IgG plays a broad role in the immune response and can be developed against virtually all pathogen types including viruses, bacteria, and fungi. To understand the conformation of a recombinant monoclonal IgG1 antibody, Houde et al. [43] used HDX-UPLC/MS to study both global and local deuterium uptake profiles of the intact mAb. The results showed that IgG1 exists in a single well-defined conformation, with regions that are highly protected from hydrogen exchange, and other regions that are dynamic and flexible. By using HDX-MS, Houde et al. also studied methionine oxidation, fucosylation, and galactosylation on an intact IgG1, and their effects on IgG1 binding to the Fcg RIIIa receptor [44]. The results showed that the extended glycan structures mediate binding with FcgRIIIa by increasing the rigidity of CH2 domain of the IgG1. Zhang et al. [45] applied HDXMS to study three major disulfide isoforms of IgG2, known as IgG2-B, IgG2-A1 and IgG2-A2. By comparing protection factors between amino acid residues, less Fab domain flexibility was found in IgG2-B, while the IgG2-A2 isoform had more flexible Fab domains. This study provided some rationale of the stability and antigen binding potency of different mAbs, as more flexible regions would be more accessible for antigen binding. Non-antibody therapeutic proteins [46], such as fusion proteins, interferon and enzymes used as therapy for cancers, immune disorders, infections, and other diseases, have also been studied by HDX-MS. For example, Houde et al. [47] utilized HDX-MS to study

the conformation and dynamics of the recombinant factor IX e Fc fusion protein (rFIX-Fc) for the treatment of hemophilia B. Results showed that fusing an IgG1 Fc to rFIX dose not significantly alter the higher-order structure of FIX or Fc and Fc functionality. In the first direct application of HDX to an approved drug, Bobst et al. [48] characterized conformational changes in the interferon b-1a (IFNb-1a) upon target binding. HDX-MS data clearly indicated the higher order structure was affected beyond the covalent modification site of IFN-b-1a. Bobst et al. also later analyzed the solution dynamics of the recombinant acid-b-glucocerebrosidase (GCase) for therapy of Type 1 Gaucher's disease [49]. HDX-MS data revealed the conformational stability and flexibility for the enzymatic activity, and changes in dynamics upon forced oxidation of GCase resulted in the reduction of the catalytic activity. 2.1.3. Antibody-drug conjugates (ADCs) Antibody-drug conjugates (ADCs) are one kind of protein therapeutics in which a mAb is conjugated with a drug molecule, usually a potent toxin for use in chemotherapy. ADCs have the potential to reduce system toxicities of the drugs during chemotherapy due to the target specificity of the mAb [50]. It is important to evaluate how the drug conjugation process impacts the conformation and dynamics of the mAb. Pan et al. [51] used HDX-MS to study monomethyl auristatin E or F conjugated with a mAb. The results showed that the ADCs and mAbs share very similar conformation and dynamics in solution, demonstrating that the drug conjugation does not induce large-scale conformational changes on the protein backbone. Pan et al. [52] also mutated the HC Ser239 into Cys239 of a wild-type mAb. The side-by-side HDXMS comparison showed that no significant conformational alternatives were found in the engineered mAb. The mutant Cys239 provides a conjugation site for the drug and the ADC maintains the same structural integrity of the antibody. These studies and others demonstrate the great potential of HDX-MS to broaden the understanding of higher-order structures in ADCs [53,54]. 2.2. Protein-ligand interactions Protein-ligand interactions play a key role in biological processes such as cell signaling and intracellular communication, and the study of these interactions is an integral part of the drug discovery process. Ligands can range from being small organic and inorganic molecules to lipids, nucleic acids, peptides, and proteins [55,56]. Among these ligands, small molecules (<800 Da) continue to compose the majority of drugs currently on the market. Progress in small molecule drug discovery relies heavily on understanding the binding mechanism of the candidate to the target protein and induced structural changes upon binding. Compared to other analytical methods, HDX-MS can provide fast and sensitive detection, which is an essential property for potential high-throughput screening studies. HDX-MS can reveal ligand binding sites and induced conformational changes to provide an understanding of the drug's quantitative structureeactivity relationship (QSAR). The measurement relies simply on binding sites showing a decrease (typically) in the deuterium exchange rate or uptake upon complexation. Therefore, HDX-MS can be very useful to localize protein-ligand interaction sites to aid novel drug design and discovery [18,57]. Recently, Konermann et al. [58] described the complete set of ‘archetypal’ binding interactions through the lens of HDX, including models that would result in net-decreases, net-zero and netincreases in dynamics. This study was the first to provide a thermodynamic rationale for interactions that counterintuitively increase protein dynamics upon complexation and provides a set of model categories through which to understand ligand binding.

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A number of studies have applied HDX to characterize therapeutically relevant protein-small molecule interactions. For example, GNF-2 [59] is a highly selective non-ATP competitive inhibitor of Bcr-Abl, which is a 210-kDa fusion protein with deregulated tyrosine kinase activity in chronic myelogenous leukemia (CML). By using of HDX-MS combined with NMR and X-ray crystallography, Zhang et al. [60] discovered GNF-5 as an analogue of GNF-2, to be a selective allosteric Bcr-Abl inhibitor (IC50 ¼ 0.22 mM), binding to the myristate-binding site of Abl kinase, and leading to dynamic changes in the ATP-binding site. This allosteric effect combined with ATP-competitive inhibitors can overcome resistance to achieve therapeutically relevant inhibition of Bcr-Abl activity for the treatment of CML. Hu et al. [61] used HDX-MS to localize the interaction regions and identify the binding sites between sodium dodecyl sulfate (SDS) and b-Lactoglobulin (BLG). Koshy et al. [62] aimed to understand the mechanism of transmembrane signaling by using HDX-MS. They employed vesicles containing a nickel-chelating lipid to bind a His-tagged chemoreceptor cytoplasmic fragment (CF) and assemble functional complexes with the associated kinases CheA and CheW involved in kinase activation in the signaling pathway. The signaling subdomain exhibits significant protection from hydrogen exchange in complexes when in a kinase-activating state, suggesting a tighter and/or larger interaction interface with CheA and CheW in this state. The Griffin group has also extensively studied the effect of small-molecule interactions on protein targets via HDX-MS. Examples include benzothiophene (BTPa) selectively interacting with estrogen receptor (ERa) [63], ligand-induced activation of nuclear receptor PPARg [64], and agonists interacting with retinoid X receptor (RXR) for anti-cancer drug designs [65]. 2.3. Protein-protein interactions Modulation of protein-protein interactions is at the center of many drug effects, especially for therapeutic antibodies. An antibody, also known as an immunoglobulin (Ig), is a Y-shaped glycoprotein composed of two light chains and two heavy chains, which are connected by disulfide bonds. Its arms and stem are referred to as the fragment antigen binding (Fab) and fragment crystallizable (Fc) regions. Fab is responsible for the recognition and binding of its respective antigen, while Fc is responsible for binding to neonatal Fc receptors (FcRn) regulating antibody levels in plasma. Therefore, antibody-antigen and antibody-receptor are the two main types of protein-protein interactions of antibody drugs. During the antibody-antigen interaction, epitopes are binding regions on an antigen recognized by its respective antibody. Epitope-mapping is the identification of residues or ‘surfaces’ involved in antibody/antigen interactions, which are of intensive interest for scientific, regulatory and intellectual property reasons [66]. There are two types of epitopes: continuous or linear epitopes, and discontinuous or conformational epitopes [67]. At present, HDX-MS is usually combined with other techniques such as X-ray crystallography, site-directed mutagenesis, and computational docking for verification [68e72]. In a typical epitope mapping study by HDX-MS, uptake values are compared between the native antigen and the antigen in the presence of antibody, with the regions of lowered deuterium exchange kinetics identified as potential epitopes [14]. While epitope mapping is perhaps the most common application of HDX in biopharmaceuticals, relatively few reports have been published of this type of work, most likely due to IP barriers. Nonetheless, some important advances in this area have been publically reported. For example, Zhang et al. [67] studied the interaction between food allergy related cashew 11 S globulin

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allergen, Ana o 2, with its two mAbs 2B5 and 1F5, to demonstrate the use of HDX-MS for the epitope mapping of a large antigen protein. Free antigen and antibody-antigen complex were subjected to HDX. The regions protected from HDX upon antibody binding agreed with previous immunological and mutational studies identifying the epitope. These results point towards HDXMS as a sensitive approach for monitoring conformational dynamics in antibody-antigen interaction and complex formation. However, long-range conformational changes or ‘allosteric effects’ caused by the interaction between antibody and antigen are also found in the HDX-MS studies, which can obscure the ‘true’ epitope in some cases [14,66,67]. Computational docking is a useful approach to predict the structures of larger protein-protein complexes from HDX data. This nascent technique is usually used to predict protein-protein or protein-ligand interaction and provides supporting evidences to the HDX-MS results [72]. Pandit et al. [66] combined HDX-MS and computational docking (HDX-DOCK) to study antibody-antigen interactions. The HDX-MS epitopes of cytochrome c with its mAb E8, IL-13 with its mAb CNTO607, and IL-17A with its mAb CAT-2200 interactions were in good agreement with published X-ray cocrystal structures. In this study, non-epitope ‘hits’ in the HDX data from allosteric effects were successfully eliminated during computational docking. The fine quality of the HDX-DOCK measured epitopes was still variable, however, with the approach yielding significantly better epitope results for the cytochrome c e E8 interaction. This study demonstrated that computational docking can be a very powerful tool for epitope mapping predictions when parameterized with HDX-MS data. Other studies using HDX-MS for epitope mapping include Sevy et al. [73] who identified the epitopes between anti-FVIII mAbs and factor VIII to find an improved treatment for hemophilia A. Bereszczak et al. [74] localized changes in HDX rates accompanying the binding between antibodies and the capsid protein (Cp) during the human infection by hepatitis B virus (HBV). Obungu et al. [75] researched human transmembrane protein Fas ligand (FasL) which belongs to the tumor necrosis factor (TNF) protein family. By uncovering the epitope regions, antibody therapy targeted at FasL can be applied for cancer and inflammatory treatments. For antibody-receptor interaction, Jensen et al. [76] provided an excellent example by applying HDX-MS to analyze native human IgG1 and its complex with the human neonatal Fc receptor (FcRn). Using electron transfer dissociation (ETD) as a ‘non-ergodic’ fragmentation method, HDX-MS is able to localize changes in conformation at a single amino acid level. As shown in Fig. 5, several regions protected from deuterium exchange were found in the antibody Fc fragment upon binding with FcRn, which were in good agreement with previous X-ray crystallographic studies. Apart from antibodies, other protein-protein interactions have also studied by HDX-MS for drug discovery. Examples include the HIV-1 accessory protein Nef interacting with Src-family kinase Hck for HIV inhibition [77]. 3. Drug development 3.1. Biosimilar antibodies A biosimilar antibody is an ‘identical’ copy of the original one, and can be manufactured when the original product's patent expires [78]. Biosimilar antibodies are developed to maintain or improve drug efficacy but with much lower research costs leading to more affordable biological treatments for patients. However, proving biosimilarity is much more challenging for protein therapeutics compared to small molecules. This is because slightly

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Fig. 5. HDX-MS showed differential deuterium exchange regions of native human IgG1 upon binding with the human neonatal Fc receptor (FcRn). The HDX plots of heavy-chain (HC) and light-chain (LC) were monitored at 1 min, 1 h, 2.5 h and 5 h. HC peptides 57e79 of IgG1 showed no significant deuterium uptake change before (gray curve) and after interaction (dashed black curve) with FcRn. However, HC peptides 1e18, 167e182, 188e205, 243e260, 315e356, 434e454 and LC peptides 55e71 showed reduced deuterium uptake in the absence (gray curve) and presence (red or orange curves) of FcRn. In the central schematic, colored regions of the homology model of IgG1 indicates the HDX-MS results of no changes (gray) or reduced deuterium uptake (red and orange) upon FcRn binding. Adapted from Ref. [76] with permission of American Society for Biochemistry and Molecular Biology© 2015. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

different manufacturing processes may affect the structure, modifications or dynamics of potential biosimilars in subtle ways that nonetheless have a substantial impact on safety, stability and potency. Therefore, rigorous comparability studies between biosimilars and reference products are essential to establish biopharmaceutical equivalence and maintain manufacturing consistency. Drug approval authorities such as the European Medicines Agency (EMA) and the Food and Drug Administration (FDA) have released guidelines for the regulatory review of biosimilars [79]. As discussed above, HDX-MS has been used as an informative method for higher order structure characterization. In the context of biosimilars, HDX-MS is especially suitable to conduct conformational comparisons of biopharmaceuticals during target-directed drug development [8,14]. One example of this comes from a publically disclosed process to approve a biosimilar for Rituximab (Roche/Genentech) [MabThera™ (EU)/Rituxan™ (USA)], a therapeutic mAb for the treatment of non-Hodgkin's lymphoma and chronic lymphocytic leukemia [79]. The biosimilar (GP2013) was proposed by Sandoz Biopharmaceuticals. To understand the physicochemical and functional comparability between GP2013 and the original product, arrays of orthogonal analytical methods and biological characterization were carried out. The HDX-MS portion of the analysis indicated that, against expectations, GP2013 and the rituximab originator maintained the same conformation even when using different cell lines and manufacturing processes. Ultimately, GP2013 was shown to be highly similar to rituximab at the level of primary and higher order structure, post-translational modifications and biological properties. This demonstrates that biosimilar development of complex molecules such as mAbs is possible.

Currently, GP2013 is ongoing clinical trials and waiting for regulatory filing and approval. 3.2. Structural modification Structural modification of proteins can improve pharmacokinetic behaviors of therapeutic proteins for drug development [80,81]. Modifications of proteins include enzymatic posttransitional modifications (PTMs) by expression system such as glycosylation and phosphorylation, ‘designer’ PTMs such as PEGylation, and non-enzymatic PTMs by stress or storage such as oxidation, deamidation, N-glutamate cyclization, C-lysine truncation, and amide bond hydrolysis, etc. [82]. These modifications can cause possible conformational changes, size heterogeneity and charge variants which may affect drug stability and efficacy. HDXMS has been used to better understand these modifications and their effects on the structure of therapeutic proteins, including measurements of both global and localized changes in protein conformation [82e88]. For example, after deamidation, sialylation, oxidation and Clysine clipping of a recombinant human IgG1 mAb (MAb1), Tang et al. [83] isolated four major charge variants of MAb1 by cation exchange chromatography. Local HDX-MS was then used to evaluate the conformation and solution-phase dynamics of these charge variants by measuring deuterium exchange levels over time at the peptide level. HDX-MS was combined with SUPREX [84] which measures the unfolding profile and stability of the protein as a function of the concentration of chemical denaturants such as GuHCl. The results revealed that all four charge variants of MAb1 did not show a significant difference in conformation, solution

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dynamics or stability. This research provides a convenient methodology for comparability studies of other charge variant antibodies. Zhang et al. [85] employed HDX-MS to examine the conformational changes in mAbs caused by methionine (Met) oxidation, aspartic acid (Asp) isomerization and asparagine (Asn) deamidation. The results showed that Met oxidation was highly dependent on its location and the glycosylation state of the mAb. Meanwhile, Asp isomerization and Asn deamidation had very limited effects on mAb conformation. Yan et al. [86] also studied Met oxidation and Asp isomerization of the complementarity-determining regions (CDRs) in the heavy chain of a mAb1 model. The results indicated that Asp isomerization and Met oxidation in CDR2 resulted in opposing conformational impacts on local regions, leading to different antibody-antigen binding affinities. Other protein therapeutics that undergo multiple processing mechanisms and modifications are also analyzed by HDX by comparison to a reference state. Houde et al. [87] used HDX-MS to compare higher order structures of several different preparations (different batch and culture media) and modifications (oxidized or PEGylated) of interferon-b-1a (IFN). Graphical display of HDX-MS data in the format of a “mirror plot” or “butterfly chart” (Fig. 6a) allows easy visual comparison of spatial and temporal HDX properties for different samples. The plot of the HDX-MS difference data (Fig. 6b) clearly indicated the higher order structural similarity (PEGylated) or difference (oxidized) between experimental IFN and reference IFN. Similarly, PEGylated and non-PEGylated granulocyte colony stimulating factor (G-CSF) was successfully compared using HDX-MS by Wei et al. [88]. These studies highlight the powerful assessment of protein conformation by HDX-MS in biopharmaceutical comparability studies. 3.3. Formulation Therapeutic proteins are vulnerable to various environmental stress factors due to their structural complexity and flexibility. Degradation or aggregation can occur during manufacturing, storage, distribution and even administration [89]. Hence, formulation strategies are needed to improve stability and minimize degradation of these therapeutic proteins for long-term storage. A variety of pharmaceutical excipients such as sugars, polyols, amino acids, salts, and surfactants are commonly added into formulations to improve the conformational and storage stability of protein therapeutics [90]. A better understanding of protein-excipient interactions and their effects on conformational stability and local dynamics may lead to improvements in protein formulation methodologies. Manikwar et al. [91] studied the effects of stabilizing (sucrose) and destabilizing (arginine) excipients on the conformational and storage stability of an IgG1 mAb-B. HDX-MS was performed to identify changes in the local flexibility within mAb-B. Results showed that sucrose increased the mAb's conformational stability and reduced insoluble aggregates. In contrast, arginine decreased the mAb's conformational stability and increased mAb aggregates. Compared to the control buffer, sucrose caused decreases in local flexibility across several domains of mAb-B, while arginine caused an increase in flexibility in the CH2 and VHeCH1 domains and a decrease in flexibility in the VL domain. The increase in local flexibility was associated with conformational destabilization. These results support the hypothesis that decreasing the flexibility of key regions within the CH2 domain results in overall physical stability of the IgG1 mAb-B. This study was the first to demonstrate the utility of HDX-MS for measuring conformational changes induced by stabilizing agents, which allows for rational genetic engineering leading to more stabilized mAbs [92e94]. Similarly, Zhang et al.

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[95] studied the effects of sucrose and benzyl alcohol on recombinant human granulocyte colony stimulating factor (GCSF) conformational dynamics by HDX-MS. Other applications of HDX-MS for stabilization and formulation development of mAbs were reviewed by Volkin et al. [96]. 3.4. Manufacturing Since the conformation of a protein determines its biological activity, manufacturing of commercial protein drugs with consistent higher order structures and therapeutic properties is of central importance in the biopharmaceutical industry. Variation in protein conformation may arise due to different manufacturing processes or between batch productions. HDX-MS can characterize minor changes in higher order structure and dynamics of protein therapeutics, and could be an effective and routine examining method for quality control purposes at all stages of the manufacturing process. Examples were illustrated by Wei et al. [14] to investigate conformational changes of protein therapeutics as a result of changes in the manufacturing process. Comparison studies of mAb samples from three different lots were conducted by HDX-MS. Global HDX studies all showed that there were no significant differences among the three lots of mAb samples. A positive control experiment showed that the treatment of the same mAb with 1.5 M Guanidine-HCl for 1 h displayed different HDX behaviors from the untreated mAb. The treated sample did not undergo a complete unfolding transition under these conditions, but nonetheless exhibited substantially more deuterium uptake, demonstrating that HDX-MS is highly sensitive to global changes in dynamics that may proceed a loss of function (e.g., via aggregation or denaturation). Studies described by Houde et al. [87] could also be viewed as proof-of-principle for application of HDX to manufacturing process control. Distinct lots of interferon-b-1a (IFN) were produced using different tissue culture media (serum-free) and growth conditions. Peptide level comparisons by HDX-MS were consistent with the reference IFN in all cases. Different batches of IFN (reference IFN vs the same sample stored at 70  C for over 8 years) also showed no significant differences in deuterium uptake values. These studies demonstrate the potential of HDX-MS to become a routine quality control method for GMP (good manufacturing practice) in the biopharmaceutical industry. 4. Emerging techniques 4.1. Time-resolved HDX-MS (TRHDX-MS) The labeling time of the analyte with deuterium in a conventional HDX-MS setting is usually from 10 s to hours. However, in cases where the protein structure is very dynamic, such as intrinsically disordered proteins (IDP), the exchange could be so fast (<1 s) that maximum deuterium exchange will be reached even before the first measurement takes place. Some processes that are of great biological importance, including catalytically relevant conformational transitions in enzymatic reactions, would not be detected by conventional HDX-MS. Additionally, the ‘allosteric effects’ that obfuscate binding sites in HDX measurements of proteinprotein/ligand interactions may not occur (or may be suppressed) on a shorter timescale. Pulsed HDX-MS in the gas-phase (in the mass spectrometer), has been proposed to address this problem, however its application is very limited due to the complicated gasphase exchange mechanism [97], structural differences of the protein in the gas-phase and in solution [98], and instrumentation restrictions [98].

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Fig. 6. Comparability profiles of reference interferon-b-1a (IFN) versus oxidized IFN [87]. (a) Mirror plot for visual comparison of HDX rates for IFN (top) and oxidized IFN (bottom), peptides 10e20 showed similarities while peptides 30e40 showed differences in HDX uptake data. (b) Difference plot calculated from data in (a) indicates that the main difference in HDX regions are in peptides 26e38. Reproduced from Ref. [87] with permission of John Wiley & Sons, Inc.© 2011.

On the other hand, Konermann et al. [99,100] introduced a continuous-flow apparatus with two concentric capillaries that allows for millisecond mixing of two solvents triggering the reaction of interest, followed by immediate analysis by ESI-MS. This approach, known as Time-Resolved ElectroSpray Ionization Mass Spectrometry (TRESI-MS) allows transient solution-phase processes, such as protein folding and reaction kinetics, to be investigated by MS on the millisecond timescale. Rob et al. [101e103] later incorporated TRESI-MS onto a microfluidic chip (Fig. 7) enabling on-chip quenching and protein digestion for local HDX-MS analysis. This novel TRHDX-MS technique is highly suitable for sub-second HDX labeling of weakly structured proteins and rapid conformational dynamics [101]. Zhu et al. [105] used TRHDX-MS to obtain detailed information on the residual structures of Tau protein and the shifts in Tau conformational bias induced by hyperphosphorylation. Lento et al. [106] studied the local structural changes in the monomer-dimer equilibrium of Pseudomonas aeruginosa strain K122-4 (DK122) in solution prior to oligomerization into protein nanotubes. For the study of protein-ligand interactions, Resetca et al. [107] investigated the interaction of signal transducer and activator of transcription 3 (STAT3) and small molecule inhibitors of Src homology 2 (SH2) domain as potential chemotherapeutic agents. Both changes in dynamics of the highly unstructured SH2 domain and allosteric perturbations outside of the SH2 domain were found by TRHDXMS. As mentioned previously, identification of epitopes in

Fig. 7. The microfluidic chip enables time-resolved hydrogen deuterium exchange (TRHDX) coupled with mass spectrometry for sub-second detection of weakly structured proteins and rapid conformational dynamics. The kinetic mixer for rapid mixing, along with an acid quenching channel and proteolytic pepsin chamber were integrated onto the microfluidic chip. The lysed peptides were analyzed by MS for further identification and HDX analysis. Reproduced from Ref. [104] with permission of Federation of European Biochemical Societies© 2016.

antigen-antibody binding may be interfered by allosteric effects. A preliminary report from Deng et al. suggests that millisecond timescale HDX labeling may suppress or eliminate these allosteric artifacts, providing enhanced epitope mapping by HDXMS [108].

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5. Challenges and future direction Limitations of HDX-MS for its wide acceptance and routine application include sophisticated experimental platforms, laborious manual data processing, challenges in achieving the necessary degree of reproducibility, and method standardization issues. Automation of the instrumental systems, such as is available in the Waters HDX system (currently the only commercial HDX system on the market), will provide seamless sample handling of HDX-LC/MS for a better sample throughput [109]. In parallel, advances in software development for data analysis are needed to shorten data processing times and improve data presentation [110]. In addition to the DynamX HDX Data Analysis package from Waters, other software such as HDX Work Bench [111] and HDX Analyzer [112] among others, give a number of choices to users for interpretation of HDX-MS data. Enhanced commercial or academic availability of HDX analysis software would undoubtedly make HDX-MS more widely used as a routine analytical method in biopharmaceutical industry. Improvements to HDX-MS spatial resolution from peptide to amino acid residue level could be realized by the application of enhanced electron-capture (ECD) and electrontransfer dissociation (ETD) fragmentation methods [113,114]. With standardized instrumentation and standard operating procedures (SOP) for HDX-MS methods, there are indications that the reproducibility of HDX-MS can be made sufficient to support the needs of industry [115,116]. The NIST Interlaboratory Comparison Project is also ongoing, with the aim of measuring the reproducibility of HDX-MS using a fully standardized NIST antibody reference compound [117]. Presently, HDX-MS will continue to be used with other structural approaches, as well as with computational modeling and docking studies [66] to tackle complicated questions about protein conformation and dynamics. These advancements in HDX-MS will further promote its application in aspects of drug discovery and development in biopharmaceutical industry, especially in new drug design and development [23], high-throughput screening [118], comparability profiles of biosimilars [79], quality control for protein therapeutics [14], and mechanism studies of biological interactions [119]. HDX-MS also will be more accepted as a standard analytical method for FDA filing and application in the near future. 6. Conclusions HDX-MS is quickly gaining prominence as a rapid, robust and powerful analytical technique for measuring higher order structure and conformational dynamics of protein therapeutics. Even now it is widely used in the pharmaceutical industry at all stages, from understanding protein targets, protein-ligand, and protein-protein interactions, to target-directed drug development, modification, formulation and manufacturing. HDX-MS can act as a screening method for drug candidate libraries, a tool for early and late lead optimization and a routine quality control method for protein therapeutics in manufacturing. Thus, as the biopharmaceuticals industry continues to grow, so too will the suite of HDX-MS methods, instrumentation, data processing software and computational modeling providing critical support for new drug discovery and development. Acknowledgements The Wilson lab is supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada Discovery (504027), Engage (492095-15) and Collaborative Research and Development (CRD) (485321-15) Programs. Additional support is provided by the Krembil Foundation, the Canadian Alzheimer's Society,

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Dr. Bin Deng is currently working as a Postdoctoral Fellow at Chemistry Department of York University, Toronto. His research interests mainly include biochemical mass spectrometry, protein therapeutics, microfluidics and natural products. More information can be found at: https://ca. linkedin.com/in/david-bin-deng-15651950.

Cristina obtained her BSc at York University in Specialized Honours Biochemistry. She went on to complete her MSc in Chemistr y whe re she implemented hydrogendeuterium exchange mass spectrometry to study proteinprotein interactions involved in the oligomerization of the K122-4 pilin from P. aeruginosa and between F-plasmid transfer proteins involved in bacterial conjugation. Currently, she is working as a research assistant for Dr. Derek Wilson's lab at York University.

Derek Wilson graduated from Trent University (Ontario, Canada) in 2001 with a BSc in biochemistry. This was followed by a PhD with Lars Konermann at Western University (Ontario, Canada) where he trained in bioanalytical mass spectrometry and a post-doc in 2005 with Chris Dobson at Cambridge (Cambridgeshire, UK), in bioanalytical NMR with a focus on protein folding and interactions. Shortly thereafter, he was hired as an assistant professor at York, taking up the position in 2007. He is currently director of the Center for Research in Mass Spectrometry (CRMS), manager of the Mass Spectrometry Enabled Science and Engineering (MS-ESE) training program, and lead investigator in the Technology-enhanced Biopharmaceuticals Development and Manufacturing (TBio-DM) initiative.