Prediction and Reduction of the Aggregation of Monoclonal Antibodies

Dynamic optimization of an integrated cultivation-aggregation model for mAb production

Due to their proteinaceous structure, monoclonal antibodies (mAbs) are susceptible to irreversible aggregation, with harmful consequences on drug efficacy and patient safety. To mitigate this risk in modern biopharmaceutical processes, it is critical to comply with current good manufacturing practices (cGMP) and pursue operating strategies minimizing irreversible aggregation whilst also maximizing mAb throughput. These conflicting objectives are targeted in this study by formulating and analyzing an integrated dynamic model accounting for both cultivation and aggregation of mAbs from a Chinese Hamster Ovary (CHO) cell line. Two manipulated dynamic variables are considered here in simulation studies: firstly temperature manipulation within a batch reactor, and secondly feed flow manipulation within a series of isothermal fed-batch reactors. Following this, dynamic optimization investigations have been conducted, firstly with the single objective of maximizing mAb throughput and secondly with multiple (two) objectives of maximizing mAb throughput while also minimizing irreversible aggregate content, simultaneously. The study provides key insight into tradeoffs of how simultaneous temperature and feed flowrate manipulation affects mAb throughput and aggregation inside bioreactors.

Integrated micro-scale protein a chromatography and Low pH viral inactivation unit operations on an automated platform

High throughput process development (HTPD) is established for time- and resource- efficient chromatographic process development. However, integration with non-chromatographic operations within a monoclonal antibody (mAb) purification train is less developed. An area of importance is the development of low pH viral inactivation (VI) that follows protein A chromatography. However, the lack of pH measurement devices at the micro-scale represents a barrier to implementation, which prevents integration with the surrounding unit operations, limiting overall process knowledge. This study is based upon the design and testing of a HTPD platform for integration of the protein A and low pH VI operations. This was achieved by using a design and simulation software before execution on an automated liquid handler. The operations were successfully translated to the micro-scale, as assessed by analysis of recoveries and molecular weight content. The integrated platform was then used as a tool to assess the effect of pH on HMWC during low pH hold. The laboratory-scale and micro-scale elution pools showed comparable HMWC across the pH range 3.2-3.7. The investigative power of the platform is highlighted by evaluating the resources required to conduct a hypothetical experiment. This results in lower resource demands and increased labor efficiency relative to the laboratory-scale. For example, the experiment can be conducted in 7 h, compared to 105 h, translating to labor hours, 3 h and 28 h for the micro-scale and laboratory-scale, respectively. This presents the opportunity for further integration beyond chromatographic operations within the purification sequence, to establish a fit-to-platform assessment tool for mAb process development.

Click, Compute, Create: A Review of Web-based Tools for Enzyme Engineering

Enzyme engineering, though pivotal across various biotechnological domains, is often plagued by its time-consuming and labor-intensive nature. This review aims to offer an overview of supportive in silico methodologies for this demanding endeavor. Starting from methods to predict protein structures, to classification of their activity and even the discovery of new enzymes we continue with describing tools used to increase thermostability and production yields of selected targets. Subsequently, we discuss computational methods to modulate both, the activity as well as selectivity of enzymes. Last, we present recent approaches based on cutting-edge machine learning methods to redesign enzymes. With exception of the last chapter, there is a strong focus on methods easily accessible via web-interfaces or simple Python-scripts, therefore readily useable for a diverse and broad community.

Pharmacology of erenumab in human isolated coronary and meningeal arteries: Additional effect of gepants on top of a maximum effect of erenumab

BACKGROUND AND PURPOSE

Multiple drugs targeting the calcitonin gene-related peptide (CGRP) receptor have been developed for migraine treatment. Here, the effect of the monoclonal antibody erenumab on CGRP-induced vasorelaxation was investigated in human isolated blood vessels, as well as the effect of combining erenumab with the small molecule drugs, namely rimegepant, olcegepant, or sumatriptan.

EXPERIMENTAL APPROACH

Concentration-response curves to CGRP, adrenomedullin or pramlintide were constructed in human coronary artery (HCA) and human middle meningeal artery (HMMA) segments, incubated with or without erenumab and/or olcegepant. pA2 or pKb values were calculated to determine the potency of erenumab in both tissues. To study whether acutely acting antimigraine drugs exerted additional CGRP-blocking effects on top of erenumab, HCA segments were incubated with a maximally effective concentration of erenumab (3 μM), precontracted with KCl and exposed to CGRP, followed by rimegepant, olcegepant, or sumatriptan in increasing concentrations.

KEY RESULTS

Erenumab shifted the concentration-response curve to CGRP in both vascular tissues. However, in HCA, the Schild plot slope was significantly smaller than unity, whereas this was not the case in HMMA, indicating different CGRP receptor mechanisms in these tissues. In HCA, rimegepant, olcegepant and sumatriptan exerted additional effects on CGRP on top of a maximal effect of erenumab.

CONCLUSIONS AND IMPLICATIONS

Gepants have additional effects on top of erenumab for CGRP-induced relaxation and could be effective in treating migraine attacks in patients already using erenumab as prophylaxis.

How enzymatic hydrolysis of polysorbate 20 influences colloidal protein stability

Polysorbates (PS) are esters of ethoxylated sorbitol anhydrides of different composition and are widely used surfactants in biologics. PSs are applied to increase protein stability and concomitant shelf-life via shielding against e.g., interfacial stresses. Due to the presence of specific lipolytic host cell protein (HCP) contaminations in the drug substance, PSs can be degraded via enzymatic hydrolysis. Surfactant hydrolysis leads to the formation of degradants, such as free fatty acids that might form fatty acid particles. In addition, PS degradation may reduce surfactant functionality and thus reduce the protection of the active pharmaceutical ingredient (API). Although enzymatic degradation was observed and reported in the last years, less is known about the relationship between certain polysorbate degradation patterns and the increase of mechanical and interfacial stress towards the API. In this study, the impact of specifically hydrolyzed polysorbate 20 (PS20) towards the stabilization of two monoclonal antibodies (mAbs) during accelerated shaking stress conditions was investigated. The results show that a specific enzymatic degradation pattern of PS20 can influence the colloidal stability of biopharmaceutical formulations. Furthermore, the kinetics of the appearance of visual phenomena, opalescence, and particle formation depended on the polysorbate degradation fingerprint as induced via the presence of surrogate enzymes. The current case study shows the importance of focusing on specific polysorbate ester fractions to understand the overall colloidal protein stabilizing effect. The performed study gives first insight into the functional properties of PS and helps to evaluate the impact of PS degradation in the formulation development of biopharmaceuticals in general.

Surfactants reduce aggregation of monoclonal antibodies in cell culture medium with improvement in performance of mammalian cell culture

Therapeutic monoclonal antibodies (mAbs) are biologics produced using mammalian cells and represent an important class of biotherapeutics. Aggregation in mAbs is a major challenge that can be mitigated by rigorous and reproducible upstream and downstream approaches. The impact of frequently used surfactants, like polysorbate 20, polysorbate 80, poloxamer 188, and 2-hydroxypropyl-beta-cyclodextrin, on aggregation of mAbs during cell culture was investigated in this study. Their impact on cell proliferation, viability, and mAb titer was also investigated. Polysorbate 20 and polysorbate 80 at the concentration of 0.01 g/L and poloxamer 188 at the concentration of 5 g/L were found to be effective in reducing aggregate formation in cell culture medium, without affecting the cell growth or viability. Furthermore, their presence in culture media resulted in increased cell proliferation as compared to the control group. Addition of these surfactants at the specified concentrations increased monomer production while decreasing high molecular weight species in the medium. After mAbs were separated, using protein "A" chromatography, flasks with surfactant exhibited improved antibody stability, when analyzed by DLS. Thus, while producing aggregation-prone mAbs via mammalian cell culture, these excipients may be employed as cell culture medium supplements to enhance the quality and yield of functional mAbs.

Understanding and controlling the molecular mechanisms of protein aggregation in mAb therapeutics

In antibody development and manufacturing, protein aggregation is a common challenge that can lead to serious efficacy and safety issues. To mitigate this problem, it is important to investigate its molecular origins. This review discusses (1) our current molecular understanding and theoretical models of antibody aggregation, (2) how various stress conditions related to antibody upstream and downstream bioprocesses can trigger aggregation, and (3) current mitigation strategies employed towards inhibiting aggregation. We discuss the relevance of the aggregation phenomenon in the context of novel antibody modalities and highlight how in silico approaches can be exploited to mitigate it.

Discovery and Characterization of an Acid-Labile Serine-Lysine Cross-Link in Antibody High-Molecular-Weight Species Using a Multipronged Mass Spectrometry Approach

Characterizing the cross-links responsible for the covalent high-molecular-weight (HMW) species in therapeutic monoclonal antibodies (mAbs) is of great importance as it not only provides a framework for risk assessment but also offers insights for process improvement. However, owing to the complexity and low abundance, identification of novel and unknown cross-links in mAb products can be very challenging. Here, applying a multipronged MS-based approach, we report the discovery of a novel covalent cross-link formed via an imine bond between lysine and serine residues. In particular, this Ser-Lys cross-link was found to be acid-labile and can be easily overlooked by conventional LC-MS techniques operated at low pH. It is worth noting that although imine-based cross-link has been previously reported in collagen protein cross-linking, this is the first time that a Ser-Lys cross-link has been found in a mAb product that contributes to covalent HMW species formation.

How can we discover developable antibody-based biotherapeutics?

Antibody-based biotherapeutics have emerged as a successful class of pharmaceuticals despite significant challenges and risks to their discovery and development. This review discusses the most frequently encountered hurdles in the research and development (R&D) of antibody-based biotherapeutics and proposes a conceptual framework called biopharmaceutical informatics. Our vision advocates for the syncretic use of computation and experimentation at every stage of biologic drug discovery, considering developability (manufacturability, safety, efficacy, and pharmacology) of potential drug candidates from the earliest stages of the drug discovery phase. The computational advances in recent years allow for more precise formulation of disease concepts, rapid identification, and validation of targets suitable for therapeutic intervention and discovery of potential biotherapeutics that can agonize or antagonize them. Furthermore, computational methods for de novo and epitope-specific antibody design are increasingly being developed, opening novel computationally driven opportunities for biologic drug discovery. Here, we review the opportunities and limitations of emerging computational approaches for optimizing antigens to generate robust immune responses, in silico generation of antibody sequences, discovery of potential antibody binders through virtual screening, assessment of hits, identification of lead drug candidates and their affinity maturation, and optimization for developability. The adoption of biopharmaceutical informatics across all aspects of drug discovery and development cycles should help bring affordable and effective biotherapeutics to patients more quickly.

KA-Search, a method for rapid and exhaustive sequence identity search of known antibodies

Antibodies with similar amino acid sequences, especially across their complementarity-determining regions, often share properties. Finding that an antibody of interest has a similar sequence to naturally expressed antibodies in healthy or diseased repertoires is a powerful approach for the prediction of antibody properties, such as immunogenicity or antigen specificity. However, as the number of available antibody sequences is now in the billions and continuing to grow, repertoire mining for similar sequences has become increasingly computationally expensive. Existing approaches are limited by either being low-throughput, non-exhaustive, not antibody specific, or only searching against entire chain sequences. Therefore, there is a need for a specialized tool, optimized for a rapid and exhaustive search of any antibody region against all known antibodies, to better utilize the full breadth of available repertoire sequences. We introduce Known Antibody Search (KA-Search), a tool that allows for the rapid search of billions of antibody variable domains by amino acid sequence identity across either the variable domain, the complementarity-determining regions, or a user defined antibody region. We show KA-Search in operation on the [Formula: see text]2.4 billion antibody sequences available in the OAS database. KA-Search can be used to find the most similar sequences from OAS within 30 minutes and a representative subset of 10 million sequences in less than 9 seconds. We give examples of how KA-Search can be used to obtain new insights about an antibody of interest. KA-Search is freely available at https://github.com/oxpig/kasearch .

Predictive Nature of High-Throughput Assays in ADC Formulation Screening

Utilization of high-throughput biophysical screening techniques during early screening studies is warranted due to the limited amount of material and large number of samples. But the predictability of the data to longer-term storage stability is critical as the high-throughput methods assist in defining the design space for the longer-term studies. In this study, the biophysical properties of two ADCs in 16 formulation conditions were evaluated using high-throughput techniques. Conformational stability and colloidal stability were evaluated by determining Tm values, kD, B22, and Tagg. In addition, the samples were placed on stability and the extent of aggregate formation over the 8-week interval was determined. The rank order of the 16 different formulations in the high-throughput assays was compared to the rank order observed during the stability studies to assess the predictive capabilities of the screening methods. It was demonstrated that similar rank orders can be expected between high-throughput physical stability indicating assays such as Tagg and B22 and traditional aggregation by SEC data, whereas conformational stability read-outs (Tm) are less predictive. In addition, the high-throughput assays appropriately identified the poor performing formulation conditions, which is ultimately what is desired of screening assays.

An overview of descriptors to capture protein properties - Tools and perspectives in the context of QSAR modeling

Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.

Ion Mobility Mass Spectrometry (IM-MS) for Structural Biology: Insights Gained by Measuring Mass, Charge, and Collision Cross Section

The investigation of macromolecular biomolecules with ion mobility mass spectrometry (IM-MS) techniques has provided substantial insights into the field of structural biology over the past two decades. An IM-MS workflow applied to a given target analyte provides mass, charge, and conformation, and all three of these can be used to discern structural information. While mass and charge are determined in mass spectrometry (MS), it is the addition of ion mobility that enables the separation of isomeric and isobaric ions and the direct elucidation of conformation, which has reaped huge benefits for structural biology. In this review, where we focus on the analysis of proteins and their complexes, we outline the typical features of an IM-MS experiment from the preparation of samples, the creation of ions, and their separation in different mobility and mass spectrometers. We describe the interpretation of ion mobility data in terms of protein conformation and how the data can be compared with data from other sources with the use of computational tools. The benefit of coupling mobility analysis to activation via collisions with gas or surfaces or photons photoactivation is detailed with reference to recent examples. And finally, we focus on insights afforded by IM-MS experiments when applied to the study of conformationally dynamic and intrinsically disordered proteins.

Identification of AL proteins from 10 λ-AL amyloidosis patients by mass spectrometry extracted from abdominal fat and heart tissue

BACKGROUND

Systemic AL amyloidosis arises from the misfolding of patient-specific immunoglobulin light chains (LCs). Potential drivers of LC amyloid formation are mutational changes and post-translational modifications (PTMs). However, little information is available on the exact primary structure of the AL proteins and their precursor LCs.

OBJECTIVE

We analyse the exact primary structure of AL proteins extracted from 10 λ AL amyloidosis patients and their corresponding precursor LCs.

MATERIALS AND METHODS

By cDNA sequencing of the precursor LC genes in combination with mass spectrometry of the AL proteins, the exact primary structure and PTMs were determined. This information was used to analyse their biochemical properties.

RESULTS

All AL proteins comprise the V_L and a small part of the C_L with a common C-terminal truncation region. While all AL proteins retain the conserved native disulphide bond of the V_L, we found no evidence for presence of other common PTMs. The analysis of the biochemical properties revealed that the isoelectric point of the V_L is significantly increased due to introduced mutations.

CONCLUSION

Our data imply that mutational changes influence the surface charge properties of the V_L and that common proteolytic processes are involved in the generation of the cleavage sites of AL proteins.

Exploiting the intrinsic misfolding propensity of the KRAS oncoprotein

Mutant KRAS is a major driver of oncogenesis in a multitude of cancers but remains a challenging target for classical small molecule drugs, motivating the exploration of alternative approaches. Here, we show that aggregation-prone regions (APRs) in the primary sequence of the oncoprotein constitute intrinsic vulnerabilities that can be exploited to misfold KRAS into protein aggregates. Conveniently, this propensity that is present in wild-type KRAS is increased in the common oncogenic mutations at positions 12 and 13. We show that synthetic peptides (Pept-ins™) derived from two distinct KRAS APRs could induce the misfolding and subsequent loss of function of oncogenic KRAS, both of recombinantly produced protein in solution, during cell-free translation and in cancer cells. The Pept-ins exerted antiproliferative activity against a range of mutant KRAS cell lines and abrogated tumor growth in a syngeneic lung adenocarcinoma mouse model driven by mutant KRAS G12V. These findings provide proof-of-concept that the intrinsic misfolding propensity of the KRAS oncoprotein can be exploited to cause its functional inactivation.

Afraid of the wall of death? Considerations on monoclonal antibody characteristics that trigger aggregation during peristaltic pumping

Protein aggregation is of major concern in manufacturing of biopharmaceutics. Protein aggregation upon peristaltic pumping for filtration, transfer or filling is triggered by protein adsorption to the tubing surface and subsequent film rupture during roller movement. While the impact of tubing type and formulation has been studied in more detail, the contribution of the protein characteristics is not fully resolved. We studied the aggregation propensity of six monoclonal antibodies during peristaltic pumping and characterized their colloidal and conformational stability, hydrophobicity, and surface activity. A high affinity to the surface resulting in faster adsorption and film renewal was key for the formation of protein particles ≥ 1 µm. Film formation and renewal were influenced by the antibody hydrophobicity, potential for electrostatic self-interaction and conformational stability. The initial interfacial pressure increase within the first minute can serve as a good predictor for antibody adsorption and particle formation propensity. Our results highlight the complexity of protein adsorption and emphasize the importance of formulation development to reduce protein particle formation by avoidance of adsorption to interfaces.

A guide to studying protein aggregation

Disrupted protein folding or decreased protein stability can lead to the accumulation of (partially) un- or misfolded proteins, which ultimately cause the formation of protein aggregates. Much of the interest in protein aggregation is associated with its involvement in a wide range of human diseases and the challenges it poses for large-scale biopharmaceutical manufacturing and formulation of therapeutic proteins and peptides. On the other hand, protein aggregates can also be functional, as observed in nature, which triggered its use in the development of biomaterials or therapeutics as well as for the improvement of food characteristics. Thus, unmasking the various steps involved in protein aggregation is critical to obtain a better understanding of the underlying mechanism of amyloid formation. This knowledge will allow a more tailored development of diagnostic methods and treatments for amyloid-associated diseases, as well as applications in the fields of new (bio)materials, food technology and therapeutics. However, the complex and dynamic nature of the aggregation process makes the study of protein aggregation challenging. To provide guidance on how to analyse protein aggregation, in this review we summarize the most commonly investigated aspects of protein aggregation with some popular corresponding methods.

Enhancing and stabilizing monoclonal antibody production by Chinese hamster ovary (CHO) cells with optimized perfusion culture strategies

The perfusion medium is critical in maintaining high cell concentration in cultures for the production of monoclonal antibody by Chinese hamster ovary cells. In this study, the effects of perfusion culture strategies when using different media on the process stability, product titer, and product quality were investigated in 3-L bioreactor. The results indicated that continuous perfusion could maintain higher levels of cell density, product titer, and quality in comparison with those of the intermittent perfusion culture. Next, the perfusion culture conditions with different perfusion rates and temperature reduction methods were further optimized. When combining the high perfusion rates and delayed reduction of culture temperature at day 6, the product titer reached a higher level of 16.19 g/L with the monomer relative abundant of 97.6%. In this case, the main peak of the product reached 56.3% and the total N-glycans ratio was 95.2%. To verify the effectiveness of the optimized perfusion culture in a larger scale, a 200-L bioreactor was used to perform and the final product titer reached the highest level of 16.79 g/L at day 16. Meanwhile, the product quality (monomer abundant of 97.6%, main peak of 56.3%, and N-glycans ratio of 96.5%) could also be well maintained. This study provided some guidance for the high-efficient production of monoclonal antibody by CHO cells via optimized perfusion culture strategy.

Approaches to expand the conventional toolbox for discovery and selection of antibodies with drug-like physicochemical properties

Antibody drugs should exhibit not only high-binding affinity for their target antigens but also favorable physicochemical drug-like properties. Such drug-like biophysical properties are essential for the successful development of antibody drug products. The traditional approaches used in antibody drug development require significant experimentation to produce, optimize, and characterize many candidates. Therefore, it is attractive to integrate new methods that can optimize the process of selecting antibodies with both desired target-binding and drug-like biophysical properties. Here, we summarize a selection of techniques that can complement the conventional toolbox used to de-risk antibody drug development. These techniques can be integrated at different stages of the antibody development process to reduce the frequency of physicochemical liabilities in antibody libraries during initial discovery and to co-optimize multiple antibody features during early-stage antibody engineering and affinity maturation. Moreover, we highlight biophysical and computational approaches that can be used to predict physical degradation pathways relevant for long-term storage and in-use stability to reduce the need for extensive experimentation.

Binding affinity prediction for antibody-protein antigen complexes: A machine learning analysis based on interface and surface areas

Specific antibodies can bind to protein antigens with high affinity and specificity, and this property makes them one of the best protein-based therapeutics. Accurate prediction of antibody‒protein antigen binding affinity is crucial for designing effective antibodies. The current predictive methods for protein‒protein binding affinity usually fail to predict the binding affinity of an antibody‒protein antigen complex with a comparable level of accuracy. Here, new models specific for antibody‒antigen binding affinity prediction are developed according to the different types of interface and surface areas present in antibody‒antigen complex. The contacts-based descriptors are also employed to construct or train different models specific for antibody‒protein antigen binding affinity prediction. The results of this study show that (i) the area-based descriptors are slightly better than the contacts-based descriptors in terms of the predictive power; (ii) the new models specific for antibody‒protein antigen binding affinity prediction are superior to the previously-used general models for predicting the protein‒protein binding affinities; (iii) the performances of the best area-based and contacts-based models developed in this work are better than the performances of a recently-developed graph-based model (i.e., CSM-AB) specific for antibody‒protein antigen binding affinity prediction. The new models developed in this work would not only help understand the mechanisms underlying antibody‒protein antigen interactions, but would also be of some applicable utility in the design and virtual screening of antibody-based therapeutics.

Assessing developability early in the discovery process for novel biologics

Beyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures. Here, we review some of the most important developability properties that can be assessed early on for biologics. These include the influence of the source of the biologic, its biophysical and pharmacokinetic properties, and how well it can be expressed recombinantly. We furthermore present in silico, in vitro, and in vivo methods and techniques that can be exploited at different stages of the discovery process to identify molecules with liabilities and thereby facilitate the selection of the most optimal drug leads. Finally, we reflect on the most relevant developability parameters for injectable versus orally delivered biologics and provide an outlook toward what general trends are expected to rise in the development of biologics.

Biosimilar monoclonal antibodies: Challenges and approaches towards formulation

Many biologic drug products, particularly monoclonal antibodies (mAbs), were off-patented between 2015 and 2020, and this process is continuing as the number of biologics approvals has increased. However, the availability of affordable biosimilars is delayed by secondary patents related to the formulation and manufacturing process. Therefore, an alternative formulation development is required to avoid infringement of formulation related patents. Several variables must be considered while developing alternative non-infringement formulations, including the time gap between the expiration of the molecule patent and the formulation patent, the ability not to infringe other secondary patents (process-related), and project timelines. As a part of life cycle management, innovator companies are adopting multiple strategies to delay biosimilar competition. Biosimilar companies could use the innovator formulation knowledge space to develop alternative formulations at the expense of time and cost. The present review discusses the key approaches in biosimilar formulation development, and further summarizes the use of innovator formulation knowledge space for biosimilar mAbs product development.

Antibody Interfaces Revealed Through Structural Mining

Antibodies are fundamental effectors of humoral immunity, and have become a highly successful class of therapeutics. There is increasing evidence that antibodies utilize transient homotypic interactions to enhance function, and elucidation of such interactions can provide insights into their biology and new opportunities for their optimization as drugs. Yet the transitory nature of weak interactions makes them difficult to investigate. Capitalizing on their rich structural data and high conservation, we have characterized all the ways that antibody fragment antigen-binding (Fab) regions interact crystallographically. This approach led to the discovery of previously unrealized interfaces between antibodies. While diverse interactions exist, β-sheet dimers and variable-constant elbow dimers are recurrent motifs. Disulfide engineering enabled interactions to be trapped and investigated structurally and functionally, providing experimental validation of the interfaces and illustrating their potential for optimization. This work provides first insight into previously undiscovered oligomeric interactions between antibodies, and enables new opportunities for their biotherapeutic optimization.

Spray-Dried and Spray-Freeze-Dried Powder Formulations of an Anti-Interleukin-4Rα Antibody for Pulmonary Delivery

OBJECTIVE

The therapeutic options for severe asthma are limited, and the biological therapies are all parenterally administered. The purpose of this study was to formulate a monoclonal antibody that targets the receptor for IL-4, an interleukin implicated in the pathogenesis of severe asthma, into a dry powder intended for delivery via inhalation.

METHODS

Dehydration was achieved using either spray drying or spray freeze drying, which exposes the thermolabile biomacromolecules to stresses such as shear and adverse temperatures. 2-hydroxypropyl-beta-cyclodextrin was incorporated into the formulation as protein stabiliser and aerosol performance enhancer. The powder formulations were characterised in terms of physical and aerodynamic properties, while the antibody was assessed with regard to its structural stability, antigen-binding ability, and in vitro biological activity after drying.

RESULTS

The spray-freeze-dried formulations exhibited satisfactory aerosol performance, with emitted fraction exceeding 80% and fine particle fraction of around 50%. The aerosolisation of the spray-dried powders was hindered possibly by high residual moisture. Nevertheless, the antigen-binding ability and inhibitory potency were unaffected for the antibody in the selected spray-dried and spray-freeze-dried formulations, and the antibody was physically stable even after one-year storage at ambient conditions.

CONCLUSIONS

The findings of this study establish the feasibility of developing an inhaled dry powder formulation of an anti-IL-4R antibody using spray drying and spray freeze drying techniques with potential for the treatment of severe asthma.

Application of Supervised and Unsupervised Learning Approaches for Mapping Storage Conditions of Biopharmaceutical Product-A Case Study of Human Serum Albumin

The stability of biopharmaceutical therapeutics over the storage period/shelf life has been a challenging concern for manufacturers. A noble strategy for mapping best and suitable storage conditions for recombinant human serum albumin (rHSA) in laboratory mixture was optimized using chromatographic data as per principal component analysis (PCA), and similarity was defined using hierarchical cluster analysis. In contrast, separability was defined using linear discriminant analysis (LDA) models. The quantitation was performed for rHSA peak (analyte of interest) and its degraded products, i.e., dimer, trimer, agglomerates and other degradation products. The chromatographic variables were calculated using validated stability-indicating assay method. The chromatographic data mapping was done for the above-mentioned peaks over three months at different temperatures, i.e., 20°C, 5-8°C and at room temperature (25°C). The PCA had figured out the ungrouped variable, whereas supervised mapping was done using LDA. As an outcome result of LDA, about 60% of data were correctly classified with the highest sensitivity for 25°C (Aq), 25°C and 5-8°C (Aq with 5% glucose as a stabilizer), whereas the highest specificity was observed for samples stored at 5-8°C (Aq with 5% glucose as a stabilizer).

A Designer Nanoparticle Platform for Controlled Intracellular Delivery of Bioactive Macromolecules: Inhibition of Ubiquitin-Specific Protease 7 in Breast Cancer Cells

Biological therapeutics represent an increasing and critical component of newly approved drugs; however, the inability to deliver biologics intracellularly in a controlled manner remains a major limitation. We have developed a semi-synthetic, tunable phage-like particle (PLP) platform derived from bacteriophage λ. The shell surface can be decorated with small-molecule, biological and synthetic moieties, alone or in combination and in defined ratios. Here, we demonstrate that the platform can be used to deliver biological macromolecules intracellularly and in a controlled manner. Ubiquitin-specific protease 7 (USP7) is a deubiquitinating enzyme that has been widely recognized as an ideal target for the treatment of a variety of cancers. Recently, UbV.7.2, a novel biologic derived from the ubiquitin scaffold, was developed for inhibition of USP7, but issues remain in achieving efficient and controlled intracellular delivery of the biologic. We have shown that decoration of PLPs with trastuzumab (Trz), a HER2-targeted therapeutic used in the treatment of various cancers, results in specific targeting and uptake of Trz-PLPs into HER2-overexpressing breast cancer cells. By simultaneously decorating PLPs with Trz and UbV.7.2, we now show that these particles are also internalized by HER2-positive cells, thus providing a means for intracellular delivery of the biologic in a controlled fashion. Internalized particles retain USP7 inhibition activity of UbV.7.2 and alter the metabolic and proteomic landscapes of these cells. This study demonstrates that the λ "designer nanoparticles" represent a powerful system for the intracellular delivery of biologics in a defined dose.

Methods to Produce Monoclonal Antibodies for the Prevention and Treatment of Viral Infections

A viral threat can arise suddenly and quickly turn into a major epidemic or pandemic. In such a case, it is necessary to develop effective means of therapy and prevention in a short time. Vaccine development takes decades, and the use of antiviral compounds is often ineffective and unsafe. A quick response may be the use of convalescent plasma, but a number of difficulties associated with it forced researchers to switch to the development of safer and more effective drugs based on monoclonal antibodies (mAbs). In order to provide protection, such drugs must have a key characteristic-neutralizing properties, i.e., the ability to block viral infection. Currently, there are several approaches to produce mAbs in the researchers' toolkit, however, none of them may serve as a gold standard. Each approach has its own advantages and disadvantages. The choice of the method depends both on the characteristics of the virus and on time constraints and technical challenges. This review provides a comparative analysis of modern methods to produce neutralizing mAbs and describes current trends in the design of antibodies for therapy and prevention of viral diseases.

Two physics‐based models for pH ‐dependent calculations of protein solubility

When engineering a protein for its biological function, many physicochemical properties are also optimized throughout the engineering process, and the protein's solubility is among the most important properties to consider. Here, we report two novel computational methods to calculate the pH-dependent protein solubility, and to rank the solubility of mutants. The first is an empirical method developed for fast ranking of the solubility of a large number of mutants of a protein. It takes into account electrostatic solvation energy term calculated using Generalized Born approximation, hydrophobic patches, protein charge, and charge asymmetry, as well as the changes of protein stability upon mutation. This method has been tested on over 100 mutations for 17 globular proteins, as well as on 44 variants of five different antibodies. The prediction rate is over 80%. The antibody tests showed a Pearson correlation coefficient, R, with experimental data from .83 to .91. The second method is based on a novel, completely force-field-based approach using CHARMm program modules to calculate the binding energy of the protein to a part of the crystal lattice, generated from X-ray structure. The method predicted with very high accuracy the solubility of Ribonuclease SA and its 3K and 5K mutants as a function of pH without any parameter adjustments of the existing BIOVIA Discovery Studio binding affinity model. Our methods can be used for rapid screening of large numbers of design candidates based on solubility, and to guide the design of solution conditions for antibody formulation.

Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics

Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the "developability assessment" of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability guidelines based on in silico metrics that can be used for the assessment of antibody stability and manufacturability.

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs) are tremendous, the design and discovery of new candidates remain a time and cost-intensive endeavor. In this regard, progress in the generation of data describing antigen binding and developability, computational methodology, and artificial intelligence may pave the way for a new era of in silico on-demand immunotherapeutics design and discovery. Here, we argue that the main necessary machine learning (ML) components for an in silico mAb sequence generator are: understanding of the rules of mAb-antigen binding, capacity to modularly combine mAb design parameters, and algorithms for unconstrained parameter-driven in silico mAb sequence synthesis. We review the current progress toward the realization of these necessary components and discuss the challenges that must be overcome to allow the on-demand ML-based discovery and design of fit-for-purpose mAb therapeutic candidates.

Expanding the toolbox for predictive parameters describing antibody stability considering thermodynamic and kinetic determinants

PURPOSE

Introduction of the activation energy (E_a) as a kinetic parameter to describe and discriminate monoclonal antibody (mAb) stability.

METHODS

E_a is derived from intrinsic fluorescence (IF) unfolding thermograms. An apparent irreversible three-state fit model based on the Arrhenius integral is developed to determine E_a of respective unfolding transitions. These activation energies are compared to the thermodynamic parameter of van´t Hoff enthalpies (∆H_vh). Using a set of 34 mAbs formulated in four different formulations, both the apparent thermodynamic and kinetic parameters together with apparent melting temperatures are correlated collectively with each other to storage stabilities to evaluate its predictive power with respect to long-term effects potentially reflected in shelf-life.

RESULTS

E_a allows for the discrimination of (i) different parent mAbs, (ii) different variants that originate from parent mAbs, and (iii) different formulations. Interestingly, we observed that the E_a of the CH₂ unfolding transition shows strongest correlations with monomer and aggregate content after storage at accelerated and stress conditions when collectively compared to ∆H_vh and T_m of the CH₂ transition. Moreover, the predictive parameters determined for the CH₂ domain show generally stronger correlations with monomer and aggregate content than those derived for the Fab. Qualitative assessment by ranking E_a of the Fab domain showed good agreement with monomer content in storage stabilities of individual mAb sub-sets.

CONCLUSION

E_a from IF unfolding transitions can be used in addition to other commonly used thermodynamic predictive parameters to discriminate and characterize thermal stability of different mAbs in different formulations. Hence, it shows great potential for antibody engineering and formulation scientists.

Ongoing Challenges to Develop High Concentration Monoclonal Antibody-based Formulations for Subcutaneous Administration: Quo Vadis?

Although many subcutaneously (s.c.) delivered, high-concentration antibody formulations (HCAF) have received regulatory approval and are widely used commercially, formulation scientists are still presented with many ongoing challenges during HCAF development with new mAb and mAb-based candidates. Depending on the specific physicochemical and biological properties of a particular mAb-based molecule, such challenges vary from pharmaceutical attributes e.g., stability, viscosity, manufacturability, to clinical performance e.g., bioavailability, immunogenicity, and finally to patient experience e.g., preference for s.c. vs. intravenous delivery and/or preferred interactions with health-care professionals. This commentary focuses on one key formulation obstacle encountered during HCAF development: how to maximize the dose of the drug? We examine methodologies for increasing the protein concentration, increasing the volume delivered, or combining both approaches together. We discuss commonly encountered hurdles, i.e., physical protein instability and solution volume limitations, and we provide recommendations to formulation scientists to facilitate their development of s.c. administered HCAF with new mAb-based product candidates.

Stress-dependent flexibility of a full-length human monoclonal antibody: Insights from molecular dynamics to support biopharmaceutical development

After several decades of advancements in drug discovery, product development of biopharmaceuticals remains a time- and resource-consuming endeavor. One of the main reasons is associated to the lack of fundamental understanding of conformational dynamics of such biologic entities, and how they respond to various stresses encountered during manufacturing. In this work, we have studied the conformational dynamics of human IgG₁κ b12 monoclonal antibody (mAb) using molecular dynamics simulations. The hundreds of nanoseconds long trajectories reveal that b12 mAb is highly flexible. Its variable domains show greater conformational fluctuations than the constant domains. Additionally, it collapses towards a more globular shape in response to thermal stress, leading to decrease in the total solvent exposed surface area and radius of gyration. This behavior is more pronounced for the deglycosylated b12 mAb, and it appears to correlate with increase in inter-domain contacts between specific regions of the antibody. Conformational fluctuations also cause temporary formation and disruption of hydrophobic and charged patches on the antibody surface, which is particularly important for the prediction of CMC properties during development phases of antibody-based biotherapeutics. The insights gained through these simulations may help the development of biologic drugs, especially with regards to manufacturing processes where antibodies may undergo significant thermal stress.

Glycan Profile Analysis of Engineered Trastuzumab with Rationally Added Glycosylation Sequons Presents Significantly Increased Glycan Complexity

Protein aggregation constitutes a recurring complication in the manufacture and clinical use of therapeutic monoclonal antibodies (mAb) and mAb derivatives. Antibody aggregates can reduce production yield, cause immunogenic reactions, decrease the shelf-life of the pharmaceutical product and impair the capacity of the antibody monomer to bind to its cognate antigen. A common strategy to tackle protein aggregation involves the identification of surface-exposed aggregation-prone regions (APR) for replacement through protein engineering. It was shown that the insertion of N-glycosylation sequons on amino acids proximal to an aggregation-prone region can increase the physical stability of the protein by shielding the APR, thus preventing self-association of antibody monomers. We recently implemented this approach in the Fab region of full-size adalimumab and demonstrated that the thermodynamic stability of the Fab domain increases upon N-glycosite addition. Previous experimental data reported for this technique have lacked appropriate confirmation of glycan occupancy and structural characterization of the ensuing glycan profile. Herein, we mutated previously identified candidate positions on the Fab domain of Trastuzumab and employed tandem mass spectrometry to confirm attachment and obtain a detailed N-glycosylation profile of the mutants. The Trastuzumab glycomutants displayed a glycan profile with significantly higher structural heterogeneity compared to the HEK Trastuzumab antibody, which contains a single N-glycosylation site per heavy chain located in the CH2 domain of the Fc region. These findings suggest that Fab N-glycosites have higher accessibility to enzymes responsible for glycan maturation. Further, we have studied effects on additional glycosylation on protein stability via accelerated studies by following protein folding and aggregation propensities and observed that additional glycosylation indeed enhances physical stability and prevent protein aggregation. Our findings shed light into mAb glycobiology and potential implications in the application of this technique for the development of “biobetter” antibodies.

Systematic Engineering of Optimized Autonomous Heavy-Chain Variable Domains

Autonomous heavy-chain variable (V_H) domains are the smallest functional antibody fragments, and they possess unique features, including small size and convex paratopes, which provide enhanced targeting of concave epitopes that are difficult to access with larger conventional antibodies. However, human V_H domains have evolved to fold and function with a light chain partner, and alone, they typically suffer from low stability and high aggregation propensity. Development of autonomous human V_H domains, in which aggregation propensity is reduced without compromising antigen recognition, has proven challenging. Here, we used an autonomous human V_H domain as a scaffold to construct phage-displayed synthetic libraries in which aspartate was systematically incorporated at different paratope positions. In selections, the library yielded many anti-EphA1 receptor V_H domains, which were characterized in detail. Structural analyses of a parental anti-EphA1 V_H domain and an improved variant provided insights into the effects of aspartate and other substitutions on preventing aggregation while retaining function. Our naïve libraries and in vitro selection procedures offer a systematic approach to generating highly functional autonomous human V_H domains that resist aggregation and could be used for basic research and biomedical applications.

Advances in mRNA-based drug discovery in cancer immunotherapy

INTRODUCTION

Immune checkpoint inhibitors and adoptive T-cell therapy based on chimeric antigen receptors are the spearhead strategies to exploit the immune system to fight cancer. To take advantage of the full potential of the immune system, cancer immunotherapy must incorporate new biotechnologies such as mRNA technology that may synergize with already approved immunotherapies and act more effectively on immune targets.

AREAS COVERED

This review describes the basics of mRNA biotechnology and provides insight into the recent advances in the use of mRNA for the local and systemic delivery of immunostimulatory antibodies, proinflammatory cytokines or for optimizing adoptive T-cell therapy.

EXPERT OPINION

mRNA-based nanomedicines have great potential to expand the arsenal of immunotherapy tools due to their ability to simplify and accelerate drug development and their suitability for transient and local expression of immunostimulatory molecules, whose systemic and sustained expression would be toxic. The success of mRNA-based COVID-19 vaccines has highlighted the feasibility of this approach. Continuous advances in the delivery and construction of RNA-based vectors hold promise for improvements in clinical efficacy.

Factors affecting the quality of therapeutic proteins in recombinant Chinese hamster ovary cell culture

Chinese hamster ovary (CHO) cells are the most widely used mammalian host cells for the commercial production of therapeutic proteins. Fed-batch culture is widely used to produce therapeutic proteins, including monoclonal antibodies, because of its operational simplicity and high product titer. Despite technical advances in the development of culture media and cell cultures, it is still challenging to maintain high productivity in fed-batch cultures while also ensuring good product quality. In this review, factors that affect the quality attributes of therapeutic proteins in recombinant CHO (rCHO) cell culture, such as glycosylation, charge variation, aggregation, and degradation, are summarized and categorized into three groups: culture environments, chemical additives, and host cell proteins accumulated in culture supernatants. Understanding the factors that influence the therapeutic protein quality in rCHO cell culture will facilitate the development of large-scale, high-yield fed-batch culture processes for the production of high-quality therapeutic proteins.

Potential of Phage Display Antibody Technology for Cardiovascular Disease Immunotherapy

Cardiovascular disease (CVD) is one of the leading causes of death worldwide. CVD includes coronary artery diseases such as angina, myocardial infarction, and stroke. "Lipid hypothesis" which is also known as the cholesterol hypothesis proposes the linkage of plasma cholesterol level with the risk of developing CVD. Conventional management involves the use of statins to reduce the serum cholesterol levels as means for CVD prevention or treatment. The regulation of serum cholesterol levels can potentially be regulated with biological interventions like monoclonal antibodies. Phage display is a powerful tool for the development of therapeutic antibodies with successes over the recent decade. Although mainly for oncology, the application of monoclonal antibodies as immunotherapeutic agents could potentially be expanded to CVD. This review focuses on the concept of phage display for antibody development and discusses the potential target antigens that could potentially be beneficial for serum cholesterol management.

Effect of charged mutation on aggregation of a pentapeptide: Insights from molecular dynamics simulations

Aggregation of therapeutic monoclonal antibodies (mAbs) can negatively affect their chemistry, manufacturing, and control attributes and lead to undesirable immune responses in patients. Therefore, optimization of lead mAb drug candidates during discovery stages to mitigate aggregation is increasingly becoming an integral part of their developability assessments. The disruption of short sequence motifs called aggregation prone regions (APRs) found in amino acid sequences of mAb candidates can potentially mitigate their aggregation. In this work, we have performed molecular dynamics simulations to study the aggregation of an APR (VLVIY) found in λ light chains of human antibodies and its single point mutant KLVIY. Eighteen different multicopy peptide simulation systems of "VLVIY" and "KLVIY" were constructed by varying their concentrations, temperatures, termini capping, and flanking gate-keeper regions. Within 20 ns of the simulation, peptide "VLVIY" formed an aggregate of 100 peptides at ~0.1 M concentration with a 60% reduction in solvent accessible surface area (SASA). Furthermore, analysis of the SASA change, peptide cluster distribution, and water residence time demonstrated how Val ➔ Lys mutation resists aggregation and improves solubility. Presence of Lys slows down aggregation kinetics via charge-charge repulsions and by raising the kinetic barrier to formation of large oligomers. However, the effect of the Val ➔ Lys mutation is dependent on sequence and structural contexts around the APR. This mutation also alters the solvation shell around the peptide by favoring solute-solvent interactions, thereby increasing its solubility. This work has provided a detailed mechanistic explanation of how APR disruption can mitigate aggregation in biotherapeutics and improve their developability.

Rational optimization of a monoclonal antibody improves the aggregation propensity and enhances the CMC properties along the entire pharmaceutical process chain

The discovery of therapeutic monoclonal antibodies (mAbs) primarily focuses on their biological activity favoring the selection of highly potent drug candidates. These candidates, however, may have physical or chemical attributes that lead to unfavorable chemistry, manufacturing, and control (CMC) properties, such as low product titers, conformational and colloidal instabilities, or poor solubility, which can hamper or even prevent development and manufacturing. Hence, there is an urgent need to consider the developability of mAb candidates during lead identification and optimization. This work provides a comprehensive proof of concept study for the significantly improved developability of a mAb variant that was optimized with the help of sophisticated in silico tools relative to its difficult-to-develop parental counterpart. Interestingly, a single amino acid substitution in the variable domain of the light chain resulted in a three-fold increased product titer after stable expression in Chinese hamster ovary cells. Microscopic investigations revealed that wild type mAb-producing cells displayed potential antibody inclusions, while the in silico optimized variant-producing cells showed a rescued phenotype. Notably, the drug substance of the in silico optimized variant contained substantially reduced levels of aggregates and fragments after downstream process purification. Finally, formulation studies unraveled a significantly enhanced colloidal stability of the in silico optimized variant while its folding stability and potency were maintained. This study emphasizes that implementation of bioinformatics early in lead generation and optimization of biotherapeutics reduces failures during subsequent development activities and supports the reduction of project timelines and resources.

Modeling the impact of amino acid substitution in a monoclonal antibody on cation exchange chromatography

A vital part of biopharmaceutical research is decision making around which lead candidate should be progressed in early-phase development. When multiple antibody candidates show similar biological activity, developability aspects are taken into account to ease the challenges of manufacturing the potential drug candidate. While current strategies for developability assessment mainly focus on drug product stability, only limited information is available on how antibody candidates with minimal differences in their primary structure behave during downstream processing. With increasing time-to-market pressure and an abundance of monoclonal antibodies (mAbs) in development pipelines, developability assessments should also consider the ability of mAbs to integrate into the downstream platform. This study investigates the influence of amino acid substitutions in the complementarity-determining region (CDR) of a full-length IgG1 mAb on the elution behavior in preparative cation exchange chromatography. Single amino acid substitutions within the investigated mAb resulted in an additional positive charge in the light chain (L) and heavy chain (H) CDR, respectively. The mAb variants showed an increased retention volume in linear gradient elution compared with the wild-type antibody. Furthermore, the substitution of tryptophan with lysine in the H-CDR3 increased charge heterogeneity of the product. A multiscale in silico analysis, consisting of homology modeling, protein surface analysis, and mechanistic chromatography modeling increased understanding of the adsorption mechanism. The results reveal the potential effects of lead optimization during antibody drug discovery on downstream processing.

AlphaFold and the amyloid landscape

Protein aggregation is a widespread phenomenon with important implications in many scientific areas. Although amyloid formation is typically considered as detrimental, functional amyloids that perform physiological roles have been identified in all kingdoms of life. Despite their functional and pathological relevance, the structural details of the majority of molecular species involved in the amyloidogenic process remains elusive. Here, we explore the application of AlphaFold, a highly accurate protein structure predictor, in the field of protein aggregation. While we envision a straightforward application of AlphaFold in assisting the design of globular proteins with improved solubility for biomedical and industrial purposes, the use of this algorithm for predicting the structure of aggregated species seems far from trivial. First, in amyloid diseases, the presence of multiple amyloid polymorphs and the heterogeneity of aggregation intermediates challenges the "one sequence, one structure" paradigm, inherent to sequence-based predictions. Second, aberrant aggregation is not the subject of positive selective pressure, precluding the use of evolutionary-based approaches, which are the core of the AlphaFold pipeline. Instead, amyloid polymorphism seems to be constrained by the need for a defined structure-activity relationship in functional amyloids. They may thus provide a starting point for the application of AlphaFold in the amyloid landscape.

Recombinant Antibody Production Using a Dual-Promoter Single Plasmid System

Monoclonal antibodies (mAbs) have demonstrated tremendous effects on the treatment of various disease indications and remain the fastest growing class of therapeutics. Production of recombinant antibodies is performed using mammalian expression systems to facilitate native antibody folding and post-translational modifications. Generally, mAb expression systems utilize co-transfection of heavy chain (hc) and light chain (lc) genes encoded on separate plasmids. In this study, we examine the production of two FDA-approved antibodies using a bidirectional (BiDi) vector encoding both hc and lc with mirrored promoter and enhancer elements on a single plasmid, by analysing the individual hc and lc mRNA expression levels and subsequent quantification of fully-folded IgGs on the protein level. From the assessment of different promoter combinations, we have developed a generic expression vector comprised of mirrored enhanced CMV (eCMV) promoters showing comparable mAb yields to a two-plasmid reference. This study paves the way to facilitate small-scale mAb production by transient cell transfection with a single vector in a cost- and time-efficient manner.

Complementary Structural Information for Stressed Antibodies from Hydrogen-Deuterium Exchange and Covalent Labeling Mass Spectrometry

Identifying changes in the higher-order structure (HOS) of therapeutic monoclonal antibodies upon storage, stress, or mishandling is important for ensuring efficacy and avoiding adverse effects. Here, we demonstrate diethylpyrocarbonate (DEPC)-based covalent labeling (CL) mass spectrometry (MS) and hydrogen-deuterium exchange (HDX)/MS can be used together to provide site-specific information about subtle conformational changes that are undetectable by traditional techniques. Using heat-stressed rituximab as a model protein, we demonstrate that CL/MS is more sensitive than HDX/MS to subtle HOS structural changes under low stress conditions (e.g., 45 and 55 °C for 4 h). At higher heat stress (65 °C for 4 h), we find CL/MS and HDX/MS provide complementary information, as CL/MS reports on changes in side chain orientation while HDX/MS reveals changes in backbone dynamics. More interestingly, we demonstrate that the two techniques work synergistically to identify likely aggregation sites in the heat-stressed protein. In particular, the C_H3 and C_L domains experience decreases in deuterium uptake after heat stress, while only the C_H3 domain experiences decreases in DEPC labeling extent as well, suggesting the C_H3 domain is a likely site of aggregation and the C_L domain only undergoes a decrease in backbone dynamics. The combination of DEPC-CL/MS and HDX/MS provides valuable structural information, and the two techniques should be employed together when investigating the HOS of protein therapeutics.

Potential aggregation hot spots in recombinant human keratinocyte growth factor: a computational study

The recombinant human keratinocyte growth factor (rhKGF) is a highly aggregation-prone therapeutic protein. The high aggregation liability of rhKGF is manifested by loss of the monomeric state, and accumulation of the aggregated species even at moderate temperatures. Here, we analyzed the rhKGF for its vulnerability toward aggregation by detection of aggregation-prone regions (APRs) using several sequence-based computational tools including TANGO, ZipperDB, AGGRESCAN, Zyggregator, Camsol, PASTA, SALSA, WALTZ, SODA, Amylpred, AMYPDB, and structure-based tools including SolubiS, CamSol structurally corrected, Aggrescan3D and spatial aggregation propensity (SAP) algorithm. The sequence-based prediction of APRs in rhKGF indicated that they are mainly located at positions 10-30, 40-60, 61-66, 88-120, and 130-140. Mapping on the rhKGF structure revealed that most of these residues including F16-R25, I43, E45, R47-I56, F61, Y62, N66, L88-E91, E108-F110, A112, N114, T131, and H133-T140 are surface-exposed in the native state which can promote aggregation without major unfolding event, or the conformational change may occur in the oligomers. The other regions are buried in the native state and their contribution to non-native aggregation is mediated by a preceding unfolding event. The structure-based prediction of APRs using the SAP tool limited the number of identified APRs to the dynamically-exposed hydrophobic residues including V12, A50, V51, L88, I89, L90, I118, L135, and I139 mediating the native-state aggregation. Our analysis of APRs in rhKGF identified the regions determining the intrinsic aggregation propensity of the rhKGF which are the candidate positions for engineering the rhKGF to reduce its aggregation tendency.Communicated by Ramaswamy H. Sarma.

Quantification of Single-Molecule Protein Binding Kinetics in Complex Media with Prism-Coupled Plasmonic Scattering Imaging

Measuring molecular binding is critical for understanding molecular-scale biological processes and screening drugs. Label-free detection technologies, such as surface plasmon resonance (SPR), have been developed for analyzing analytes in their natural forms. However, the specificity of these methods is solely relying on surface chemistry and has often nonspecific binding issues when working with samples in complex media. Herein, we show that single-molecule-based measurement can distinct specific and nonspecific binding processes by quantifying the mass and binding dynamics of individual-bound analyte molecules, thus allowing the binding kinetic analysis in complex media such as serum. In addition, this single-molecule imaging is realized in a commonly used Kretschmann prism-coupled SPR system, thus providing a convenient solution to realize high-resolution imaging on widely used prism-coupled SPR systems.

Novel Method for the Isolation of Proteins and Small Target Molecules from Biological and Aqueous Media by Salt-Assisted Phase Transformation of Their PEGylated Recognition Counterparts

An efficient and simple method for the application of PEGylated affinity ligands in precipitative isolation of protein target molecules (TMs) from a biological fluid such as blood serum or small target molecules from an aqueous medium is presented for the first time. This approach is based on the high binding specificity of PEGylated recognition molecules (PEG-RMs) to their TMs and the unique physicochemical properties of PEG that result in their salt-assisted phase transformation. Addition of PEG-RM to blood serum results in the formation of an RM-specific macromolecular complex (PEG-RM + TM → PEG-RM.TM) that undergoes facile salt-assisted phase transformation to a separable semisolid with ammonium sulfate. PEG-RM.TM is then dissociated into its components by pH reduction or an increase of ionic strength (PEG-RM.TM → PEG-RM + TM). PEG-RM is salted out to afford pure TM in solution. The same phenomenon is observed when RM or TM are small molecules. The general applicability of the method was validated by PEGylation of two proteins (protein A, sheep antihuman IgG) and a small molecule (salicylic acid) used as model RMs for the isolation of Igs, IgG, and serum albumin from blood serum. The isolated protein TMs were shown to be pure and aggregate-free by gel electrophoresis and dynamic light scattering (DLS). IgG isolated by this method was further characterized by peptide mass fingerprinting. PEGylated protein A was used to demonstrate the recyclability and scale-up potential of PEG-RM. IgG isolated by this method from blood serum of a hepatitis C-vaccinated individual was tested for its binding to sheep antihuman IgG by UV spectroscopy, and its bioactivity was ascertained by comparison of its enzyme-linked immunosorbent assay (ELISA) result to that of a blood sample from the same individual. Reciprocity of RM and TM was ascertained using PEGylated salicylic acid to obtain pure serum albumin, and PEGylated serum albumin was utilized for near-exclusive isolation of one drug from an aqueous equimolar mixture of three drugs (salicylic acid, 91%; capecitabine, 6%; and deferiprone, 3%). Advantages of this approach, including target specificity and general applicability and celerity, over other affinity methods for the isolation of proteins are discussed at a molecular level.

Interaction of clinical-stage antibodies with heme predicts their physiochemical and binding qualities

Immunoglobulin repertoires contain a fraction of antibodies that recognize low molecular weight compounds, including some enzymes' cofactors, such as heme. Here, by using a set of 113 samples with variable region sequences matching clinical-stage antibodies, we demonstrated that a considerable number of these antibodies interact with heme. Antibodies that interact with heme possess specific sequence traits of their antigen-binding regions. Moreover they manifest particular physicochemical and functional qualities i.e. increased hydrophobicity, higher propensity of self-binding, higher intrinsic polyreactivity and reduced expression yields. Thus, interaction with heme is a strong predictor of different molecular and functional qualities of antibodies. Notably, these qualities are of high importance for therapeutic antibodies, as their presence was associated with failure of drug candidates to reach clinic. Our study reveled an important facet of information about relationship sequence-function in antibodies. It also offers a convenient tool for detection of liabilities of therapeutic antibodies.