Protein aggregation, particle formation, characterization & rheology

Mung bean protein isolate: Extraction, structure, physicochemical properties, modifications, and food applications

The intake of plant-based proteins is rapidly growing around the world due to their nutritional and functional properties, as well as growing demand for vegetarian and vegan diets. Mung bean seeds have been traditionally consumed in Asian countries due to their unique botanical and health-promoting characteristics. In recent years, mung bean protein isolate (MBPI) has attracted much attention due to its ideal techno-functional features, such as water and oil absorption capacity, solubility, emulsifying, foaming, and thermal properties. Therefore, it can be utilized in a native or modified form in different food sectors, such as biodegradable/edible films, colloidal systems, and plant-based alternative products. This study provides a comprehensive review on the extraction methods, amino acid profile, structure, physicochemical properties, modifications, and food applications of MBPI.

Classical and Nonclassical Nucleation Mechanisms of Insulin Crystals

Although the Classical Nucleation Theory (CNT) is the most consensual theory to explain protein nucleation mechanisms, experimental observations during the shear-induced assays suggest that the CNT does not always describe the insulin nucleation process. This is the case at intermediate precipitant (ZnCl2) solution concentrations (2.3 mM) and high-temperature values (20 and 40 °C) as well as at low precipitant solution concentrations (1.6 mM) and low-temperature values (5 °C). In this work, crystallization events following the CNT registered at high precipitant solution concentrations (3.1 and 4.7 mM) are typically described by a Newtonian response. On the other hand, crystallization events following a nonclassical nucleation pathway seem to involve the formation of a metastable intermediate state before crystal formation and are described by a transition from Newtonian to shear-thinning responses. A dominant shear-thinning behavior (shear viscosity values ranging more than 6 orders of magnitude) is found during aggregation/agglomeration events. The rheological analysis is complemented with different characterization techniques (Dynamic Light Scattering, Energy-Dispersive Spectroscopy, Circular Dichroism, and Differential Scanning Calorimetry) to understand the insulin behavior in solution, especially during the occurrence of aggregation/agglomeration events. To the best of our knowledge, the current work is the first study describing nonclassical nucleation mechanisms during shear-induced crystallization experiments, which reveals the potential of the interdisciplinary approach herein described and opens a window for a clear understanding of protein nucleation mechanisms.

Experimental techniques for detecting and evaluating the amyloid fibrils

Amyloid fibrils are insoluble proteins with intricate β-sheet structures associated with various human diseases, including Parkinson's, Alzheimer's, and prion diseases. Proteins can form aggregates when their structure is misfolded, resulting in highly organized amyloid fibrils or amorphous aggregates. The formation of protein aggregates is a promising research field for mitigating diseases and the pharmaceutical and food industries. It is important to monitor and minimize the appearance of aggregates in these protein products. Several methods exist to assess protein aggregation, that includes from basic investigations to advanced biophysical techniques. Physicochemical parameters such as molecular weight, conformation, structure, and dimension are examined to study aggregation. There is an urgent need to develop methods for the detection of protein aggregation and amyloid fibril formation both in vitro and in vivo. This chapter focuses on a comprehensive discussion of the methods used to characterize and evaluate aggregates and amyloid fibrils.

Study of Monoclonal Antibody Aggregation at the Air-Liquid Interface under Flow by ATR-FTIR Spectroscopic Imaging

Throughout bioprocessing, transportation, and storage, therapeutic monoclonal antibodies (mAbs) experience stress conditions that may cause protein unfolding and/or chemical modifications. Such structural changes may lead to the formation of aggregates, which reduce mAb potency and may cause harmful immunogenic responses in patients. Therefore, aggregates need to be detected and removed or ideally prevented from forming. Air-liquid interfaces, which arise during various stages of bioprocessing, are one of the stress factors causing mAb aggregation. In this study, the behavior of an immunoglobulin G (IgG) at the air-liquid interface was investigated under flow using macro attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic imaging. This chemically specific imaging technique allows observation of adsorption of IgG to the air-liquid interface and detection of associated secondary structural changes. Chemical images revealed that IgG rapidly accumulated around an injected air bubble under flow at 45 °C; however, no such increase was observed at 25 °C. Analysis of the second derivative spectra of IgG at the air-liquid interface revealed changes in the protein secondary structure associated with increased intermolecular β-sheet content, indicative of aggregated IgG. The addition of 0.01% w/v polysorbate 80 (PS80) reduced the amount of IgG at the air-liquid interface in a static setup at 30 °C; however, this protective effect was lost at 45 °C. These results suggest that the presence of air-liquid interfaces under flow may be detrimental to mAb stability at elevated temperatures and demonstrate the power of ATR-FTIR spectroscopic imaging for studying the structural integrity of mAbs under bioprocessing conditions.

Glucagon: Delivery advancements for hypoglycemia management

As the 100th anniversary of glucagon's discovery approaches, we reflect on the remarkable journey of understanding its pivotal role in glucose regulation. Advancements in glucagon delivery systems for managing hypoglycemia are unfolding with promise, albeit accompanied by formulation and implementation challenges. Recent developments include non-injectable methods like BAQSIMI® (Nasal glucagon) offers a user-friendly option, but stability, bioavailability, and rapid onset remain formulation hurdles. Closed-loop systems, combining glucagon with insulin, aim to automate glucose control, demanding stable and precise formulations compatible with complex algorithms. However, achieving co-delivery harmony and effective dual-hormone responses poses substantial challenges. Ogluo® and Gvoke HypoPen® are auto-injector pens, a ready-to-use solution that can rapidly control hypoglycemia and eliminate the need for mixing powder and liquid. GlucaGen® Hypokit® and Glucagon Emergency Kits are traditional deliveries that possess complexity during administration and are still widely used in clinical practice. In addition to this advancement, we have covered the recent patents and clinical trials of glucagon delivery. The synergy of patent innovation and clinical validation offers a glimpse into the transformative potential of glucagon delivery yet underscores the intricate path toward widespread adoption and improved diabetes care. Finally, this review will help the formulation scientist, clinicians, healthcare providers, and patient to manage hypoglycemia using glucagon.

Use of high-intensity ultrasound as a pre-treatment for complex coacervation from whey protein isolate and iota-carrageenan

The aim of this work was to evaluate the influence of high intensity ultrasound (HIUS) treatment on the molecular conformation of whey protein isolated (WPI) as a previous step for complex coacervation with iota carrageenan (IC) and its effect on the surface functional properties of complex coacervates (CC). Both biopolymers were hydrated (1% w/w) separately. A WPI suspension was treated with an ultrasonic bath (40 kHz, 600 W, 30 and 60 min, 100% amplitude). A non-sonicated protein was used as a control. Coacervation was achieved by mixing WPI and IC dispersions (10 min). FTIR-ATR analysis (400-4000 cm-1) detected changes after sonication on WPI secondary structure (1600-1700 cm-1), electrostatic interaction between WPI and IC by electronegative IC charged groups like sulfate (1200-1260 cm-1), anhydrous oxygen of the 3.6 anhydro-D-galactose (940-1066 cm-1) and the electropositive regions of WPI. Rheology results showed pseudoplastic behavior of both IC and WPI-IC with a significant change in viscosity level. Further, HIUS treatment had a positive effect on the emulsifying properties of the WPI-IC coacervates, increasing the time foaming (30 min) and emulsion stability (1 month) percentage. HIUS and complex coacervation proved to be an efficient tool to improve the surface functional properties of WPI.

Protein Association in Solution: Statistical Mechanical Modeling

Protein molecules associate in solution, often in clusters beyond pairwise, leading to liquid phase separations and high viscosities. It is often impractical to study these multi-protein systems by atomistic computer simulations, particularly in multi-component solvents. Instead, their forces and states can be studied by liquid state statistical mechanics. However, past such approaches, such as the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, were limited to modeling proteins as spheres, and contained no microscopic structure-property relations. Recently, this limitation has been partly overcome by bringing the powerful Wertheim theory of associating molecules to bear on protein association equilibria. Here, we review these developments.

Quantitative analysis of antibody aggregates by combination of pinched-flow fractionation and coulter method

For the pharmaceutical development of proteins, multiple methods of analysis are recommended for evaluating aggregation, and the development of more quantitative and simpler analytical techniques for subvisible particles is expected. This study introduces the Pinched-Flow Fractionation (PFF)-Coulter method, which combines the Pinched-flow fractionation (PFF) and Coulter methods to analyze the concentration of submicron-sized particles. The PFF method separates the particles by size. Separated particles were individually detected using the Coulter method. We have utilized the PFF-Coulter method to quantitatively analyze particle concentrations using standard particles, evaluate detection limits, variability, and correlation between theoretical and measured values, and analyze mixtures of different particle sizes. The PFF-Coulter method allows for quantitatively analyzing of particle sizes from 0.2 to 2.0 μm. The quantifiable weight concentration range was 2.5 × 10-2 - 50 μg/mL, and the number concentration range was 104-1010 particles/mL. The sample volume was small (<10 μL). The PFF-Coulter method is capable of quantitative analysis that complements data from conventional measurement techniques, and when used in conjunction with existing submicron-size particle analysis techniques, will enable more accurate particle analysis.

Predicting Colloidal Stability of High-Concentration Monoclonal Antibody Formulations in Common Pharmaceutical Buffers Using Improved Polyethylene Glycol Induced Protein Precipitation Assay

Colloidal stability is an important consideration when developing high concentration mAb formulations. PEG-induced protein precipitation is a commonly used assay to assess the colloidal stability of protein solutions. However, the practical usefulness and the current theoretical model for this assay have yet to be verified over a large formulation space across multiple mAbs and mAb-based modalities. In the present study, we used PEG-induced protein precipitation assays to evaluate colloidal stability of 3 mAbs in 24 common formulation buffers at 20 and 5 °C. These prediction assays were conducted at low protein concentration (1 mg/mL). We also directly characterized high concentration (100 mg/mL) formulations for cold-induced phase separation, turbidity, and concentratibility by ultrafiltration. This systematic study allowed analysis of the correlation between the results of low concentration assays and the high concentration attributes. The key findings of this study include the following: (1) verification of the usefulness of three different parameters (Cmid, μB, and Tcloud) from PEG-induced protein precipitation assays for ranking colloidal stability of high concentration mAb formulations; (2) a new method to implement PEG-induced protein precipitation assay suitable for high throughput screening with low sample consumption; (3) improvement in the theoretical model for calculating robust thermodynamic parameters of colloidal stability (μB and εB) that are independent of specific experimental settings; (4) systematic evaluation of the effects of pH and buffer salts on colloidal stability of mAbs in common formulation buffers. These findings provide improved theoretical and practical tools for assessing the colloidal stability of mAbs and mAb-based modalities during formulation development.

Interfacial Adsorption Controls Particle Formation in Antibody Formulations Subjected to Extensional Flows and Hydrodynamic Shear

During their manufacturing and delivery to patients, therapeutic proteins are commonly exposed to various interfaces and to hydrodynamic shear forces. Although adsorption of proteins to solid-liquid interfaces is known to foster formation of protein aggregates and particles, the impact of shear remains controversial, in part because of experimental challenges in separating the effects of shear from those caused by simultaneous exposure to interfaces. Extensional flows (occurring when solutions flow through sudden contractions) exert localized elongational forces that have been suspected to be damaging to proteins. In this work, we measured aggregation and particle formation in formulations of polyclonal and monoclonal antibodies subjected to extensional flow, high shear (105 s-1) and exposure to stainless-steel/water interfaces. Modification of the surface charge at the stainless steel/water interface changed protein adsorption characteristics without altering shear profiles, enabling shear and interfacial interactions to be separated. Even under conditions where antibodies were subjected to high hydrodynamic shear and extensional flow, production of subvisible particles could be inhibited by modifying the stainless-steel surface charge to minimize antibody adsorption. Digital images of particles recorded by flow imaging microscopy (FIM) and analyzed with machine learning algorithms were consistent with a particle formation mechanism by which antibodies adsorb and aggregate at the stainless-steel/water interface and subsequently form particles when shear displaces the interfacial aggregates, transporting them into the bulk solution. Topographical differences measured using atomic force microscopy (AFM) supported the proposed mechanism by showing reduced levels of protein adsorption on surface-charge-modified stainless-steel.

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.

Studying Intermolecular Interactions in an Antibody-Drug Conjugate Through Chemical Screening and Computational Modeling

Antibody-drug conjugates (ADCs) combine the selectivity of antibodies with the cytotoxicity of drug payloads to yield highly targeted and potent therapeutics. Owing to the need to chemically modify residues for attachment of the payload and their more complex structure compared to either component alone, ADCs can present additional challenges related to stability of the final drug product. Here, we report for the first time the use of high-throughput experimental screens and computational techniques to tune the conformational and colloidal behavior of a monomethyl auristatin F-based ADC. The ADC, which exhibits high opalescence with strongly attractive protein-protein interactions, is transformed into a more stable structure by experimentally traversing a library of more than ∼100 formulations. A significant reduction in turbidity and increase in diffusion interaction parameter is observed by varying properties such as pH and ionic strength. Computational modeling rationalized these changes and pointed to the presence of attractive electrostatic interactions between ADC molecules facilitated by the drug payload and histidine residues. Taken together, the experimental and computational work presented provides a general roadmap of studies to perform during ADC development to find stable formulations, while the mechanistic learnings can be applied towards the design and stabilization of other IgG1-based ADCs.

Mechanism of Insoluble Aggregate Formation in a Reconstituted Solution of Spray-Dried Protein Powder

BACKGROUND

Spray-drying is considered a promising alternative drying method to lyophilization (freeze-drying) for therapeutic proteins. Particle counts in reconstituted solutions of dried solid dosage forms of biologic drug products are closely monitored to ensure product quality. We found that high levels of particles formed after reconstitution of protein powders that had been spray-dried under suboptimal conditions.

METHODS

Visible and subvisible particles were evaluated. Soluble proteins in solution before spray-drying and in the reconstituted solution of spray-dried powder were analyzed for their monomer content levels and melting temperatures. Insoluble particles were collected and analyzed by Fourier transform infrared microscopy (FTIR), and further analyzed with hydrogen-deuterium exchange (HDX).

RESULTS

Particles observed after reconstitution were shown not to be undissolved excipients. FTIR confirmed their identity as proteinaceous in nature. These particles were therefore considered to be insoluble protein aggregates, and HDX was applied to investigate the mechanism underlying aggregate formation. Heavy-chain complementarity-determining region 1 (CDR-1) in the aggregates showed significant protection by HDX, suggesting CDR-1 was critical for aggregate formation. In contrast, various regions became more conformationally dynamic globally, suggesting the aggregates have lost protein structural integrity and partially unfolded after spray-drying.

DISCUSSION

The spray-drying process could have disrupted the higher-order structure of proteins and exposed the hydrophobic residues in CDR-1 of the heavy chain, contributing to the formation of aggregate through hydrophobic interactions upon reconstitution of spray-dried powder. These results can contribute to efforts to design spray-dry resilient protein constructs and improve the robustness of the spray-drying process.

Prediction of protein aggregation propensity employing SqFt-based logistic regression model

Here we present a novel machine-learning approach to predict protein aggregation propensity (PAP) which is a key factor in the formation of amyloid fibrils based on logistic regression (LR). Amyloid fibrils are associated with various neurodegenerative diseases (ND) such as Alzheimer's disease (AD) and Parkinson's disease (PD), which are caused by oxidative stress and impaired protein homeostasis. Accordingly, the paper uses a dataset of hexapeptides with known aggregation tendencies and eight physiochemical features to train and test the LR model. Also, it evaluates the performance of the LR model using F-measure and Matthews correlation coefficient (MCC) as metrics and compares it with other existing methods. Moreover, it investigates the effect of combining sequence and feature information in the prediction. In conclusion, the LR model with sequence and feature information achieves high F-measure (0.841) and MCC (0.6692), outperforming other methods and demonstrating its efficiency and reliability for PAP prediction. In addition, the overall performance of the concluded method was higher than the other known servers, for instance, Aggrescan, Metamyl, Foldamyloid, and PASTA 2.0. The LR model can be accessed at: https://github.com/KatherineEshari/Protein-aggregation-prediction.

The role of water in reactions catalysed by hydrolases under conditions of molecular crowding

Under macromolecular crowding (MC) conditions such as cellular, extracellular, food and other environments of biotechnological interest, the thermodynamic activity of the different macromolecules present in the system is several orders of magnitude higher than in dilute solutions. In this state, the diffusion rates are affected by the volume exclusion induced by the crowders. Immiscible liquid phases, which may arise in MC by liquid-liquid phase separation, may induce a dynamic confinement of reactants, products and/or enzymes, tuning reaction rates. In cellular environments and other crowding conditions, membranes and macromolecules provide, on the whole, large surfaces that can perturb the solvent, causing its immobilisation by adsorption in the short range and also affecting the solvent viscosity in the long range. The latter phenomenon can affect the conformation of a protein and/or the degree of association of its protomers and, consequently, its activity. Changes in the water structure can also alter the enzyme-substrate interaction, and, in the case of hydrolytic enzymes, where water is one of the substrates, it also affects the reaction mechanism. Here, we review the evidence for how macromolecular crowding affects the catalysis induced by hydrolytic enzymes, focusing on the structure and dynamics of water.

Characterization and Mechanism of Gel Deterioration of Egg Yolk Powder during Storage

Egg yolk forms have several health and industrial applications, but their storage characteristics and gel mechanisms have not been thoroughly studied. In order to investigate the relationship between the changes in structure and properties of egg yolk gel and egg yolk powder during storage, in this paper, egg yolk powder was stored at 37 °C for 0, 1, 3, and 6 months in an accelerated storage experiment, and the influence of storage time on the gel properties of egg yolk powder was analyzed. The results showed that the contents of protein carbonylation and sulfhydryl in the yolk decreased gradually with the extension of storage time. Circular dichroism and fluorescence spectra showed that the ordered structure and structural stability of egg yolk proteins decreased gradually. Oxidation led to the formation of intermolecular crosslinking in the egg yolk proteins and oxidized aggregates, resulting in a decrease in surface hydrophobicity, which affected the gel properties of the egg yolk powder after rehydration, resulting in the phenomenon of lipid migration and gel degradation. The results provide a theoretical basis for improving egg yolk powder's overall quality and storage stability.

Rheological, Physical, and Spectroscopical Characterization of Gamma-Irradiated Albumin Nanoparticles Loaded with Anthocyanin

Anthocyanins are the main active compounds in blueberry. However, they have poor oxidation stability. If anthocyanins are encapsulated in protein nanoparticles, their oxidation resistance could be increased as a result of the slowing down of the oxidation process. This work describes the advantages of using a γ-irradiated bovine serum albumin nanoparticle bound to anthocyanins. The interaction was characterized biophysically, mainly by rheology. By computational calculation and simulation based on model nanoparticles, we estimated the number of molecules forming the albumin nanoparticles, which allowed us to infer the ratio of anthocyanin/nanoparticles. Measurements by UV-vis spectroscopy, FTIR spectroscopy, fluorescence spectroscopy, dynamic light scattering (DLS), ζ potential, electron transmission microscopy, and rheology at room (25 °C) and physiological (37 °C) temperatures were performed. The spectroscopy measurements allowed identifying additional hydrophobic sites created during the irradiation process of the nanoparticle. On the basis of the rheological studies, it was observed that the BSA-NP trend is a Newtonian flow behavior type for all the temperatures selected, and there is a direct correlation between dynamic viscosity and temperature values. Furthermore, when anthocyanins are added, the system increases its resistance to the flow as reflected in the morphological changes observed by TEM, thus confirming the relationship between viscosity values and aggregate formation.

Antibodies Adsorbed to the Air-Water Interface Form Soft Glasses

When monoclonal antibodies are exposed to an air-water interface, they form aggregates, which negatively impacts their performance. Until now, the detection and characterization of interfacial aggregation have been difficult. Here, we exploit the mechanical response imparted by interfacial adsorption by measuring the interfacial shear rheology of a model antibody, anti-streptavidin immunoglobulin-1 (AS-IgG1), at the air-water interface. Strong viscoelastic layers of AS-IgG1 form when the protein is adsorbed from the bulk solution. Creep experiments correlate the compliance of the interfacial protein layer with the subphase solution pH and bulk concentration. These, along with oscillatory strain amplitude and frequency sweeps, show that the viscoelastic behavior of the adsorbed layers is that of a soft glass with interfacial shear moduli on the order of 10-3 Pa m. Shifting the creep compliance curves under different applied stresses forms master curves consistent with stress-time superposition of soft interfacial glasses. The interfacial rheology results are discussed in the context of the interface-mediated aggregation of AS-IgG1.

Characterization of the physiochemical properties, microstructure, and molecular interactions of a novel rice-pea protein gel

The application of rice and pea proteins in food production is limited due to their undesirable processing performance. The objective of this research was to develop a novel rice-pea protein gel using alkali-heat treatment. This gel had a higher solubility, stronger gel strength, better water retention capacity, and denser bilayer network. This is due to the alkali-heat induced modifications for the secondary structures of proteins (i.e., a decrease in the α-helix, and an increase in the β-sheets) and the interactions between protein molecules. The network structure of gel was more compact by adding 2% and 4% alkali-heat rice protein (AH-RP). This resulted in a stable double-layer network structure of gel. Adding 4% AH-RP significantly improved the hardness and elasticity of gel. This gel will have a good potential use for being the ingredient to produce the functional foods and meat analogs.

Enhanced Thermal Stability and Reduced Aggregation in an Antibody Fab Fragment at Elevated Concentrations

The aggregation of protein therapeutics such as antibodies remains a major challenge in the biopharmaceutical industry. The present study aimed to characterize the impact of the protein concentration on the mechanisms and potential pathways for aggregation, using the antibody Fab fragment A33 as the model protein. Aggregation kinetics were determined for 0.05 to 100 mg/mL Fab A33, at 65 °C. A surprising trend was observed whereby increasing the concentration decreased the relative aggregation rate, ln(v) (% day^-1), from 8.5 at 0.05 mg/mL to 4.4 at 100 mg/mL. The absolute aggregation rate (mol L^-1 h^-1) increased with the concentration following a rate order of approximately 1 up to a concentration of 25 mg/mL. Above this concentration, there was a transition to an apparently negative rate order of -1.1 up to 100 mg/mL. Several potential mechanisms were examined as possible explanations. A greater apparent conformational stability at 100 mg/mL was observed from an increase in the thermal transition midpoint (T_m) by 7-9 °C, relative to those at 1-4 mg/mL. The associated change in unfolding entropy (△S_vh) also increased by 14-18% at 25-100 mg/mL, relative to those at 1-4 mg/mL, indicating reduced conformational flexibility in the native ensemble. Addition of Tween or the crowding agents Ficoll and dextran, showed that neither surface adsorption, diffusion limitations nor simple volume crowding affected the aggregation rate. Fitting of kinetic data to a wide range of mechanistic models implied a reversible two-state conformational switch mechanism from aggregation-prone monomers (N*) into non-aggregating native forms (N) at higher concentrations. k_D measurements from DLS data also suggested a weak self-attraction while remaining colloidally stable, consistent with macromolecular self-crowding within weakly associated reversible oligomers. Such a model is also consistent with compaction of the native ensemble observed through changes in T_m and △S_vh.

Investigating Thermally Induced Aggregation of Somatropin- New Insights Using Orthogonal Techniques

Three orthogonal techniques were used to provide new insights into thermally induced aggregation of the therapeutic protein Somatropin at pH 5.8 and 7.0. The techniques were Dynamic Light Scattering (DLS), Asymmetric Flow-Field Flow-Fractionation (AF4), and the TEM-based analysis system MiniTEM™. In addition, Differential Scanning Calorimetry (DSC) was used to study the thermal unfolding and stability. DSC and DLS were used to explain the initial aggregation process and aggregation rate at the two pH values. The results suggest that electrostatic stabilization seems to be the main reason for the faster initial aggregation at pH 5.8, i.e., closer to the isoelectric point of Somatropin. AF4 and MiniTEM were used to investigate the aggregation pathway further. Combining the results allowed us to demonstrate Somatropin's thermal aggregation pathway at pH 7.0. The growth of the aggregates appears to follow two steps. Smaller elongated aggregates are formed in the first step, possibly initiated by partly unfolded species. In the second step, occurring during longer heating, the smaller aggregates assemble into larger aggregates with more complex structures.

Effects of flexibility in coarse-grained models for bovine serum albumin and immunoglobulin G

We construct a coarse-grained, structure-based, low-resolution, 6-bead flexible model of bovine serum albumin (BSA, PDB: 4F5S), which is a popular example of a globular protein in biophysical research. The model is obtained via direct Boltzmann inversion using all-atom simulations of a single molecule, and its particular form is selected from a large pool of 6-bead coarse-grained models using two suitable metrics that quantify the agreement in the distribution of collective coordinates between all-atom and coarse-grained Brownian dynamics simulations of solutions in the dilute limit. For immunoglobulin G (IgG), a similar structure-based 12-bead model has been introduced in the literature [Chaudhri et al., J. Phys. Chem. B 116, 8045 (2012)] and is employed here to compare findings for the compact BSA molecule and the more anisotropic IgG molecule. We define several modified coarse-grained models of BSA and IgG, which differ in their internal constraints and thus account for a variation of flexibility. We study denser solutions of the coarse-grained models with purely repulsive molecules (achievable by suitable salt conditions) and address the effect of packing and flexibility on dynamic and static behavior. Translational and rotational self-diffusivity is enhanced for more elastic models. Finally, we discuss a number of effective sphere sizes for the BSA molecule, which can be defined from its static and dynamic properties. Here, it is found that the effective sphere diameters lie between 4.9 and 6.1 nm, corresponding to a relative spread of about ±10% around a mean of 5.5 nm.

An Intra-Company Analysis of Inherent Particles in Biologicals Shapes the Protein Particle Mitigation Strategy Across Development Stages

To better understand protein aggregation and inherent particle formation in the biologics pipeline at Novartis, a cross-functional team collected and analyzed historical protein particle issues. Inherent particle occurrences from the past 10 years were systematically captured in a protein particle database. Where the root cause was identified, a number of product attributes (such as development stage, process step, or protein format) were trended. Several key themes were revealed: 1) there was a higher propensity for inherent particle formation with non-mAbs than with mAbs; 2) the majority of particles were detected following manufacturing at scale, and were not predicted by the small-scale studies; 3) most issues were related to visible particles, followed by subvisible particles; 4) 50% of the issues were manufacturing related. These learnings became the foundation of a particle mitigation strategy across development and technical transfer, and resulted in a set of preventive actions. Overall, this study provides further insight into a recognized industry challenge and hopes to inspire the biopharmaceutical industry to transparently share their experiences with inherent particles formation.

Assessing and Engineering Antibody Stability Using Experimental and Computational Methods

Engineering increased stability into antibodies can improve their developability. While a range of properties need to be optimized, thermal stability and aggregation are two key factors that affect the antibody yield, purity, and specificity throughout the development and manufacturing pipeline. Therefore, an ideal goal would be to apply protein engineering methods early-on, such as in parallel to affinity maturation, to screen out potential drug molecules with the desired conformational and colloidal stability. This chapter introduces our methods to computationally characterize an antibody Fab fragment, propose stabilizing variants, and then experimentally verify these predictions.

Machine Learning Analysis Provides Insight into Mechanisms of Protein Particle Formation Inside Containers During Mechanical Agitation

Container choice can influence particle generation within protein formulations. Incompatibility between proteins and containers can manifest as increased particle concentrations, shifts in particle size distributions and changes in particle morphology distributions. In this study, flow imaging microscopy (FIM) combined with machine learning-based goodness-of-fit hypothesis testing algorithms were used in accelerated stability studies to investigate the impact of containers on particle formation. Containers in four major container categories subdivided into eleven container types were filled with monoclonal antibody formulations and agitated with and without headspace, producing subvisible particles. Digital images of the particles were recorded using flow imaging microscopy and analyzed with machine learning algorithms. Particle morphology distributions depended on container category and type, revealing differences that would not have been obvious by analysis of particle concentrations or container surface characteristics alone. Additionally, the algorithm was used to compare morphologies of particles generated in containers against those generated using isolated stresses at air-liquid and container-air-liquid interfaces. These comparisons showed that the morphology distributions of particles formed during agitation most closely resemble distributions that result from exposure of proteins to moving triple interface lines at points where container-air-liquid interfaces intersect. The approach described here can be used to identify dominant causes of particle generation due to protein-container interactions.

Amyloidogenesis via interfacial shear in a containerless biochemical reactor aboard the International Space Station

Fluid interfaces significantly influence the dynamics of protein solutions, effects that can be isolated by performing experiments in microgravity, greatly reducing the amount of solid boundaries present, allowing air-liquid interfaces to become dominant. This investigation examined the effects of protein concentration on interfacial shear-induced fibrillization of insulin in microgravity within a containerless biochemical reactor, the ring-sheared drop (RSD), aboard the international space station (ISS). Human insulin was used as a model amyloidogenic protein for studying protein kinetics with applications to in situ pharmaceutical production, tissue engineering, and diseases such as Alzheimer’s, Parkinson’s, infectious prions, and type 2 diabetes. Experiments investigated three main stages of amyloidogenesis: nucleation studied by seeding native solutions with fibril aggregates, fibrillization quantified using intrinsic fibrillization rate after fitting measured solution intensity to a sigmoidal function, and gelation observed by detection of solidification fronts. Results demonstrated that in surface-dominated amyloidogenic protein solutions: seeding with fibrils induces fibrillization of native protein, intrinsic fibrillization rate is independent of concentration, and that there is a minimum fibril concentration for gelation with gelation rate and rapidity of onset increasing monotonically with increasing protein concentration. These findings matched well with results of previous studies within ground-based analogs.

Comparison of hydrophobicity scales for predicting biophysical properties of antibodies

While antibody-based therapeutics have grown to be one of the major classes of novel medicines, some antibody development candidates face significant challenges regarding expression levels, solubility, as well as stability and aggregation, under physiological and storage conditions. A major determinant of those properties is surface hydrophobicity, which promotes unspecific interactions and has repeatedly proven problematic in the development of novel antibody-based drugs. Multiple computational methods have been devised for in-silico prediction of antibody hydrophobicity, often using hydrophobicity scales to assign values to each amino acid. Those approaches are usually validated by their ability to rank potential therapeutic antibodies in terms of their experimental hydrophobicity. However, there is significant diversity both in the hydrophobicity scales and in the experimental methods, and consequently in the performance of in-silico methods to predict experimental results. In this work, we investigate hydrophobicity of monoclonal antibodies using hydrophobicity scales. We implement several scoring schemes based on the solvent-accessibility and the assigned hydrophobicity values, and compare the different scores and scales based on their ability to predict retention times from hydrophobic interaction chromatography. We provide an overview of the strengths and weaknesses of several commonly employed hydrophobicity scales, thereby improving the understanding of hydrophobicity in antibody development. Furthermore, we test several datasets, both publicly available and proprietary, and find that the diversity of the dataset affects the performance of hydrophobicity scores. We expect that this work will provide valuable guidelines for the optimization of biophysical properties in future drug discovery campaigns.

How neutron scattering techniques benefit investigating structures and dynamics of monoclonal antibody

Over the past several decades, great progresses have been made for the pharmaceutical industry of monoclonal antibody (mAb). More and more mAb products were approved for human therapeutics. This review describes the state of art of utilizing neutron scattering to investigate mAbs, in the aspects of structures, dynamics, physicochemical stability, functionality, etc. Firstly, brief histories of mAbs and neutron scattering, as well as some basic knowledges and principles of neutron scattering were introduced. Then specific examples were demonstrated. For the structure and structural evolution investigation of in dilute and concentrated mAbs solution, in situ small angle neutron scattering (SANS) was frequently utilized. Neutron reflectometry (NR) is powerful to probe the absorption behaviors of mAbs on various surfaces and interfaces. While for dynamic investigation, quasi-elastic scattering techniques such as neutron spin echo (NSE) demonstrate the capabilities. With this review, how to utilize and take advantages of neutron scattering on investigating structures and dynamics of mAbs were demonstrated and discussed.

High-Pressure, Low-Temperature Induced Unfolding and Aggregation of Monoclonal Antibodies: Role of the Fc and Fab Fragments

The effects of high pressure and low temperature on the stability of two different monoclonal antibodies (MAbs) were examined in this work. Fluorescence and small-angle neutron scattering were used to monitor the in situ effects of pressure to infer shifts in tertiary structure and characterize aggregation prone intermediates. Partial unfolding was observed for both MAbs, to different extents, under a range of pressure/temperature conditions. Fourier transform infrared spectroscopy was also used to monitor ex situ changes in secondary structure. Preservation of native secondary structure after incubation at elevated pressures and subzero ° C temperatures was independent of the extent of tertiary unfolding and reversibility. Several combinations of pressure and temperature were also used to discern the respective contributions of the isolated Ab fragments (Fab and Fc) to unfolding and aggregation. The fragments for each antibody showed significantly different partial unfolding profiles and reversibility. There was not a simple correlation between stability of the full MAb and either the Fc or Fab fragment stabilities across all cases, demonstrating a complex relationship to full MAb unfolding and aggregation behavior. That notwithstanding, the combined use of spectroscopic and scattering techniques provides insights into MAb conformational stability and hysteresis in high-pressure, low-temperature environments.

A Descriptor set for Quantitative Structure-Property Relationship Prediction in Biologics

In addition to attaining the desired binding to their targets, a crucial aspect in the development of biotherapeutics is 'developability', which includes several desirable properties such as high solubility, low viscosity and aggregation, physico-chemical stability and low immunogenicity. The lack of any of these properties can lead to significant obstacles in advancing them to clinic; thus in silico methods capable of raising warning flags in earlier stages of development are highly beneficial. We have developed a computational framework based on a large and diverse set of protein specific descriptors ideal for making liability predictions using a machine-learning approach. This set offers a high degree of feature diversity classifiable by sequence, structure and surface patches. We assess the sensitivity and applicability of these descriptors in four dedicated case studies that are believed to be representative of biophysical characterizations commonly employed during the development process. In addition to data sets obtained from public sources, we have validated the descriptors on novel experimental data sets in order to address antibody developability and to generate prospective predictions on Adnectins. The results demonstrate that the descriptors are well suited to assist in the improvement of properties of systems that exhibit poor solubility or aggregation.

An Interlaboratory Comparison on the Characterization of a Sub-micrometer Polydisperse Particle Dispersion

The measurement of polydisperse protein aggregates and particles in biotherapeutics remains a challenge, especially for particles with diameters of ≈ 1 µm and below (sub-micrometer). This paper describes an interlaboratory comparison with the goal of assessing the measurement variability for the characterization of a sub-micrometer polydisperse particle dispersion composed of five sub-populations of poly(methyl methacrylate) (PMMA) and silica beads. The study included 20 participating laboratories from industry, academia, and government, and a variety of state-of-the-art particle-counting instruments. The received datasets were organized by instrument class to enable comparison of intralaboratory and interlaboratory performance. The main findings included high variability between datasets from different laboratories, with coefficients of variation from 13 % to 189 %. Intralaboratory variability was, on average, 37 % of the interlaboratory variability for an instrument class and particle sub-population. Drop-offs at either end of the size range and poor agreement on maximum counts of particle sub-populations were noted. The mean distributions from an instrument class, however, showed the size-coverage range for that class. The study shows that a polydisperse sample can be used to assess performance capabilities of an instrument set-up (including hardware, software, and user settings) and provides guidance for the development of polydisperse reference materials.

Relationship between the Structure and Chaperone Activity of Human αA-Crystallin after Its Modification with Diabetes-Associated Oxidative Agents and Protective Role of Antioxidant Compounds

The study was aimed to evaluate the impact of peroxynitrite (PON, oxidative stress agent in diabetes), methylglyoxal (MGO, diabetes-associated reactive carbonyl compound), and their simultaneous application on the structural and functional features of human αA-crystallin (αA-Cry) using various spectroscopy techniques. Additionally, the surface tension and oligomer size distribution of the treated and untreated protein were tested using tensiometric analysis and dynamic light scattering, respectively. Our results indicated that the reaction of PON and MGO with human αA-Cry leads to the formation of new chromophores, alterations in the secondary to quaternary protein structure, reduction in the size of protein oligomers, and significant enhancement in the chaperone activity of αA-Cry. To reverse the effects of the tested compounds, ascorbic acid and glutathione (main components of lens antioxidant defense system) were applied. As expected, the two antioxidant compounds significantly prevented formation of high molecular weight aggregates of αA-Cry (according to SDS-PAGE). Our results suggest that the lens antioxidant defense system, in particular, glutathione, may provide a strong protection against rapid incidence and progression of diabetic cataract by preventing the destructive reactions of highly reactive DM-associated metabolites.

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.

Design and development of topical liposomal formulations in a regulatory perspective

The skin is the absorption site for drug substances intended to treat loco-regional diseases, although its barrier properties limit the permeation of drug molecules. The growing knowledge of the skin structure and its physiology have supported the design of innovative nanosystems (e.g. liposomal systems) to improve the absorption of poorly skin-permeable drugs. However, despite the dozens of clinical trials started, few topically applied liposomal systems have been authorized both in the EU and the USA. Indeed, the intrinsic complexity of the topically applied liposomal systems, the higher production costs, the lack of standardized methods and the more stringent guidelines for assessing their benefit/risk balance can be seen as causes of such inefficient translation. The present work aimed to provide an overview of the physicochemical and biopharmaceutical characterization methods that can be applied to topical liposomal systems intended to be marketed as medicinal products, and the current regulatory provisions. The discussion highlights how such methodologies can be relevant for defining the critical quality attributes of the final product, and they can be usefully applied based on the phase of the life cycle of a liposomal product: to guide the formulation studies in the early stages of development, to rationally design preclinical and clinical trials, to support the pharmaceutical quality control system and to sustain post-marketing variations. The provided information can help define harmonized quality standards able to overcome the case-by-case approach currently applied by regulatory agencies in assessing the benefit/risk of the topically applied liposomal systems.

A microfluidic approach to studying the injection flow of concentrated albumin solutions

Abstract

Subcutaneous injection by means of prefilled syringes allows patients to self-administrate high-concentration (100 g/L or more) protein-based drugs. Although the shear flow of concentrated globulins or monoclonal antibodies has been intensively studied and related to the injection force proper of SC processes, very small attention has been paid to the extensional behavior of this category of complex fluids. This work focuses on the flow of concentrated bovine serum albumin (BSA) solutions through a microfluidic “syringe-on-chip” contraction device which shares some similarities with the geometry of syringes used in SC self-injection. By comparing the velocity and pressure measurements in complex flow with rheometric shear measurements obtained by means of the “Rheo-chip” device, it is shown that the extensional viscosity plays an important role in the injection process of protinaceous drugs.

Article Highlights

A microfluidic “syringe on chip” device mimicking the injection flow of protinaceous drugs has been developed.

The velocity field of concentrated BSA solutions through the “syringe on chip” is Newtonian-like.

The extensional viscosity of concentrated protein solutions should also be considered when computing injection forces through needles.

New Model to Predict the Concentration-Dependent Viscosity of Monoclonal Antibody Solutions

Concentrated monoclonal antibody solutions exhibit high solution viscosity, which is experimentally measured to be ∼1-2 orders of magnitude higher than the viscosity of water. However, physical processes responsible for the high antibody viscosity are not fully understood. We show that fluid occlusion due to the trapped solvent molecules within the boundaries formed by the aggregated antibodies is responsible for the elevated solution viscosity. We develop a theory to predict the viscosity of monoclonal antibodies based on the geometry of the antibody molecule and the aggregate morphology. We validate our theory with experiments and highlight useful insights obtained from the viscosity equation which could help in controlling the drug viscosity at the molecular design stage itself.

Long-term stability predictions of therapeutic monoclonal antibodies in solution using Arrhenius-based kinetics

Long-term stability of monoclonal antibodies to be used as biologics is a key aspect in their development. Therefore, its possible early prediction from accelerated stability studies is of major interest, despite currently being regarded as not sufficiently robust. In this work, using a combination of accelerated stability studies (up to 6 months) and first order degradation kinetic model, we are able to predict the long-term stability (up to 3 years) of multiple monoclonal antibody formulations. More specifically, we can robustly predict the long-term stability behaviour of a protein at the intended storage condition (5 °C), based on up to six months of data obtained for multiple quality attributes from different temperatures, usually from intended (5 °C), accelerated (25 °C) and stress conditions (40 °C). We have performed stability studies and evaluated the stability data of several mAbs including IgG1, IgG2, and fusion proteins, and validated our model by overlaying the 95% prediction interval and experimental stability data from up to 36 months. We demonstrated improved robustness, speed and accuracy of kinetic long-term stability prediction as compared to classical linear extrapolation used today, which justifies long-term stability prediction and shelf-life extrapolation for some biologics such as monoclonal antibodies. This work aims to contribute towards further development and refinement of the regulatory landscape that could steer toward allowing extrapolation for biologics during the developmental phase, clinical phase, and also in marketing authorisation applications, as already established today for small molecules.

Effects of Shear Rate and Protein Concentration on Amyloidogenesis via Interfacial Shear

The influence of hydrodynamics on protein fibrillization kinetics is relevant to biophysics, biochemical reactors, medicine, and disease. This investigation focused on the effects of interfacial shear on the fibrillization kinetics of insulin. Human insulin served as a model protein for studying shear-induced fibrillization with relevance to amyloid diseases such as Alzheimer's, Parkinson's, prions, and type 2 diabetes. Insulin solutions at different protein concentrations were subjected to shear flows with prescribed interfacial angular velocities using a knife-edge (surface) viscometer (KEV) operating in a laminar axisymmetric flow regime where inertia is significant. Fibrillization kinetics were quantified using intrinsic fibrillization rate and times (onset, half, and end) determined through spectroscopic measurement of monomer extinction curves and fitting to a sigmoidal function. Additionally, the occurrence of gelation was determined through macroscopic imaging and transient fibril microstructure was captured using fluorescence microscopy. The results showed that increasing interfacial shear rate produced a monotonic increase in intrinsic fibrillization rate and a monotonic decrease in fibrillization time. Protein concentration did not significantly impact the intrinsic fibrillization rate or times; however, a minimum fibril concentration for gelation was found. Protein microstructure showed increasing aggregation and plaque/cluster formation with time.

Rapid aggregation of therapeutic monoclonal antibodies by bubbling induced air/liquid interfacial and agitation stress at different conditions

Degradation of therapeutic monoclonal antibodies (mAb) due to interfacial agitation through air bubbling was investigated. Samples containing mAb in phosphate buffered saline were subjected to rapid bubbling by using a peristaltic pump at an air flow rate of 11.5 mL/min. Samples were analyzed by visual observation, UV-Vis, fluorescence, circular dichroism and infrared spectroscopy, size-exclusion chromatography (SEC), dynamic light scattering, microscopy, and cell-based activity assays. The stressed samples showed increasing turbidity with bubbling time, with mAb1 showing a protein loss of 53% in the supernatant at the latest time point (240 min), indicating formation of sub-visible and visible aggregates. Aggregate rich samples exhibited altered secondary structure and higher hydrophobicity with 40% reduction in activity. The supernatants of the stressed samples showed unchanged secondary and tertiary structure without the presence of any oligomers in SEC. Furthermore, the impact of various factors that could affect aggregation was investigated and it was found that the extent of aggregation was affected by protein concentration, sample volume, presence of surfactants, temperature, air flow rate, and presence of silicone oil. In conclusion, exposure to air/liquid interfacial stress through bubbling into liquid mAb samples effectively generated sub-visible and visible aggregates, making air bubbling an attractive approach for interfacial stress degradation studies of mAbs.

Multiscale Water Dynamics on Protein Surfaces: Protein-Specific Response to Surface Ions

Proteins function in crowded aqueous environments, interacting with a diverse range of compounds, and among them, dissolved ions. These interactions are water-mediated. In the present study, we combine field-dependent NMR relaxation (NMRD) and theory to probe water dynamics on the surface of proteins in concentrated aqueous solutions of hen egg-white lysozyme (LZM) and bovine serum albumin (BSA). The experiments reveal that the presence of salts (NaCl or NaI) leads to an opposite ion-specific response for the two proteins: an addition of salt to LZM solutions increases water relaxation rates with respect to the salt-free case, while for BSA solutions, a decrease is observed. The magnitude of the change depends on the ion identity. The developed model accounts for the non-Lorentzian shape of the NMRD profiles and reproduces the experimental data over four decades in Larmor frequency (10 kHz to 110 MHz). It is applicable up to high protein concentrations. The model incorporates the observed ion-specific effects via changes in the protein surface roughness, represented by the surface fractal dimension, and the accompanying changes in the surface water residence times. The response is protein-specific, linked to geometrical aspects of the individual protein surfaces, and goes beyond protein-independent Hofmeister-style ordering of ions.

Influence of Protein Adsorption on Aggregation in Prefilled Syringes

Protein aggregate formation in prefilled syringes (PFSs) can be influenced by protein adsorption and desorption at the solid-liquid interface. Although inhibition of protein adsorption on the PFS surface can lead to a decrease in the amount of aggregation, the mechanism underlying protein adsorption-mediated aggregation in PFSs is unclear. This study investigated protein aggregation caused by protein adsorption on silicone oil-free PFS surfaces [borosilicate glass (GLS) and cycloolefin polymer (COP)] and the factors affecting the protein adsorption on the PFS surfaces. The adsorbed proteins formed multilayered structures that consisted of two distinct types of layers: proteins adsorbed on the surface of the material and proteins adsorbed on top of the proteins on the surface. A pH-dependent electrostatic interaction was the dominant force for protein adsorption on the GLS surface, while hydrophobic effects were dominant for protein adsorption on the COP surface. When the repulsion force between proteins was weak, protein adsorption on the adsorbed protein layer was increased for both materials and as a result, protein aggregation increased. Therefore, a formulation with high colloidal stability can minimize protein adsorption on the COP surface, leading to reduced protein aggregation.