Therapeutic protein aggregation: mechanisms, design, and control

High concentration formulation developability approaches and considerations

The growing need for biologics to be administered subcutaneously and ocularly, coupled with certain indications requiring high doses, has resulted in an increase in drug substance (DS) and drug product (DP) protein concentrations. With this increase, more emphasis must be placed on identifying critical physico-chemical liabilities during drug development, including protein aggregation, precipitation, opalescence, particle formation, and high viscosity. Depending on the molecule, liabilities, and administration route, different formulation strategies can be used to overcome these challenges. However, due to the high material requirements, identifying optimal conditions can be slow, costly, and often prevent therapeutics from moving rapidly into the clinic/market. In order to accelerate and derisk development, new experimental and in-silico methods have emerged that can predict high concentration liabilities. Here, we review the challenges in developing high concentration formulations, the advances that have been made in establishing low mass and high-throughput predictive analytics, and advances in in-silico tools and algorithms aimed at identifying risks and understanding high concentration protein behavior.

Determination of Conformational and Functional Stability of Potential Plague Vaccine Candidate in Formulation

Generally, protein-based vaccines are available in liquid form and are highly susceptible to instability under elevated temperature changes including freezing conditions. There is a need to create a convenient formulation of protein/peptides that can be stored at ambient conditions without loss of activity or production of adverse effects. The efficiency of naturally occurring biocompatible polymer dextran in improving the shelf-life and biological activity of a highly thermally unstable plague vaccine candidate protein called Low Calcium Response V antigen (LcrV), which can be stored at room temperature (30 ± 2 °C), has been evaluated. To determine the preferential interactions with molecular-level insight into solvent-protein interactions, analytical techniques such asspectroscopy, particle size distribution, gel electrophoresis, microscopy, and thermal analysis have been performed along with the evaluation of humoral immune response, invivo. The analytical methods demonstrate the structural stability of the LcrV protein by expressing its interaction with the excipients in the formulation. The invivo studies elicited the biological activity of the formulated antigen with a significantly higher humoral immune response (p-value = 0.047) when compared to the native, adjuvanted antigen. We propose dextran as a potential biopolymer with its co-excipient sodium chloride (NaCl) to provide protein compactness, i.e., prevent protein unfolding by molecular crowding or masking mechanism using preferential hydrophobic interaction for up to three weeks at room temperature (30 ± 2 °C).

High-Throughput Counting and Sizing of Therapeutic Protein Aggregates in the Nanometer Size Range by Nano-Flow Cytometry

Protein aggregation is one of the greatest challenges in biopharmaceuticals as it could decrease therapeutic efficacy, induce immunogenicity, and reduce shelf life of protein drugs. However, there lacks high-throughput methods than can count and size protein aggregates in the nanometer size range, especially for those smaller than 100 nm. Employing a laboratory-built nano-flow cytometer (nFCM) that enables light scattering detection of single silica nanoparticles as small as 24 nm with sizing resolution and accuracy comparable to those of electron microscopy, here, we report a new benchmark to analyze single protein aggregates as small as 40 nm. With an analysis rate of up to 10,000 particles/min, the size distribution and particle concentration of nanometer protein aggregates can be acquired in 2-3 min. Employing heat-induced aggregation of bovine serum albumin (BSA) at high concentrations as the model system, effects of different categories of excipients, including sugars, polyols, salts, and amino acids on the inhibition of protein aggregation were investigated. Strikingly enough, as high as 10¹⁰ to 10¹² particles/mL of protein aggregates were observed in the size range of 40 to 200 nm for therapeutic proteins of human serum albumin injection, reconstituted recombinant human interieukin-2 solution, and human immunoglobulin injection. nFCM opens a new avenue to count and size nanometer protein aggregates, suggesting its future usability in the quality assessment and formulation promotion of therapeutic proteins.

Biophysical studies of amorphous protein aggregation and in vivo immunogenicity

Amorphous protein aggregates are oligomers that lack specific, high-order structures. Soluble amorphous aggregates are smaller than ~1 µm. Despite their lack of high-order structure, amorphous protein aggregates exhibit specific biophysical properties such as reversibility of formation, density, conformation, and biochemical stability. Our mutational analysis using a Solubility Controlling Peptide (SCP) tag strongly suggests that amorphous aggregation of small globular proteins can significantly increase in vivo immune response and that the magnitude of enhanced immune responses depends on the aggregates' biophysical and biochemical properties. We propose that SCP tags might help develop subunit (protein) adjuvant-free (immunostimulant-free) vaccines by controlling the aggregation propensity of target proteins.

Application of Fundamental Chemical Principles for Solvation Effects: A Unified Perspective for Interaction Patterns in Solution

We demonstrate the utility of basic chemical principles like the "|Δμ| big is good" (DMB) rule for the study of solvation interactions between distinct solutes such as ions and solvents. The corresponding approach allows us to define relevant criteria for maximum solvation energies of ion pairs in different solvents in terms of electronegativities and chemical hardnesses. Our findings reveal that the DMB principle culminates into the strong and weak acids and bases concept as recently derived for specific ion effects in various solvents. The further application of the DMB approach highlights a similar condition for the chemical hardnesses with a reminiscence to the hard/soft acids and bases principle. Comparable conclusions can also be drawn with regard to the change of the solvent. We show that favorable solvent interactions are mainly driven by low chemical hardnesses as well as high electronegativity differences between the ions and the solvent. Our findings highlight that solvation interactions are governed by basic chemical principles, which demonstrates the close similarity between solvation mechanisms and chemical reactions.

Stability Convergence in Antibody Coformulations

Combined administration of antibody therapeutics has proven to be beneficial for patients with cancer or infectious diseases. As a result, there is a growing trend toward multiple antibodies premixed into a single product form and delivered to patients as a fixed-dose coformulation. However, combining antibodies into a single coformulation could be challenging as proteins have the potential to interact and alter their stability and degradation profiles in the mixture, compared to that in isolation. We show that in two specific antibody-antibody coformulations, the more stable antibody component increased the stability of the less stable component, which in return destabilized the more stable component, hence exhibiting an overall convergence of stability in the coformulation.

ATR-FTIR Biosensors for Antibody Detection and Analysis

Quality control of drug products is of paramount importance in the pharmaceutical world. It ensures product safety, efficiency, and consistency. In the case of complex biomolecules such as therapeutic proteins, small variations in bioprocess parameters can induce substantial variations in terms of structure, impacting the drug product quality. Conditions for obtaining highly reproducible grafting of 11-mercaptoundecanoic acid were determined. On that basis, we developed an easy-to-use, cost effective, and timesaving biosensor based on ATR-FTIR spectroscopy able to detect immunoglobulins during their production. A germanium crystal, used as an internal reflection element (IRE) for FTIR spectroscopy, was covalently coated with immunoglobulin-binding proteins. This thereby functionalized surface could bind only immunoglobulins present in complex media such as culture media or biopharmaceutical products. The potential subsequent analysis of their structure by ATR-FTIR spectroscopy makes this biosensor a powerful tool to monitor the production of biotherapeutics and assess important critical quality attributes (CQAs) such as high-order structure and aggregation level.

Predicting Experimental B22 Values and the Effects of Histidine Charge States for Monoclonal Antibodies Using Coarse-Grained Molecular Simulations

Static light scattering (SLS) was used to characterize five monoclonal antibodies (MAbs) as a function of total ionic strength (TIS) at pH values between 5.5 and 7.0. Second osmotic virial coefficient (B₂₂) values were determined experimentally for each MAb as a function of TIS using low protein concentration SLS data. Coarse-grained molecular simulations were performed to predict the B₂₂ values for each MAb at a given pH and TIS. To include the effect of charge fluctuations of titratable residues in the B₂₂ calculations, a statistical approach was introduced in the Monte Carlo algorithm based on the protonation probability based on a given pH value and the Henderson-Hasselbalch equation. The charged residues were allowed to fluctuate individually, based on the sampled microstates and the influence of electrostatic interactions on net protein-protein interactions during the simulations. Compared to static charge simulations, the new approach provided improved results compared to experimental B₂₂ values at pH conditions near the pK_a of titratable residues.

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.

Structure-Activity Relationship of the Dimeric and Oligomeric Forms of a Cytotoxic Biotherapeutic Based on Diphtheria Toxin

Protein aggregation is a well-recognized problem in industrial preparation, including biotherapeutics. These low-energy states constantly compete with a native-like conformation, which is more pronounced in the case of macromolecules of low stability in the solution. A better understanding of the structure and function of such aggregates is generally required for the more rational development of therapeutic proteins, including single-chain fusion cytotoxins to target specific receptors on cancer cells. Here, we identified and purified such particles as side products of the renaturation process of the single-chain fusion cytotoxin, composed of two diphtheria toxin (DT) domains and interleukin 13 (IL-13), and applied various experimental techniques to comprehensively understand their molecular architecture and function. Importantly, we distinguished soluble purified dimeric and fractionated oligomeric particles from aggregates. The oligomers are polydisperse and multimodal, with a distribution favoring lower and even stoichiometries, suggesting they are composed of dimeric building units. Importantly, all these oligomeric particles and the monomer are cystine-dependent as their innate disulfide bonds have structural and functional roles. Their reduction triggers aggregation. Presumably the dimer and lower oligomers represent the metastable state, retaining the native disulfide bond. Although significantly reduced in contrast to the monomer, they preserve some fraction of bioactivity, manifested by their IL-13RA2 receptor affinity and selective cytotoxic potency towards the U-251 glioblastoma cell line. These molecular assemblies probably preserve structural integrity and native-like fold, at least to some extent. As our study demonstrated, the dimeric and oligomeric cytotoxin may be an exciting model protein, introducing a new understanding of its monomeric counterpart’s molecular characteristics.

In-Silico Characterization of von Willebrand Factor Bound to FVIII

Factor VIII belongs to the coagulation cascade and is expressed as a long pre-protein (mature form, 2351 amino acids long). FVIII is deficient or defective in hemophilic A patients, who need to be treated with hemoderivatives or recombinant FVIII substitutes, i.e., biologic drugs. The interaction between FVIII and von Willebrand factor (VWF) influences the pharmacokinetics of FVIII medications. In vivo, full-length FVIII (FL-FVIII) is secreted in a plasma-inactive form, which includes the B domain, which is then proteolyzed by thrombin protease activity, leading to an inactive plasma intermediate. In this work, we analyzed through a computational approach the binding of VWF with two structure models of FVIII (secreted full-length with B domain, and B domain-deleted FVIII). We included in our analysis the atomic model of efanesoctocog alfa, a novel and investigational recombinant FVIII medication, in which the VWF is covalently linked to FVIII. We carried out a structural analysis of VWF/FVIII interfaces by means of protein–protein docking, PISA (Proteins, Interfaces, Structures and Assemblies), and protein contact networks (PCN) analyses. Accordingly, our computational approaches to previously published experimental data demonstrated that the domains A3-C1 of B domain-deleted FVIII (BDD-FVIII) is the preferential binding site for VWF. Overall, our computational approach applied to topological analysis of protein–protein interface can be aimed at the rational design of biologic drugs other than FVIII medications.

Differential Surface Adsorption Phenomena for Conventional and Novel Surfactants Correlates with Changes in Interfacial mAb Stabilization

Protein adsorption on surfaces can result in loss of drug product stability and efficacy during the production, storage, and administration of protein-based therapeutics. Surface-active agents (excipients) are typically added in protein formulations to prevent undesired interactions of proteins on surfaces and protein particle formation/aggregation in solution. The objective of this work is to understand the molecular-level competitive adsorption mechanism between the monoclonal antibody (mAb) and a commercially used excipient, polysorbate 80 (PS80), and a novel excipient, N-myristoyl phenylalanine-N-polyetheramine diamide (FM1000). The relative rate of adsorption of PS80 and FM1000 was studied by pendant bubble tensiometry. We find that FM1000 saturates the interface faster than PS80. Additionally, the surface-adsorbed amounts from X-ray reflectivity (XRR) measurements show that FM1000 blocks a larger percentage of interfacial area than PS80, indicating that a lower bulk FM1000 surface concentration is sufficient to prevent protein adsorption onto the air/water interface. XRR models reveal that with an increase in mAb concentration (0.5-2.5 mg/mL: IV based formulations), an increased amount of PS80 concentration (below critical micelle concentration, CMC) is required, whereas a fixed value of FM1000 concentration (above its relatively lower CMC) is sufficient to inhibit mAb adsorption, preventing mAb from co-existing with surfactants on the surface layer. With this observation, we show that the CMC of the surfactant is not the critical factor to indicate its ability to inhibit protein adsorption, especially for chemically different surfactants, PS80 and FM1000. Additionally, interface-induced aggregation studies indicate that at minimum surfactant concentration levels in protein formulations, fewer protein particles form in the presence of FM1000. Our results provide a mechanistic link between the adsorption of mAbs at the air/water interface and the aggregation induced by agitation in the presence of surfactants.

An Overview on the Recent Advances in Alternative Solvents as Stabilizers of Proteins and Enzymes

Currently, the use of alternative solvents is increasing, namely ionic liquids (ILs) and deep eutectic solvents (DESs) in diverse fields of knowledge, such as biochemistry, chemistry, chemical engineering, biotechnology and biomedicine. Particularly, when compared to traditional solvents, these alternative solvents have great importance for biomolecules due to the enhanced solubility, structure stability and the biological activity of biomolecules, such as protein and enzymes. Thus, in this review article, the recent developments and efforts on the technological developments carried out with ILs and DESs for the stabilization and activation of proteins and enzymes are provided. The most studied IL- and DES-based formulations for proteins and enzymes are discussed and the molecular mechanisms and interactions related to the increased stability promoted by these alternative solvents are disclosed, while emphasizing their main advantages.

Failure mode identification of Insulin drug products - Impact of relevant stress conditions on the quality of the drug

Fast-acting insulin drug products (DPs) are carried and administered by diabetic patients to maintain their blood glucose level throughout the day, exposing the DPs to stress conditions. Apidra, Novolog, and Humalog insulin DPs were tested under various stress conditions. Dynamic light scattering (DLS), and size exclusion chromatography (SEC) were used to monitor the stability and aggregation. Thermal stress alone did not influence the stability. However, 24 hr exposure to vigorous mechanical stress shifted the DLS size peaks of Novolog and Humalog from 5 ± 1 nm to > 50.9 ± 25.6 nm, and the SEC native protein peak areas decreased 52% for Novolog and 18.4% for Humalog. Combined stress accelerated protein aggregation more drastically. Novolog and Humalog size shifted (>75 nm) after 3 hr and the peak area decreased > 97.9% after 6 hr exposure, indicating that high temperature accelerated the aggregation triggered by agitation. Soluble aggregates were captured by DLS early on compared to SEC. Apidra was comparably stable indicating DP formulation plays a critical role in stability. Our study provides a greater understanding of potential failure modes patients and care givers may encounter while handling insulin DPs.

Discovering Novel Small Molecule Compound for Prevention of Monoclonal Antibody Self-Association

Designing an antibody with the desired affinity to the antigen is challenging, often achieved by lengthening the hydrophobic CDRs, which can lead to aggregation and cause major hindrance to the development of successful biopharmaceutical products. Aggregation can cause immunogenicity, viscosity and stability issues affecting both the safety and quality of the product. As the hydrophobic residues on the CDR are required for direct binding to antigens, it is not always possible to substitute these residues for aggregation-reduction purposes. Therefore, discovery of specific excipients to prevent aggregation is highly desirable for formulation development. Here, we used a combination of in silico screening methods to identify aggregation-prone regions on an aggregation-prone therapeutic antibody. The most aggregation-prone region on the antibody was selected to conduct virtual screening of compounds that can bind to such regions and act as an aggregation breaker. The most promising excipient candidate was further studied alongside plain buffer formulations and formulations with trehalose using coarse-grained molecular dynamics (CGMD) simulations with MARTINI force field. Mean interaction value between two antibody molecules in each formulation was calculated based on 1024 replicates of 512 ns of such CGMD simulations. Corresponding formulations with an excipient:antibody ratio of 1:5 were compared experimentally by measuring the diffusion interaction parameter k_D and accelerated stability studies. Although the compound with the highest affinity score did not show any additional protective effects compared with trehalose, this study proved using a combination of in silico tools can aid excipient design and formulation development.

Role of ionic liquids on stabilization of therapeutic proteins and model proteins

Ionic liquids (ILs) exhibit potential as excipients to stabilize proteins in solutions. This mini-review is not a detailed reference book on ILs, rather a brief overview of the main achievements published in the literature on their effect on protein aggregation, unfolding, structural and thermal stability, and activity. The main focus of the manuscript is three widely studied groups of ionic liquids: imidazolium-, cholinium- and alkylammonium-based and their effect on the model and therapeutic proteins.

Direct Cytosolic Delivery of Proteins Using Lyophilized and Reconstituted Polymer-Protein Assemblies

PURPOSE

Cytosolic delivery of proteins accesses intracellular targets for chemotherapy and immunomodulation. Current delivery systems utilize inefficient endosomal pathways of uptake and escape that lead to degradation of delivered cargo. Cationic poly(oxanorbornene)imide (PONI) polymers enable highly efficient cytosolic delivery of co-engineered proteins, but aggregation and denaturation in solution limits shelf life. In the present study we evaluate polymer-protein nanocomposite vehicles as candidates for lyophilization and point-of-care resuspension to provide a transferrable technology for cytosolic protein delivery.

METHODS

Self-assembled nanocomposites of engineered poly(glutamate)-tagged (E-tagged) proteins and guanidinium-functionalized PONI homopolymers were generated, lyophilized, and stored for 2 weeks. After reconstitution and delivery, cytosolic access of E-tagged GFP cargo (GFPE15) was assessed through diffuse cytosolic and nuclear fluorescence, and cell killing with chemotherapeutic enzyme Granzyme A (GrAE10). Efficiency was quantified between freshly prepared and lyophilized samples.

RESULTS

Reconstituted nanocomposites retained key structural features of freshly prepared assemblies, with minimal loss of material. Cytosolic delivery (> 80% efficiency of freshly prepared nanocomposites) of GFPE15 was validated in several cell lines, with intracellular access validated and quantified through diffusion into the nucleus. Delivery of GrAE10 elicited significant tumorigenic cell death. Intracellular access of cytotoxic protein was validated through cell viability.

CONCLUSION

Reconstituted nanocomposites achieved efficient cytosolic delivery of protein cargo and demonstrated therapeutic applicability with delivery of GrAE10. Overall, this strategy represents a versatile and highly translatable method for cytosolic delivery of proteins.

Recombinant antibodies aggregation and overcoming strategies in CHO cells

Mammalian cell lines are frequently used as the preferred host cells for producing recombinant therapeutic proteins (RTPs) having post-translational modified modifications similar to those observed in proteins produced by human cells. Nowadays, most RTPs approved for marketing are produced in Chinese hamster ovary (CHO) cells. Recombinant therapeutic antibodies (RTAs) are among the most important and promising RTPs for biomedical applications. A major limitation associated with the use of RTAs is their aggregation, which can be caused by a variety of factors; this results in a reduction of quality. RTA aggregations are especially concerning as they can trigger human immune responses in humans and may be fatal. Therefore, the mechanisms underlying RTA aggregation and measures for avoiding aggregation are interesting topics in RTAs research. In this review, we discuss recent progress in the field of RTAs aggregation, with a focus on factors that cause aggregation during RTA production and the development of strategies for overcoming RTA aggregation. KEY POINTS: • The recombinant antibody aggregation in mammalian cell systems is reviewed. • Intracellular environment and extracellular parameters influence recombinant antibody aggregation. • Reducing the aggregations can improve the quality of recombinant antibodies.

Ion-Mediated Morphological Diversity in Protein Amyloid Systems

Salt ions are considered among the major determinants ruling protein folding, stability, and self-assembly in the context of amyloid-related diseases, protein drug development, and functional biomaterials. Here, we report that Hofmeister ions not only determine the rate constants of the aggregation reaction for human insulin and hen egg white lysozyme but also control the generation of a plethora of amyloid-like morphologies ranging from the nanoscale to the microscale. We anticipate that the latter is a result of a balance between colloidal and conformational stability combined with an ion-specific effect and highlight the importance of salt ions in controlling the biological functions of protein aggregates.

Ion Mobility-Mass Spectrometry Reveals the Structures and Stabilities of Biotherapeutic Antibody Aggregates

Stability is a key critical quality attribute monitored throughout the development of monoclonal antibody (mAb) therapeutics. Minor changes in their higher order structure (HOS) caused by stress or environment may alter mAb aggregation, immunogenicity, and efficacy. In addition, the structures of the resulting mAb aggregates are largely unknown, as are their dependencies on conditions under which they are created. In this report, we investigate the HOS of mAb monomers and dimers under a variety of forced degradation conditions with ion mobility-mass spectrometry (IM-MS) and collision-induced unfolding (CIU) technologies. We evaluate two model IgG1 antibodies that differ significantly only in their complementarity-determinant regions: IgG1α and IgG1β. Our data covering both heat- and pH-based forced degradation conditions, aquired on two different IM-MS platforms, show that these mAbs undergo global HOS changes at both monomer and dimer levels upon degradation, but shifts in collision cross section (CCS) differ under pH or heat degradation conditions. In addition, the level of CCS change detected is different between IgG1α and IgG1β, suggesting that differences in the CDR drive differential responses to degradation that influence the antibody HOS. Dramatically different CIU fingerprints are obtained for IgG1α and IgG1β monomers and dimers for both degradation conditions. Finally, we constructed a series of computational models of mAb dimers for comparison with experimental CCS values and found evidence for a compact, overlapped dimer structure under native and heat degradation conditions, possibly adopting an inverted or nonoverlapped quaternary structure when produced through pH degredation. We conclude by discussing the potential impact of our findings on ongoing biotherapeutic discovery and development efforts.

Temperature and pH-Dependent Behaviors of mAb Drugs: A Case Study for Trastuzumab

The distortions in the high-order structure of therapeutic monoclonal antibodies (mAbs) under different environmental conditions acutely affect mAb stability, resulting in altered safety, efficacy, and shelf-life profiles. The overall stability of mAbs depends on many factors, and it requires complementary techniques for an in-depth analysis. The stability of mAbs can be characterized by differential centrifugal sedimentation (DCS), differential scanning calorimetry (DSC), differential scanning fluorimetry (DSF), and size exclusion chromatography (SEC) techniques. In this report, temperature-ramped dynamic light scattering (DLS), and circular dichroism (CD) spectroscopy were employed as complementary tools to show how temperature and pH affect the aggregation of a model mAb, trastuzumab, in solution. The results showed that the aggregation onset temperature of trastuzumab defined by DLS was 75 °C, which decreases the amount of β-sheets and causes a slight increase in helix structures. Moreover, the melting temperature of trastuzumab was determined to be between 80–83 °C by temperature-ramped CD spectrophotometry, which is in line with the Tm of trastuzumab’s Fab region tested with DSC. Thus, unfolding and aggregation of trastuzumab start simultaneously at 75 °C, and unfolding triggers the aggregation. The temperature-ramped CD and DLS methods are robust tools to determine the thermal behavior of biosimilars in various solution conditions. Their complementary usage provides solid scientific background for regulatory applications and a better understanding of mAb instability and its relationship with structural changes.

Computational models for studying physical instabilities in high concentration biotherapeutic formulations

Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

Investigation of the pH-dependent aggregation mechanisms of GCSF using low resolution protein characterization techniques and advanced molecular dynamics simulations

Granulocyte-colony stimulating factor (GCSF) is a widely used therapeutic protein to treat neutropenia. GCSF has an increased propensity to aggregate if the pH is increased above 5.0. Although GCSF is very well experimentally characterized, the exact pH-dependent aggregation mechanism of GCSF is still under debate. This study aimed to model the complex pH-dependent aggregation behavior of GCSF using state-of-the-art simulation techniques. The conformational stability of GCSF was investigated by performing metadynamics simulations, while the protein-protein interactions were investigated using coarse-grained (CG) simulations of multiple GCSF monomers. The CG simulations were directly compared with small-angle X-ray (SAXS) data. The metadynamics simulations demonstrated that the orientations of Trp residues in GCSF are dependent on pH. The conformational change of Trp residues is due to the loss of Trp-His interactions at the physiological pH, which in turn may increase protein flexibility. The helical structure of GCSF was not affected by the pH conditions of the simulations. Our CG simulations indicate that at pH 4.0, the colloidal stability may be more important than the conformational stability of GCSF. The electrostatic potential surface and CG simulations suggested that the basic residues are mainly responsible for colloidal stability as deprotonation of these residues causes a reduction of the highly positively charged electrostatic barrier close to the aggregation-prone long loop regions.

Protein aggregation and crystallization with ionic liquids: Insights into the influence of solvent properties

Ionic liquids (ILs) have been used in solvents for proteins in many applications, including biotechnology, pharmaceutics, and medicine due to their tunable physicochemical and biological properties. Protein aggregation is often undesirable, and predominantly occurs during bioprocesses, while the aggregation process can be reversible or irreversible and the aggregates formed can be native/non-native and soluble/insoluble. Recent studies have clearly identified key properties of ILs and IL-water mixtures related to protein performance, suggesting the use of the tailorable properties of ILs to inhibit protein aggregation, to promote protein crystallization, and to control protein aggregation pathways. This review discusses the critical properties of IL and IL-water mixtures and presents the latest understanding of the protein aggregation pathways and the development of IL systems that affect or control the protein aggregation process. Through this feature article, we hope to inspire further advances in understanding and new approaches to controlling protein behavior to optimize bioprocesses.

Stability assessment of FDA-approved ramucirumab monoclonal antibody; validated SE-HPLC method for degradation pattern evaluation

Ramucirumab (RAMU) is a recently US Food and Drug Administration-approved monoclonal antibody that is included in various anticancer protocols. It has a structural complexity and high degradation risk that have a significant effect on its safety and effectiveness. The major aim of this work was to assess the degradation pattern of RAMU based on physicochemical characterization. Mechanical agitation, repeated freeze-thaw cycles, pH and temperature were the selected stress conditions to which RAMU samples were subjected. The SE-HPLC method was applied and validated to monitor the RAMU monomer along with its aggregates and/or fragments. The purity of the separated peaks together with system suitability parameters were determined through the calculation of percentage purity and percentage drop in RAMU concentration. The results were interpreted by correlating them with those of dynamic light scattering and reducing and non-reducing sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Samples incubated at pH 2.0-10.0 and 37°C for up to 4 weeks were analysed, recording detection of reversed phase (RP) aggregates and low molecular weight peptide fragments. Similarly, samples under short-term storage conditions of 4 weeks at different temperatures (-20, 2-8, 25, 37 and 50°C) showed low molecular weight peptide fragments but to a lesser extent. These results highlight the alarming effect on RAMU multidose vial efficacy and safety.

Design of a Novel Fab-Like Antibody Fragment with Enhanced Stability and Affinity for Clinical use

With increasing interest in applying recombinant monoclonal antibodies (mAbs) in human medicine, engineered mAb fragments with reduced size and improved stability are in demand to overcome current limitations in clinical use. Herein, a novel Fab-like antibody fragment generated via an in silico-based engineering approach where the CH1 and CL domains of Fab are replaced by the IgG1 CH3 domains is described. This construct, designated as FabCH3, maintains the natural N-terminus and C-terminus of IgG antibody, can be expressed at a high level in bacterial cells and, importantly, exhibits much higher stability and affinity than the parental Fab when tested in a mesothelin-specific Fab m912, as well as a vascular endothelial growth factor A (VEGFA)-specific Fab Ranibizumab (in vivo). The high-resolution crystal structures of m912 FabCH3 and m912 Fab are determined, and the comparative analysis reveals more rigid structures in both constant domains and complementarity-determining regions of FabCH3, explaining its enhanced stability and affinity. Overall, the stabilized FabCH3 described in this report provides a versatile platform for engineering Fab-like antibody fragments with higher stability and antigen-binding affinity that can be used as a distinct class of antibody therapeutics.

Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics

Machine learning has been recently used to predict therapeutic antibody aggregation rates and viscosity at high concentrations (150 mg/ml). These works focused on commercially available antibodies, which may have been optimized for stability. In this study, we measured accelerated aggregation rates at 45°C and viscosity at 150 mg/ml for 20 preclinical and clinical-stage antibodies. Features obtained from molecular dynamics simulations of the full-length antibody and sequences were used for machine learning model construction. We found a k-nearest neighbors regression model with two features, spatial positive charge map on the CDRH2 and solvent-accessible surface area of hydrophobic residues on the variable fragment, gives the best performance for predicting antibody aggregation rates (r = 0.89). For the viscosity classification model, the model with the highest accuracy is a logistic regression model with two features, spatial negative charge map on the heavy chain variable region and spatial negative charge map on the light chain variable region. The accuracy and the area under precision recall curve of the classification model from validation tests are 0.86 and 0.70, respectively. In addition, we combined data from another 27 commercial mAbs to develop a viscosity predictive model. The best model is a logistic regression model with two features, number of hydrophobic residues on the light chain variable region and net charges on the light chain variable region. The accuracy and the area under precision recall curve of the classification model are 0.85 and 0.6, respectively. The aggregation rates and viscosity models can be used to predict antibody stability to facilitate pharmaceutical development.

Application of Site-Identification by Ligand Competitive Saturation in Computer-Aided Drug Design

Site Identification by Ligand Competitive Saturation (SILCS) is a molecular simulation approach that uses diverse small solutes in aqueous solution to obtain functional group affinity patterns of a protein or other macromolecule. This involves employing a combined Grand Canonical Monte Carlo (GCMC)-molecular dynamics (MD) method to sample the full 3D space of the protein, including deep binding pockets and interior cavities from which functional group free energy maps (FragMaps) are obtained. The information content in the maps, which include contributions from protein flexibilty and both protein and functional group desolvation contributions, can be used in many aspects of the drug discovery process. These include identification of novel ligand binding pockets, including allosteric sites, pharmacophore modeling, prediction of relative protein-ligand binding affinities for database screening and lead optimization efforts, evaluation of protein-protein interactions as well as in the formulation of biologics-based drugs including monoclonal antibodies. The present article summarizes the various tools developed in the context of the SILCS methodology and their utility in computer-aided drug design (CADD) applications, showing how the SILCS toolset can improve the drug-development process on a number of fronts with respect to both accuracy and throughput representing a new avenue of CADD applications.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

A computational method for predicting the aggregation propensity of IgG1 and IgG4(P) mAbs in common storage buffers

The propensity for some monoclonal antibodies (mAbs) to aggregate at physiological and manufacturing pH values can prevent their use as therapeutic molecules or delay time to market. Consequently, developability assessments are essential to select optimum candidates, or inform on mitigation strategies to avoid potential late-stage failures. These studies are typically performed in a range of buffer solutions because factors such as pH can dramatically alter the aggregation propensity of the test mAbs (up to 100-fold in extreme cases). A computational method capable of robustly predicting the aggregation propensity at the pH values of common storage buffers would have substantial value. Here, we describe a mAb aggregation prediction tool (MAPT) that builds on our previously published isotype-dependent, charge-based model of aggregation. We show that the addition of a homology model-derived hydrophobicity descriptor to our electrostatic aggregation model enabled the generation of a robust mAb developability indicator. To contextualize our aggregation scoring system, we analyzed 97 clinical-stage therapeutic mAbs. To further validate our approach, we focused on six mAbs (infliximab, tocilizumab, rituximab, CNTO607, MEDI1912 and MEDI1912_STT) which have been reported to cover a large range of aggregation propensities. The different aggregation propensities of the case study molecules at neutral and slightly acidic pH were correctly predicted, verifying the utility of our computational method.

Prediction of the Effect of pH on the Aggregation and Conditional Folding of Intrinsically Disordered Proteins with SolupHred and DispHred

Proteins microenvironments modulate their structures. Binding partners, organic molecules, or dissolved ions can alter the protein's compaction, inducing aggregation or order-disorder conformational transitions. Surprisingly, bioinformatic platforms often disregard the protein context in their modeling. In a recent work, we proposed that modeling how pH affects protein net charge and hydrophobicity might allow us to forecast pH-dependent aggregation and conditional disorder in intrinsically disordered proteins (IDPs). As these approaches showed remarkable success in recapitulating the available bibliographical data, we made these prediction methods available for the scientific community as two user-friendly web servers. SolupHred is the first dedicated software to predict pH-dependent aggregation, and DispHred is the first pH-dependent predictor of protein disorder. Here we dissect the features of these two software applications to train and assist scientists in studying pH-dependent conformational changes in IDPs.

Protocols for Rational Design of Protein Solubility and Aggregation Properties Using Aggrescan3D Standalone

Protein aggregation is a major hurdle in the development and manufacturing of protein-based therapeutics. Development of aggregation-resistant and stable protein variants can be guided by rational redesign using computational tools. Here, we describe the architecture and functionalities of the Aggrescan3D (A3D) standalone package for the rational design of protein solubility and aggregation properties based on three-dimensional protein structures. We present the case studies of the three therapeutic proteins, including antibodies, exploring the practical use of the A3D standalone tool. The case studies demonstrate that protein solubility can be easily improved by the A3D prediction of non-destabilizing amino acid mutations at the protein surfaces.

A3D 2.0 Update for the Prediction and Optimization of Protein Solubility

Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this chapter is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.

Systematic Investigation of Biocompatible Cationic Polymeric Nucleic Acid Carriers for Immunotherapy of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third-largest cause of cancer death worldwide, while immunotherapy is rapidly being developed to fight HCC with great potential. Nucleic acid drugs are the most important modulators in HCC immunotherapy. To boost the efficacy of therapeutics and amplify the efficiency of genetic materials, biocompatible polymers are commonly used. However, under the strong need of a summary for current developments of biocompatible polymeric nucleic acid carriers for immunotherapy of HCC, there is rare review article specific to this topic to our best knowledge. In this article, we will discuss the current progress of immunotherapy for HCC, biocompatible cationic polymers (BCPs) as nucleic acid carriers used (or potential) to fight HCC, the roles of biocompatible polymeric carriers for nucleic acid delivery, and nucleic acid delivery by biocompatible polymers for immunotherapy. At the end, we will conclude the review and discuss future perspectives. This article discusses biocompatible polymeric nucleic acid carriers for immunotherapy of HCC from multidiscipline perspectives and provides a new insight in this domain. We believe this review will be interesting to polymer chemists, pharmacists, clinic doctors, and PhD students in related disciplines.

Rapid and Simple Analysis of the Human Pepsin Secondary Structure Using a Portable Raman Spectrometer

Human pepsin is a digestive protease that plays an important role in the human digestive system. The secondary structure of human pepsin determines its bioactivity. Therefore, an in-depth understanding of human pepsin secondary structure changes is particularly important for the further improvement of the efficiency of human pepsin biological function. However, the complexity and diversity of the human pepsin secondary structure make its analysis difficult. Herein, a convenient method has been developed to quickly detect the secondary structure of human pepsin using a portable Raman spectrometer. According to the change of surface-enhanced Raman spectroscopy (SERS) signal intensity and activity of human pepsin at different pH values, we analyze the change of the human pepsin secondary structure. The results show that the content of the β-sheet gradually increased with the increase in the pH in the active range, which is in good agreement with circular dichroism (CD) measurements. The change of the secondary structure improves the sensitivity of human pepsin SERS detection. Meanwhile, human pepsin is a commonly used disease marker for the noninvasive diagnosis of gastroesophageal reflux disease (GERD); the detection limit of human pepsin we obtained is 2 μg/mL by the abovementioned method. The real clinical detection scenario is also simulated by spiking pepsin solution in saliva, and the standard recovery rate is 80.7-92.3%. These results show the great prospect of our method in studying the protein secondary structure and furthermore promote the application of SERS in clinical diagnosis.

Positive response to surfactants on the interfacial behavior and aggregation stability of Fab fragments from yolk immunoglobulin

The antigen binding fragment (Fab) is pepsin-digested product from egg yolk immunoglobulin (IgY), which shows lower immunogenicity and higher antibacterial activity. However, it limited the application of Fab due to the spontaneous adsorption and aggregation at the air-liquid interface. The present work is to investigate the effect of surfactants polysorbate 20 (PS20), poloxamer 188 (P188), and polyethylene glycol (PEG) on the aggregation stability of Fab of IgY. The results confirmed the positive role of surfactants in improving Fab stability. PS20 could effectively prevent the generation of Fab aggregates (DLS and light-obscuration analysis). It could also distinctly increase the internal hydrophobicity level, fortify the surface charge by altering the molecular conformational characteristics of Fab. The results of CLSM and surface tension demonstrated that P188 and PEG were co-adsorbed with Fab at the air-liquid interface and inhibited the formation of aggregation. PS20 competitively adsorbed in the gap between Fab molecules to inhibit the formation of aggregates. These findings would give an in-depth understanding of protein aggregation behavior influenced by surfactants and provide a theoretical basis for the development of functional food based on Fab active fragments.

Design for Solubility May Reveal Induction of Amide Hydrogen/Deuterium Exchange by Protein Self-Association

Structural heterogeneity often constrains the characterization of aggregating proteins to indirect or low-resolution methods, obscuring mechanistic details of association. Here, we report progress in understanding the aggregation of Adnectins, engineered binding proteins with an immunoglobulin-like fold. We rationally design Adnectin solubility and measure amide hydrogen/deuterium exchange (HDX) under conditions that permit transient protein self-association. Protein-protein binding commonly slows rates of HDX; in contrast, we find that Adnectin association may induce faster HDX for certain amides, particularly in the C-terminal β-strand. In aggregation-prone proteins, we identify a pattern of very different rates of amide HDX for residues linked by reciprocal hydrogen bonds in the native structure. These results may be explained by local loss of native structure and formation of an inter-protein interface. Amide HDX induced by self-association, detected here by deliberate modulation of propensity for such interactions, may be a general phenomenon with the potential to expose mechanisms of aggregation by diverse proteins.

Emerging Challenges and Innovations in Surfactant-mediated Stabilization of Biologic Formulations

Biologics may be subjected to various destabilizing conditions during manufacturing, transportation, storage, and use. Therefore, biologics must be appropriately formulated to meet their desired quality target product profiles. In the formulations of protein-based biologics, one critical component is surfactant. Polysorbate 80 and Polysorbate 20 remain the most commonly used surfactants. Surfactants can stabilize proteins through different mechanisms and help the proteins withstand destabilization stresses. However, the challenges associated with surfactants, for instance, impurities, degradation, and potential triggering of adverse immune responses, have been encountered. Therefore, there are continued efforts to develop novel surfactants to overcome these challenges associated with traditional surfactants. Meanwhile, surfactants have also found their use in formulations of newer and novel modalities, namely, antibody-drug conjugates, bispecific antibodies, and adeno-associated viruses (AAV). This review provides an updated in-depth discussion of surfactants in the above-mentioned areas, namely mechanism of action of surfactants, a critical review of challenges with surfactants and current mitigation approaches, and emerging technologies to develop novel surfactants. In addition, gaps, current mitigations, and future directions have been presented to trigger further discussion and research to facilitate the use and development of novel surfactants.

A comprehensive comparison between camelid nanobodies and single chain variable fragments

By the emergence of recombinant DNA technology, many antibody fragments have been developed devoid of undesired properties of natural immunoglobulins. Among them, camelid heavy-chain variable domains (VHHs) and single-chain variable fragments (scFvs) are the most favored ones. While scFv is used widely in various applications, camelid antibodies (VHHs) can serve as an alternative because of their superior chemical and physical properties such as higher solubility, stability, smaller size, and lower production cost. Here, these two counterparts are compared in structure and properties to identify which one is more suitable for each of their various therapeutic, diagnosis, and research applications.

Post-Column Denaturation-Assisted Native Size-Exclusion Chromatography-Mass Spectrometry for Rapid and In-Depth Characterization of High Molecular Weight Variants in Therapeutic Monoclonal Antibodies

The high molecular weight (HMW) size variants present in therapeutic monoclonal antibody (mAb) samples need to be closely monitored and characterized due to their impact on product safety and efficacy. Because of the complexity and often low abundances in final drug substance (DS) samples, characterization of such HMW species is challenging and traditionally requires offline enrichment of the HMW species followed by analysis using various analytical tools. Here, we report the development of a postcolumn denaturation-assisted native SEC-MS method that allows rapid and in-depth characterization of mAb HMW species directly from unfractionated DS samples. This method not only provides high-confidence identification of HMW complexes based on accurate mass measurement of both the intact assembly and the constituent subunits but also allows in-depth analysis of the interaction nature and location. In addition, using the extracted ion chromatograms, derived from high-quality, native-like mass spectra, the elution profiles of each noncovalent and/or nondissociable complex can be readily reconstructed, facilitating the comprehension of a complex HMW profile. The utility of this novel method was demonstrated in different applications, ranging from enriched HMW characterization at late stage development, comparability assessment due to process changes, and forced degradation study of coformulated mAbs. As this method does not require prior enrichment, it is thus desirable for providing both rapid and in-depth characterization of HMW species during the development of therapeutic mAbs.

Design of an Ice Recrystallization-Inhibiting Polyampholyte-Containing Graft Polymer for Inhibition of Protein Aggregation

Freezing-induced damage to proteins, through osmotic stress and ice recrystallization, during protein processing and long-term storage is a serious concern and may lead to loss of protein activity owing to denaturation. In this study, graft copolymers composed of a cryoprotective polymer (capable of preventing osmotic stress) and poly(vinyl alcohol) (PVA; known for its high ice recrystallization inhibition (IRI) property) were developed. The polymers had high IRI activity, albeit slightly lower than that of PVA alone, but substantially higher than that of succinylated ε-poly-l-lysine (PLLSA) alone. The graft polymers showed an efficiency higher than that of PVA or PLLSA alone in protecting proteins from multiple freeze-thaw cycles, as well as during prolonged freezing, indicating a synergy between PVA and PLLSA. The PLLSA-based graft polymer is a promising material for use in protein biopharmaceutics for the long-term storage of proteins under freezing conditions.

Rational Design of Protein-Specific Folding Modifiers

Protein-folding can go wrong in vivo and in vitro, with significant consequences for the living organism and the pharmaceutical industry, respectively. Here we propose a design principle for small-peptide-based protein-specific folding modifiers. The principle is based on constructing a "xenonucleus", which is a prefolded peptide that mimics the folding nucleus of a protein. Using stopped-flow kinetics, NMR spectroscopy, Förster resonance energy transfer, single-molecule force measurements, and molecular dynamics simulations, we demonstrate that a xenonucleus can make the refolding of ubiquitin faster by 33 ± 5%, while variants of the same peptide have little or no effect. Our approach provides a novel method for constructing specific, genetically encodable folding catalysts for suitable proteins that have a well-defined contiguous folding nucleus.

Differences in human IgG1 and IgG4 S228P monoclonal antibodies viscosity and self-interactions: Experimental assessment and computational predictions of domain interactions

Human/humanized IgG4 antibodies have reduced effector function relative to IgG1 antibodies, which is desirable for certain therapeutic purposes. However, the developability and biophysical properties for IgG4 antibodies are not well understood. This work focuses on the head-to-head comparison of key biophysical properties, such as self-interaction and viscosity, for 14 human/humanized, and chimeric IgG1 and IgG4 S228P monoclonal antibody pairs that contain the identical variable regions. Experimental measurements showed that the IgG4 S228P antibodies have similar or higher self-interaction and viscosity than that of IgG1 antibodies in 20 mM sodium acetate, pH 5.5. We report sequence and structural drivers for the increased viscosity and self-interaction detected in IgG4 S228P antibodies through a combination of experimental data and computational models. Further, we applied and extended a previously established computational model for IgG1 antibodies to predict the self-interaction and viscosity behavior for each antibody pair, providing insight into the structural characteristics and differences of these two isotypes. Interestingly, we observed that the IgG4 S228P swapped variants, where the CH3 domain was swapped for that of an IgG1, showed reduced self-interaction behavior. These domain swapped IgG4 S228P molecules also showed reduced viscosity from experiment and coarse-grained simulations. We also observed that experimental diffusion interaction parameter (kD) values have a high correlation with computational diffusivity prediction for both IgG1 and IgG4 S228P isotypes.

Abbreviations: AHc, constant region Hamaker constant; AHv, variable region Hamaker constant; CDRs, Complementarity-determining regions; CG, Coarse-grained model; CH1, Constant heavy chain 1; CH2 Constant heavy chain 2; CH3 Constant heavy chain 3; chgCH3 Effective charge on the CH3 region; CL Constant light chain; cP, Centipoise; DLS, Dynamic light scattering; Fab, Fragment antigen-binding; Fc, Fragment crystallizable; Fv, Variable domaing; (r) Radial distribution function; H1 CDR1 of Heavy Chain; H2 CDR2 of Heavy Chain; H3 CDR3 of Heavy Chain; HVI, High viscosity index; IgG1 human immunoglobulin of IgG1 subclass; IgG4 human immunoglobulin of IgG4 subclass; kD, Diffusion interaction parameter; L1 CDR1 of Light Chain; L2 CDR2 of Light Chain; L3 CDR3 of Light Chain; mAb, Monoclonal antibody; MD, Molecular dynamics; PPI Protein–protein interactions; SCM, Spatial charge map; UP-SEC, Ultra-high-performance size-exclusion chromatography; VH, Variable domain of Heavy Chain; VL, Variable domain of Light Chain

Protein Structural Denaturation Evaluated by MCR-ALS of Protein Microarray FTIR Spectra

The loss of native structure is common in proteins. Among others, aggregation is one structural modification of particular importance as it is a major concern for the efficiency and safety of biotherapeutic proteins. Yet, recognizing the structural features associated with intermolecular bridging in a high-throughput manner remains a challenge. We combined here the use of protein microarrays spotted at a density of ca 2500 samples per cm² and Fourier transform infrared (FTIR) imaging to analyze structural modifications in a set of 85 proteins characterized by widely different secondary structure contents, submitted or not to mild denaturing conditions. Multivariate curve resolution alternating least squares (MCR-ALS) was used to model a new spectral component appearing in the protein set subject to denaturing conditions. In the native protein set, 6 components were found to be sufficient to obtain good modeling of the spectra. Furthermore, their shape allowed them to be assigned to α-helix, β-sheet, and other structures. Their content in each protein was correlated with the known secondary structure, confirming these assignments. In the denatured proteins, a new component was necessary and modeled by MCR-ALS. This new component could be assigned to the intermolecular β-sheet, bridging protein molecules. MCR-ALS, therefore, unveiled a potential spectroscopic marker of protein aggregation and allowed a semiquantitative evaluation of its content. Insight into other structural rearrangements was also obtained.

Challenges for design of aggregation-resistant variants of granulocyte colony-stimulating factor

Non-native protein aggregation is a long-standing issue in pharmaceutical biotechnology. A rational design approach was used in order to identify variants of recombinant human granulocyte colony-stimulating factor (rhG-CSF) with lower aggregation propensity at solution conditions that are typical of commercial formulation. The approach used aggregation-prone-region (APR) predictors to select single amino acid substitutions that were predicted to decrease intrinsic aggregation propensity (IAP). The results of static light scattering temperature-ramps and chemical unfolding experiments demonstrated that none of the selected variants exhibited improved aggregation resistance, and the apparent conformational stability of each variant was lower than that of WT. Aggregation studies under partly denaturing conditions suggested that the IAP of at least one variant remained unaltered. Overall, this study highlights a general challenge in designing aggregation resistance for proteins, due to the need to accurately predict both APRs and conformational stability.

The Protein Folding Problem: The Role of Theory

The protein folding problem was first articulated as question of how order arose from disorder in proteins: How did the various native structures of proteins arise from interatomic driving forces encoded within their amino acid sequences, and how did they fold so fast? These matters have now been largely resolved by theory and statistical mechanics combined with experiments. There are general principles. Chain randomness is overcome by solvation-based codes. And in the needle-in-a-haystack metaphor, native states are found efficiently because protein haystacks (conformational ensembles) are funnel-shaped. Order-disorder theory has now grown to encompass a large swath of protein physical science across biology.