The Molecular Interaction Process

Native and Non-Native aggregation pathways of antibodies anticipated by cold-accelerated studies

Assessment of cold stability is essential for manufacture and commercialization of biotherapeutics. Storage stability is often estimated by measuring accelerated rates at elevated temperature and using mathematical models (as the Arrhenius equation). Although, this strategy often leads to an underestimation of protein aggregation during storage. In this work, we measured the aggregation rates of two antibodies in a broad temperature range (from 60 °C to -25 °C), using an isochoric cooling method to prevent freezing of the formulations below 0 °C. Both antibodies evidenced increasing aggregation rates when approaching extreme temperatures, because of hot and cold denaturation. This behavior was modelled using Arrhenius and Gibbs-Helmholtz equations, which enabled to deconvolute the contribution of unfolding from the protein association kinetics. This approach made possible to model the aggregation rates at refrigeration temperature (5 °C) in a relatively short timeframe (1-2 weeks) and using standard characterization techniques (SEC-HPLC and DLS).

Residue-Specific Impact of EDTA and Methionine on Protein Oxidation in Biotherapeutics Formulations Using an Integrated Biotherapeutics Drug Product Development Workflow

The rational design and selection of formulation composition to meet molecule-specific and product-specific needs are critical for biotherapeutics development to ensure physical and chemical stability. This work, based on three antibody-based (mAb) proteins (mAbA, mAbB, and mAbC), evaluates residue-specific impact of EDTA and methionine on protein oxidation, using an integrated biotherapeutics drug product development workflow. This workflow includes statistical experimental design, high-throughput experimental automation and execution, structure-based in silico modeling, inferential statistical analysis, and enhanced interactive data visualization of large datasets. This oxidation study evaluates the impact of formulation parameters including pH, protein concentration, and the presence of polysorbate 80 on the oxidation of specific conserved and variable residues of mAbs A, B, and C in the presence of stressors (iron, peroxide) and/or protectants (EDTA, L-methionine). Residue-specific analysis by automated high-throughput peptide mapping demonstrates differential residue-specific effects of EDTA and methionine in protecting against oxidation, highlighting the need for molecule-specific and product-specific selection of these excipients during formulation development. Computational modeling based on a homology model and the two-shell water coordination method (WCN) was employed to gain mechanistic understanding of residue-specific oxidation susceptibility of methionine residues. The computational determinants of local solvent exposure of methionine residues showed good correlation of WCN with experimentally determined oxidation for corresponding residues. The rapid generation of high-resolution data, statistical data analysis and interactive visualization of the high-throughput residue-level data containing ∼200 unique formulations facilitate residue-specific, molecule-specific and product-specific oxidation (global and local) assessment for oxidation protectants during early development for mAbs and related mAb-based modalities.

Blueprint for antibody biologics developability

Large-molecule antibody biologics have revolutionized medicine owing to their superior target specificity, pharmacokinetic and pharmacodynamic properties, safety and toxicity profiles, and amenability to versatile engineering. In this review, we focus on preclinical antibody developability, including its definition, scope, and key activities from hit to lead optimization and selection. This includes generation, computational and in silico approaches, molecular engineering, production, analytical and biophysical characterization, stability and forced degradation studies, and process and formulation assessments. More recently, it is apparent these activities not only affect lead selection and manufacturability, but ultimately correlate with clinical progression and success. Emerging developability workflows and strategies are explored as part of a blueprint for developability success that includes an overview of the four major molecular properties that affect all developability outcomes: 1) conformational, 2) chemical, 3) colloidal, and 4) other interactions. We also examine risk assessment and mitigation strategies that increase the likelihood of success for moving the right candidate into the clinic.

Use of Debye-Hückel-Henry charge measurements in early antibody development elucidates effects of non-specific association

The diffusion interaction parameter (kD) has been demonstrated to be a high-throughput technique for characterizing interactions between proteins in solution. kD reflects both attractive and repulsive interactions, including long-ranged electrostatic repulsions. Here, we plot the mutual diffusion coefficient (Dm) as a function of the experimentally determined Debye-Hückel-Henry surface charge (ZDHH) for seven human monoclonal antibodies (mAbs) in 15 mM histidine, pH 6. We find that graphs of Dm versus ZDHH intersect at ZDHH, ~ 2.6, independent of protein concentration. The same data plotted as kD vs. ZDHH shows a transition from net attractive to net repulsive interactions in the same region of the ZDHH intersection point. These data suggest that there is a minimum surface charge necessary on these mAbs needed to overcome attractive interactions.

Insights into the Conformation and Self-Association of a Concentrated Monoclonal Antibody using Isothermal Chemical Denaturation and Nuclear Magnetic Resonance

The purpose of this investigation was to highlight the utility of nuclear magnetic resonance (NMR) as a multi-attribute method for the characterization of therapeutic antibodies. In this case study, we compared results from isothermal chemical denaturation (ICD) and NMR with standard methods to relate conformational states of a model monoclonal antibody (mAb1) with protein-protein interactions (PPI) that lead to self - association in concentrated solutions. The increase in aggregation rate and relative viscosity for mAb1 was found to be both concentration and pH dependent. The free energy of unfolding (∆G⁰) from ICD and thermal analysis in dilute solutions indicated that although the native state predominated between pH 4 - pH 7, it was disrupted at the CH₂ and unfolded noncooperatively under acidic conditions. One-dimensional (1D) ¹H NMR and two-dimensional (2D) ¹³C-¹H NMR performed, in concentrated solutions, confirmed that PPI between pH 4-7 occurred while mAb1 was in the native state. NMR corroborated that mAb1 maintained a dominant native state at formulation-relevant conditions at the tested pH range, had increased global molecular tumbling dynamics at lower pH and confirmed increased PPI at higher pH conditions. This report aligns and compares typical characterization of an IgG1 with assessment of structure by NMR and provided a more precise assessment and deeper insight into the conformation of an IgG1 in concentrated solutions.

Nonspecific Binding-Fundamental Concepts and Consequences for Biosensing Applications

Nature achieves differentiation of specific and nonspecific binding in molecular interactions through precise control of biomolecules in space and time. Artificial systems such as biosensors that rely on distinguishing specific molecular binding events in a sea of nonspecific interactions have struggled to overcome this issue. Despite the numerous technological advancements in biosensor technologies, nonspecific binding has remained a critical bottleneck due to the lack of a fundamental understanding of the phenomenon. To date, the identity, cause, and influence of nonspecific binding remain topics of debate within the scientific community. In this review, we discuss the evolution of the concept of nonspecific binding over the past five decades based upon the thermodynamic, intermolecular, and structural perspectives to provide classification frameworks for biomolecular interactions. Further, we introduce various theoretical models that predict the expected behavior of biosensors in physiologically relevant environments to calculate the theoretical detection limit and to optimize sensor performance. We conclude by discussing existing practical approaches to tackle the nonspecific binding challenge in vitro for biosensing platforms and how we can both address and harness nonspecific interactions for in vivo systems.

Investigating photodegradation of antibodies governed by the light dosage

The present study investigated the photodegradation of three different monoclonal antibodies (mAb) by visible light. Several chromatographic techniques, such as size-exclusion and hydrophobic interaction chromatography as well as mass spectrometry were used to measure relative changes of various oxidation related monoclonal antibody species. The results show that visible light is indeed capable of inducing the formation of protein photo-oxidation products, such as acidic, basic, hydrophilic, and several other protein species with altered physicochemical properties. Although, the formation rate of degradants of these three protein species was dependent on the light source's intensity (I), their yield is clearly correlated to the applied light dosage (ld), which is defined as the product of light intensity I and irradiation time t (light dosage = I·t). Hence, our findings indicate that the degradation of monoclonal antibodies can be described according to the Bunsen-Roscoe reciprocity law. This correlation can be useful to assess the impact of photodegradation of biologics with regards to changes in light intensity and/or duration of light exposure of the protein, e.g. during the manufacturing of biologics.

Characterization and Modeling of Reversible Antibody Self-Association Provide Insights into Behavior, Prediction, and Correction

Reversible antibody self-association, while having major developability and therapeutic implications, is not fully understood or readily predictable and correctable. For a strongly self-associating humanized mAb variant, resulting in unacceptable viscosity, the monovalent affinity of self-interaction was measured in the low μM range, typical of many specific and biologically relevant protein-protein interactions. A face-to-face interaction model extending across both the heavy-chain (HC) and light-chain (LC) Complementary Determining Regions (CDRs) was apparent from biochemical and mutagenesis approaches as well as computational modeling. Light scattering experiments involving individual mAb, Fc, Fab, and Fab'2 domains revealed that Fabs self-interact to form dimers, while bivalent mAb/Fab'2 forms lead to significant oligomerization. Site-directed mutagenesis of aromatic residues identified by homology model patch analysis and self-docking dramatically affected self-association, demonstrating the utility of these predictive approaches, while revealing a highly specific and tunable nature of self-binding modulated by single point mutations. Mutagenesis at these same key HC/LC CDR positions that affect self-interaction also typically abolished target binding with notable exceptions, clearly demonstrating the difficulties yet possibility of correcting self-association through engineering. Clear correlations were also observed between different methods used to assess self-interaction, such as Dynamic Light Scattering (DLS) and Affinity-Capture Self-Interaction Nanoparticle Spectroscopy (AC-SINS). Our findings advance our understanding of therapeutic protein and antibody self-association and offer insights into its prediction, evaluation and corrective mitigation to aid therapeutic development.

A Multi-Method Approach to Assess the Self-Interaction Behavior of Infliximab

Attractive self-interaction processes in antibody formulations increase the risk of aggregation and extraordinarily elevated viscosity at high protein concentrations. These challenges affect manufacturing and application. This study aimed to understand the self-interaction process of Infliximab as a model system with pronounced attractive self-interaction. The association mechanism was studied by a multi-method approach comprising analytical ultracentrifugation, dynamic light scattering, small angle X-ray scattering, self-interaction bio-layer interferometry and hydrogen-deuterium exchange mass spectrometry. Based on our results, both Fab and Fc regions of Infliximab are involved in self-interaction. We hypothesize a mechanism based on electrostatic interactions of polar and charged residues within the identified areas of the heavy and the light chain of the mAb. The combination of fast and reliable screening methods and low throughput but high resolution methods can contribute to detailed characterization and deeper understanding of specific self-interaction processes.

Product-Specific Impact of Viscosity Modulating Formulation Excipients During Ultra-High Concentration Biotherapeutics Drug Product Development

Developing ultra-high concentration biotherapeutics drug products can be challenging due to increased viscosity, processing, and stability issues. Excipients used to alleviate these concerns are traditionally evaluated at lower protein concentrations. This study investigates whether classically known modulators of stability and viscosity at low (<50 mg/mL) to high (>50 - 150 mg/mL) protein concentrations are beneficial in ultra-high (>150 mg/mL) concentration protein formulations and drug products. This study evaluates the effect of arginine monohydrochloride, proline, and lysine monohydrochloride on viscosity and concentratability at different high and ultra-high protein concentrations using a monoclonal antibody, mAbN, formulation as a candidate protein system. The effect of excipients on the viscosity and concentratability (rate and extent) was different at high versus ultra-high protein concentrations. These results highlight that classical excipients in literature known to modulate protein interactions at low protein concentrations and reduce viscosity at high protein concentrations may need to be evaluated at target protein concentrations in a product-specific manner while developing ultra-high concentration biologics drug products.

Analysis of nonideality: insights from high concentration simulations of sedimentation velocity data

The Aviv fluorescence detection system (Aviv-FDS) has allowed the performance of sedimentation velocity experiments on therapeutic antibodies in highly concentrated environments like formulation buffers and serum. Methods were implemented in the software package SEDANAL for the analysis of nonideal, weakly associating AUC data acquired on therapeutic antibodies and proteins (Wright et al. Eur Biophys J 47:709–722, 2018, Anal Biochem 550:72–83, 2018). This involved fitting both hydrodynamic, k_s, and thermodynamic, BM₁, nonideality where concentration dependence is expressed as s = s^o/(1 + k_sc) and D = D^o(1 + 2BM₁c)/(1 + k_sc) and s^o and D^o are values extrapolated to c = 0 (mg/ml). To gain insight into the consequences of these phenomenological parameters, we performed simulations with SEDANAL of a monoclonal antibody as a function of k_s (0–100 ml/g) and BM₁ (0–100 ml/g). This provides a visual understanding of the separate and joint impact of k_s and BM₁ on the shape of high-concentration sedimentation velocity boundaries and the challenge of their unique determination by finite element methods. In addition, mAbs undergo weak self- and hetero-association (Yang et al. Prot Sci 27:1334–1348, 2018) and thus we have simulated examples of nonideal weak association over a wide range of concentrations (1–120 mg/ml). Here we demonstrate these data are best analyzed by direct boundary global fitting to models that account for k_s, BM₁ and weak association. Because a typical clinical dose of mAb is 50–200 mg/ml, these results have relevance for biophysical understanding of concentrated therapeutic proteins.

Toward Biotherapeutics Formulation Composition Engineering using Site-Identification by Ligand Competitive Saturation (SILCS)

Formulation of protein-based therapeutics employ advanced formulation and analytical technologies for screening various parameters such as buffer, pH, and excipients. At a molecular level, physico-chemical properties of a protein formulation depend on self-interaction between protein molecules, protein-solvent and protein-excipient interactions. This work describes a novel in silico approach, SILCS-Biologics, for structure-based modeling of protein formulations. SILCS Biologics is based on the Site-Identification by Ligand Competitive Saturation (SILCS) technology and enables modeling of interactions among different components of a formulation at an atomistic level while accounting for protein flexibility. It predicts potential hotspot regions on the protein surface for protein-protein and protein-excipient interactions. Here we apply SILCS-Biologics on a Fab domain of a monoclonal antibody (mAbN) to model Fab-Fab interactions and interactions with three amino acid excipients, namely, arginine HCl, proline and lysine HCl. Experiments on 100 mg/ml formulations of mAbN showed that arginine increased, lysine reduced, and proline did not impact viscosity. We use SILCS-Biologics modeling to explore a structure-based hypothesis for the viscosity modulating effect of these excipients. Current efforts are aimed at further validation of this novel computational framework and expanding the scope to model full mAb and other protein therapeutics.