Predictive Model Building for Aggregation Kinetics Based on Molecular Dynamics Simulations of an Antibody Fragment.

Computational methods including machine learning and molecular dynamics simulations have strong potential to characterize, understand, and ultimately predict the properties of proteins relevant to their stability and function as therapeutics. Such methods would streamline the development pathway by minimizing the current experimental testing required for many protein variants and formulations. The molecular understanding of thermostability and aggregation propensity has advanced significantly along with predictive algorithms based on the sequence-level or structural-level information on a protein. However, these approaches focus largely on a comparison of protein sequence variations to correlate the properties of proteins to their stability, solubility, and aggregation propensity. For therapeutic protein development, it is of equal importance to take into account the impact of the formulation conditions to elucidate and predict the stability of the antibody drugs. At the macroscopic level, changing temperature, pH, ionic strength, and the addition of excipients can significantly alter the kinetics of protein aggregation. The mechanisms controlling aggregation kinetics have been traced back to a combination of molecular features, including conformational stability, partial unfolding to aggregation-prone states, and the colloidal stability governed by surface charges and hydrophobicity. However, very little has been done to evaluate these features in the context of protein dynamics in different formulations. In this work, we have combined a range of molecular features calculated from the Fab A33 protein sequence and molecular dynamics simulations. Using the power of advanced, yet interpretable, statistical tools, it has been possible to uncover greater insights into the mechanisms behind protein stability, validating previous findings, and also develop models that can predict the aggregation kinetics within a range of 49 different solution conditions.

Molecular Dynamics Simulations Reveal How Competing Protein-Surface Interactions for Glycine, Citrate, and Water Modulate Stability in Antibody Fragment Formulations.

The design of stable formulations remains a major challenge for protein therapeutics, particularly the need to minimize aggregation. Experimental formulation screens are typically based on thermal transition midpoints (Tm), and forced degradation studies at elevated temperatures. Both approaches give limited predictions of long-term storage stability, particularly at low temperatures. Better understanding of the mechanisms of action for formulation of excipients and buffers could lead to improved strategies for formulation design. Here, we identified a complex impact of glycine concentration on the experimentally determined stability of an antibody Fab fragment and then used molecular dynamics simulations to reveal mechanisms that underpin these complex behaviors. Tm values increased monotonically with glycine concentration, but associated ΔSvh measurements revealed more complex changes in the native ensemble dynamics, which reached a maximum at 30 mg/mL. The aggregation kinetics at 65 °C were similar at 0 and 20 mg/mL glycine, but then significantly slower at 50 mg/mL. These complex behaviors indicated changes in the dominant stabilizing mechanisms as the glycine concentration was increased. MD revealed a complex balance of glycine self-interaction, and differentially preferred interactions of glycine with the Fab as it displaced hydration-shell water, and surface-bound water and citrate buffer molecules. As a result, glycine binding to the Fab surface had different effects at different concentrations, and led from preferential interactions at low concentrations to preferential exclusion at higher concentrations. During preferential interaction, glycine displaced water from the Fab hydration shell, and a small number of water and citrate molecules from the Fab surface, which reduced the protein dynamics as measured by root-mean-square fluctuation (RMSF) on the short time scales of MD. By contrast, the native ensemble dynamics increased according to ΔSvh, suggesting increased conformational changes on longer time scales. The aggregation kinetics did not change at low glycine concentrations, and so the opposing dynamics effects either canceled out or were not directly relevant to aggregation. During preferential exclusion at higher glycine concentrations, glycine could only bind to the Fab surface through the displacement of citrate buffer molecules already favorably bound on the Fab surface. Displacement of citrate increased the flexibility (RMSF) of the Fab, as glycine formed fewer bridging hydrogen bonds to the Fab surface. Overall, the slowing of aggregation kinetics coincided with reduced flexibility in the Fab ensemble at the very highest glycine concentrations, as determined by both RMSF and ΔSvh, and occurred at a point where glycine binding displaced neither water nor citrate. These final interactions with the Fab surface were driven by mass action and were the least favorable, leading to a macromolecular crowding effect under the regime of preferential exclusion that stabilized the dynamics of Fab.

Investigation of the Solid-State Interactions in Lyophilized Human G-CSF Using Hydrogen-Deuterium Exchange Mass Spectrometry.

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) previously elucidated the interactions between excipients and proteins for liquid granulocyte colony stimulating factor (G-CSF) formulations, confirming predictions made using computational structure docking. More recently, solid-state HDX mass spectrometry (ssHDX-MS) was developed for proteins in the lyophilized state. Deuterium uptake in ssHDX-MS has been shown for various proteins, including monoclonal antibodies, to be highly correlated with storage stability, as measured by protein aggregation and chemical degradation. As G-CSF is known to lose activity through aggregation upon lyophilization, we applied the ssHDX-MS method with peptide mapping to four different lyophilized formulations of G-CSF to compare the impact of three excipients on local structure and exchange dynamics. HDX at 22 °C was confirmed to correlate well with the monomer content remaining after lyophilization and storage at -20 °C, with sucrose providing the greatest protection, and then phenylalanine, mannitol, and no excipient leading to progressively less protection. Storage at 45 °C led to little difference in final monomer content among the formulations, and so there was no discernible relationship with total deuterium uptake on ssHDX. Incubation at 45 °C may have led to a structural conformation and/or aggregation mechanism no longer probed by HDX at 22 °C. Such a conformational change was observed previously at 37 °C for liquid-formulated G-CSF using NMR. Peptide mapping revealed that tolerance to lyophilization and -20 °C storage was linked to increased stability in the small helix, loop AB, helix C, and loop CD. LC-MS HDX and NMR had previously linked loop AB and loop CD to the formation of a native-like state (N*) prior to aggregation in liquid formulations, suggesting a similar structural basis for G-CSF aggregation in the liquid and solid states.

Machine Learning Integrating Protein Structure, Sequence, and Dynamics to Predict the Enzyme Activity of Bovine Enterokinase Variants.

Despite recent advances in computational protein science, the dynamic behavior of proteins, which directly governs their biological activity, cannot be gleaned from sequence information alone. To overcome this challenge, we propose a framework that integrates the peptide sequence, protein structure, and protein dynamics descriptors into machine learning algorithms to enhance their predictive capabilities and achieve improved prediction of the protein variant function. The resulting machine learning pipeline integrates traditional sequence and structure information with molecular dynamics simulation data to predict the effects of multiple point mutations on the fold improvement of the activity of bovine enterokinase variants. This study highlights how the combination of structural and dynamic data can provide predictive insights into protein functionality and address protein engineering challenges in industrial contexts.

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 (Tm) by 7-9 °C, relative to those at 1-4 mg/mL. The associated change in unfolding entropy (△Svh) 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. kD 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 Tm and △Svh.

Elucidation of critical pH-dependent structural changes in Botulinum Neurotoxin E.

Botulinum Neurotoxins (BoNT) are the most potent toxins currently known. However, they also have therapeutic applications for an increasing number of motor related conditions due to their specificity, and low diffusion into the system. Although the start- and end- points for the BoNT mechanism of action are well-studied, a critical step remains poorly understood. It is theorised that BoNTs undergo a pH-triggered conformational shift, activating the neurotoxin by priming it to form a transmembrane (TM) channel. To test this hypothesis, we combined molecular dynamics (MD) simulations and small-angle x-ray scattering (SAXS), revealing a new conformation of serotype E (BoNT/E). This conformation was exclusively observed in simulations below pH 5.5, as determined by principal component analysis (PCA), and its theoretical SAXS profile matched an experimental SAXS profile obtained at pH 4. Additionally, a localised secondary structural change was observed in MD simulations below pH 5.5, in a region previously identified as instrumental for membrane insertion for serotype A (BoNT/A). These changes were found at a critical pH value for BoNTs in vivo, and may be relevant for their therapeutic use.

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.

NMR Reveals Functionally Relevant Thermally Induced Structural Changes within the Native Ensemble of G-CSF.

Structure-function relationships in proteins refer to a trade-off between stability and bioactivity, molded by evolution of the molecule. Identifying which protein amino acid residues jeopardize global or local stability for the benefit of bioactivity would reveal residues pivotal to this structure-function trade-off. Here, we use 15N-1H heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectroscopy to probe the microenvironment and dynamics of residues in granulocyte colony-stimulating factor (G-CSF) through thermal perturbation. From this analysis, we identified four residues (G4, A6, T133, and Q134) that we classed as significant to global stability, given that they all experienced large environmental and dynamic changes and were closely correlated to each other in their NMR characteristics. Additionally, we observe that roughly four structural clusters are subject to localized conformational changes or partial unfolding prior to global unfolding at higher temperature. Combining NMR observables with structure relaxation methods reveals that these structural clusters concentrate around loop AB (binding site III inclusive). This loop has been previously implicated in conformational changes that result in an aggregation prone state of G-CSF. Residues H43, V48, and S63 appear to be pivotal to an opening motion of loop AB, a change that is possibly also important for function. Hence, we present here an approach to profiling residues in order to highlight their potential roles in the two vital characteristics of proteins: stability and bioactivity.

Protein Engineering and HDX Identify Structural Regions of G-CSF Critical to Its Stability and Aggregation.

The protein engineering and formulation of therapeutic proteins for prolonged shelf-life remain a major challenge in the biopharmaceutical industry. Understanding the influence of mutations and formulations on the protein structure and dynamics could lead to more predictive approaches to their improvement. Previous intrinsic fluorescence analysis of the chemically denatured granulocyte colony-stimulating factor (G-CSF) suggested that loop AB could subtly reorganize to form an aggregation-prone intermediate state. Hydrogen deuterium exchange mass spectrometry (HDX-MS) has also revealed that excipient binding increased the thermal unfolding transition midpoint (Tm) by stabilizing loop AB. Here, we have combined protein engineering with biophysical analyses and HDX-MS to reveal that increased exchange in a core region of the G-CSF comprising loop AB (ABI, a small helix, ABII) and loop CD packed onto helix B and the beginning of loop BC leads to a decrease in Tm and higher aggregation rates. Furthermore, some mutations can increase the population of the aggregation-prone conformation within the native ensemble, as measured by the greater local exchange within this core region.

Solution structure of deglycosylated human IgG1 shows the role of CH2 glycans in its conformation.

The human immunoglobulin G (IgG) class is the most prevalent antibody in serum, with the IgG1 subclass being the most abundant. IgG1 is composed of two Fab regions connected to a Fc region through a 15-residue hinge peptide. Two glycan chains are conserved in the Fc region in IgG; however, their importance for the structure of intact IgG1 has remained unclear. Here, we subjected glycosylated and deglycosylated monoclonal human IgG1 (designated as A33) to a comparative multidisciplinary structural study of both forms. After deglycosylation using peptide:N-glycosidase F, analytical ultracentrifugation showed that IgG1 remained monomeric and the sedimentation coefficients s020,w of IgG1 decreased from 6.45 S by 0.16-0.27 S. This change was attributed to the reduction in mass after glycan removal. X-ray and neutron scattering revealed changes in the Guinier structural parameters after deglycosylation. Although the radius of gyration (RG) was unchanged, the cross-sectional radius of gyration (RXS-1) increased by 0.1 nm, and the commonly occurring distance peak M2 of the distance distribution curve P(r) increased by 0.4 nm. These changes revealed that the Fab-Fc separation in IgG1 was perturbed after deglycosylation. To explain these changes, atomistic scattering modeling based on Monte Carlo simulations resulted in 123,284 and 119,191 trial structures for glycosylated and deglycosylated IgG1 respectively. From these, 100 x-ray and neutron best-fit models were determined. For these, principal component analyses identified five groups of structural conformations that were different for glycosylated and deglycosylated IgG1. The Fc region in glycosylated IgG1 showed a restricted range of conformations relative to the Fab regions, whereas the Fc region in deglycosylated IgG1 showed a broader conformational spectrum. These more variable Fc conformations account for the loss of binding to the Fcγ receptor in deglycosylated IgG1.

Engineering improved ethylene production: Leveraging systems biology and adaptive laboratory evolution.

Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO2 contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene-forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including Escherichia coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate-limiting steps in biological ethylene production. We employed a combination of genome-scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to EFE (wild type versus mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges.

Coupled molecular dynamics mediate long- and short-range epistasis between mutations that affect stability and aggregation kinetics.

Multiple mutations are typically required to significantly improve protein stability or aggregation kinetics. However, when several substitutions are made in a single protein, the mutations can potentially interact in a nonadditive manner, resulting in epistatic effects, which can hamper protein-engineering strategies to improve thermostability or aggregation kinetics. Here, we have examined the role of protein dynamics in mediating epistasis between pairs of mutations. With Escherichia coli transketolase (TK) as a model, we explored the epistatic interactions between two single variants H192P and A282P, and also between the double-mutant H192P/A282P and two single variants, I365L or G506A. Epistasis was determined for several measures of protein stability, including the following: the free-energy barrier to kinetic inactivation, ∆∆G‡; thermal transition midpoint temperatures, Tm; and aggregation onset temperatures, Tagg Nonadditive epistasis was observed between neighboring mutations as expected, but also for distant mutations located in the surface and core regions of different domains. Surprisingly, the epistatic behaviors for each measure of stability were often different for any given pairwise recombination, highlighting that kinetic and thermodynamic stabilities do not always depend on the same structural features. Molecular-dynamics simulations and a pairwise cross-correlation analysis revealed that mutations influence the dynamics of their local environment, but also in some cases the dynamics of regions distant in the structure. This effect was found to mediate epistatic interactions between distant mutations and could therefore be exploited in future protein-engineering strategies.

Exploiting correlated molecular-dynamics networks to counteract enzyme activity-stability trade-off.

The directed evolution of enzymes for improved activity or substrate specificity commonly leads to a trade-off in stability. We have identified an activity-stability trade-off and a loss in unfolding cooperativity for a variant (3M) of Escherichia coli transketolase (TK) engineered to accept aromatic substrates. Molecular dynamics simulations of 3M revealed increased flexibility in several interconnected active-site regions that also form part of the dimer interface. Mutating the newly flexible active-site residues to regain stability risked losing the new activity. We hypothesized that stabilizing mutations could be targeted to residues outside of the active site, whose dynamics were correlated with the newly flexible active-site residues. We previously stabilized WT TK by targeting mutations to highly flexible regions. These regions were much less flexible in 3M and would not have been selected a priori as targets using the same strategy based on flexibility alone. However, their dynamics were highly correlated with the newly flexible active-site regions of 3M. Introducing the previous mutations into 3M reestablished the WT level of stability and unfolding cooperativity, giving a 10.8-fold improved half-life at 55 °C, and increased midpoint and aggregation onset temperatures by 3 °C and 4.3 °C, respectively. Even the activity toward aromatic aldehydes increased up to threefold. Molecular dynamics simulations confirmed that the mutations rigidified the active-site via the correlated network. This work provides insights into the impact of rigidifying mutations within highly correlated dynamic networks that could also be useful for developing improved computational protein engineering strategies.

HDX and In Silico Docking Reveal that Excipients Stabilize G-CSF via a Combination of Preferential Exclusion and Specific Hotspot Interactions.

Assuring the stability of therapeutic proteins is a major challenge in the biopharmaceutical industry, and a better molecular understanding of the mechanisms through which formulations influence their stability is an ongoing priority. While the preferential exclusion effects of excipients are well known, the additional presence and impact of specific protein-excipient interactions have proven to be more elusive to identify and characterize. We have taken a combined approach of in silico molecular docking and hydrogen deuterium exchange-mass spectrometry (HDX-MS) to characterize the interactions between granulocyte colony-stimulating factor (G-CSF), and some common excipients. These interactions were related to their influence on the thermal-melting temperatures (Tm) for the nonreversible unfolding of G-CSF in liquid formulations. The residue-level interaction sites predicted in silico correlated well with those identified experimentally and highlighted the potential impact of specific excipient interactions on the Tm of G-CSF.

Selective Stabilization and Destabilization of Protein Domains in Tissue-Type Plasminogen Activator Using Formulation Excipients.

Multidomain biotherapeutic proteins present additional behavioral and analytical challenges for the optimization of their kinetic stability by formulation. Tissue-type plasminogen activator (tPA) comprises six protein domains that exhibit a complex and pH-dependent thermal unfolding profile, due to partially independent domain unfolding. Here we have used tPA as a model for evaluating the relationships between various thermal unfolding and aggregation parameters in multidomain proteins. We show that changes in the thermal unfolding profile of tPA were parametrized by the overall thermal midpoint transition temperature, Tm, and the Van't Hoff entropy for unfolding, Δ Svh, which is a measure of unfolding cooperativity. The kinetics of degradation at 45 °C, leading to aggregation, were measured as rates of monomer and activity loss. These two rates were found to be coincident at all pH. Aggregation accelerated at pH 4 due to the early unfolding of the serine protease N-terminal domain (SP-N), whereas at pH 5-8, the fraction unfolded at 45 °C ( f45) was <1%, resulting in a baseline rate of aggregation from the native ensemble. We used a Design of Experiments (DoE) approach to evaluate how formulation excipients impact and control the thermal unfolding profile for tPA and found that the relative stability of each of the tPA domains was dependent on the formulation. Therefore, the optimization of formulations for complex multidomain proteins such as tPA may need to be multiobjective, with careful selection of the desired attributes that improve stability. As aggregation rates (ln v) correlated well to Tm ( R2 = 0.77) and Δ Svh ( R2 = 0.71) but not Tagg ( R2 = 0.01), we analyzed how formulation excipients and pH would be able to optimize Tm and Δ Svh. Formulation excipient behaviors were found to group according to their combined impact on Tm and Δ Svh. The effects of each excipient were often selectively stabilizing or destabilizing to specific tPA domains and changed the stability of particular domains relative to the others. The types of mechanism by which this could occur might involve specific interactions with the protein surface, or otherwise effects that are mediated via the solvent as a result of the different surface hydrophobicities and polarities of each domain.

Tm-Values and Unfolded Fraction Can Predict Aggregation Rates for Granulocyte Colony Stimulating Factor Variant Formulations but Not under Predominantly Native Conditions.

Protein engineering and formulation optimization strategies can be taken to minimize protein aggregation in the biopharmaceutical industry. Short-term stability measures such as the midpoint transition temperature (Tm) for global unfolding provide convenient surrogates for longer-term (e.g., 2-year) degradation kinetics, with which to optimize formulations on practical time-scales. While successful in some cases, their limitations have not been fully evaluated or understood. Tm values are known to correlate with chemical degradation kinetics for wild-type granulocyte colony stimulating factor (GCSF) at pH 4-5.5. However, we found previously that the Tm of an antibody Fab fragment only correlated with its rate of monomer loss at temperatures close to the Tm. Here we evaluated Tm, the fraction of unfolded protein (fT) at temperature T, and two additional short-term stability measures, for their ability to predict the kinetics of monomer and bioactivity loss of wild-type GCSF and four variants, at 37 °C, and in a wide range of formulations. The GCSF variants introduced one to three mutations, giving a range of conformational stabilities spanning 7.8 kcal mol-1. We determined the extent to which the formulation rank order differs across the variants when evaluated by each of the four short-term stability measures. All correlations decreased as the difference in average Tm between each pair of GCSF variants increased. The rank order of formulations determined by Tm was the best preserved, with R2-values >0.7. Tm-values also provided a good predictor (R2 = 0.73) of the aggregation rates, extending previous findings to include GCSF variant-formulation combinations. Further analysis revealed that GCSF aggregation rates at 37 °C were dependent on the fraction unfolded at 37 °C (fT37), but transitioned smoothly to a constant baseline rate of aggregation at fT37 < 10-3. A similar function was observed previously for A33 Fab formulated by pH, ionic strength, and temperature, without excipients. For GCSF, all combinations of variants and formulations fit onto a single curve, suggesting that even single mutations destabilized by up to 4.8 kcal mol-1, are insufficient to change significantly the baseline rate of aggregation under native conditions. The baseline rate of aggregation for GCSF under native conditions was 66-fold higher than that for A33 Fab, highlighting that they are a specific feature of each native protein structure, likely to be dependent on local surface properties and dynamics.

Computational Design To Reduce Conformational Flexibility and Aggregation Rates of an Antibody Fab Fragment.

Computationally guided semirational design has significant potential for improving the aggregation kinetics of protein biopharmaceuticals. While improvement in the global conformational stability can stabilize proteins to aggregation under some conditions, previous studies suggest that such an approach is limited, because thermal transition temperatures ( Tm) and the fraction of protein unfolded ( fT) tend to only correlate with aggregation kinetics where the protein is incubated at temperatures approaching the Tm. This is because under these conditions, aggregation from globally unfolded protein becomes dominant. However, under native conditions, the aggregation kinetics are presumed to be dependent on local structural fluctuations or partial unfolding of the native state, which reveal regions of high propensity to form protein-protein interactions that lead to aggregation. In this work, we have targeted the design of stabilizing mutations to regions of the A33 Fab surface structure, which were predicted to be more flexible. This Fab already has high global stability, and global unfolding is not the main cause of aggregation under most conditions. Therefore, the aim was to reduce the conformational flexibility and entropy of the native protein at various locations and thus identify which of those regions has the greatest influence on the aggregation kinetics. Highly dynamic regions of structure were identified through both molecular dynamics simulation and B-factor analysis of related X-ray crystal structures. The most flexible residues were mutated into more stable variants, as predicted by Rosetta, which evaluates the ΔΔ GND for each potential point mutation. Additional destabilizing variants were prepared as controls to evaluate the prediction accuracy and also to assess the general influence of conformational stability on aggregation kinetics. The thermal conformational stability, and aggregation rates of 18 variants at 65 °C, were each examined at pH 4, 200 mM ionic strength, under which conditions the initial wild-type protein was <5% unfolded. Variants with decreased Tm values led to more rapid aggregation due to an increase in the fraction of protein unfolded under the conditions studied. As expected, no significant improvements were observed in the global conformational stability as measured by Tm. However, 6 of the 12 stable variants led to an increase in the cooperativity of unfolding, consistent with lower conformational flexibility and entropy in the native ensemble. Three of these had 5-11% lower aggregation rates, and their structural clustering indicated that the local dynamics of the C-terminus of the heavy chain had a role in influencing the aggregation rate.

An integrated biorefinery concept for conversion of sugar beet pulp into value-added chemicals and pharmaceutical intermediates.

Over 8 million tonnes of sugar beet are grown annually in the UK. Sugar beet pulp (SBP) is the main by-product of sugar beet processing which is currently dried and sold as a low value animal feed. SBP is a rich source of carbohydrates, mainly in the form of cellulose and pectin, including d-glucose (Glu), l-arabinose (Ara) and d-galacturonic acid (GalAc). This work describes the technical feasibility of an integrated biorefinery concept for the fractionation of SBP and conversion of these monosaccharides into value-added products. SBP fractionation is initially carried out by steam explosion under mild conditions to yield soluble pectin and insoluble cellulose fractions. The cellulose is readily hydrolysed by cellulases to release Glu that can then be fermented by a commercial yeast strain to produce bioethanol at a high yield. The pectin fraction can be either fully hydrolysed, using physico-chemical methods, or selectively hydrolysed, using cloned arabinases and galacturonases, to yield Ara-rich and GalAc-rich streams. These monomers can be separated using either Centrifugal Partition Chromatography (CPC) or ultrafiltration into streams suitable for subsequent enzymatic upgrading. Building on our previous experience with transketolase (TK) and transaminase (TAm) enzymes, the conversion of Ara and GalAc into higher value products was explored. In particular the conversion of Ara into l-gluco-heptulose (GluHep), that has potential therapeutic applications in hypoglycaemia and cancer, using a mutant TK is described. Preliminary studies with TAm also suggest GluHep can be selectively aminated to the corresponding chiral aminopolyol. The current work is addressing the upgrading of the remaining SBP monomer, GalAc, and the modelling of the biorefinery concept to enable economic and Life Cycle Analysis (LCA).

The solution structures of two human IgG1 antibodies show conformational stability and accommodate their C1q and FcγR ligands.

The human IgG1 antibody subclass shows distinct properties compared with the IgG2, IgG3, and IgG4 subclasses and is the most exploited subclass in therapeutic antibodies. It is the most abundant subclass, has a half-life as long as that of IgG2 and IgG4, binds the FcγR receptor, and activates complement. There is limited structural information on full-length human IgG1 because of the challenges of crystallization. To rectify this, we have studied the solution structures of two human IgG1 6a and 19a monoclonal antibodies in different buffers at different temperatures. Analytical ultracentrifugation showed that both antibodies were predominantly monomeric, with sedimentation coefficients s20,w (0) of 6.3-6.4 S. Only a minor dimer peak was observed, and the amount was not dependent on buffer conditions. Solution scattering showed that the x-ray radius of gyration Rg increased with salt concentration, whereas the neutron Rg values remained unchanged with temperature. The x-ray and neutron distance distribution curves P(r) revealed two peaks, M1 and M2, whose positions were unchanged in different buffers to indicate conformational stability. Constrained atomistic scattering modeling revealed predominantly asymmetric solution structures for both antibodies with extended hinge structures. Both structures were similar to the only known crystal structure of full-length human IgG1. The Fab conformations in both structures were suitably positioned to permit the Fc region to bind readily to its FcγR and C1q ligands without steric clashes, unlike human IgG4. Our molecular models for human IgG1 explain its immune activities, and we discuss its stability and function for therapeutic applications.

Mapping the Aggregation Kinetics of a Therapeutic Antibody Fragment.

The analytical characterization of biopharmaceuticals is a fundamental step in the early stages of development and prediction of their behavior in bioprocesses. Protein aggregation in particular is a common issue as it affects all stages of product development. In the present work, we investigate the stability and the aggregation kinetics of A33Fab, a therapeutically relevant humanized antibody fragment at a wide range of pH, ionic strength, and temperature. We show that the propensity of A33Fab to aggregate under thermally accelerated conditions is pH and ionic-strength dependent with a stronger destabilizing effect of ionic strength at low pH. In the absence of added salts, A33Fab molecules appear to be protected from aggregation due to electrostatic colloidal repulsion at low pH. Analysis by transmission electron microscopy identified significantly different aggregate species formed at low and high pH. The correlations between apparent midpoints of thermal transitions (Tm,app values), or unfolded mole fractions, and aggregation rates are reported here to be significant only at the elevated incubation temperature of 65 °C, where aggregation from the unfolded state predominates. At all other conditions, particularly at 4-45 °C, aggregation of A33 Fab was predominantly from a native-like state, and the kinetics obeyed Arrhenius behavior. Despite this, the rank order of aggregation rates observed at 45 °C, 23 and 4 °C still did not correlate well to each other, indicating that forced degradation at elevated temperatures was not a good screen for predicting behavior at low temperature.