Molecular level insight into intra-solvent interaction effects on protein stability and aggregation

Polyphosphate as a novel aggregation suppressor of gamma globulin

The aggregation of gamma globulin poses a significant challenge in maintaining the quality of biopharmaceutical products. This study aimed to develop a novel approach to prevent gamma globulin aggregation using polyphosphates (PolyPs), linear polymers comprising 14 to 130 phosphate units. The addition of PolyPs effectively suppressed the formation of subvisible particles (SVPs) in the micrometer-sized fraction of bovine gamma globulin (BGG) during storage at 40 °C, as observed through flow imaging. Furthermore, PolyPs mitigated the decrease in soluble protein concentration under these conditions. Mass photometry and isothermal titration calorimetry revealed that PolyPs spontaneously form complexes with BGG. The negative zeta potential and positive B22 and kDiff values suggested that the BGG-PolyP complexes were stabilized by electrostatic repulsion. Importantly, far-UV circular dichroism confirmed that the secondary structure of BGG remained unaffected by complexation with PolyPs. Notably, arginine-a commonly used aggregation suppressor-failed to prevent the formation of SVPs in BGG under similar conditions. This study demonstrates the potential of biocompatible and stable PolyPs as a novel additive for inhibiting gamma globulin aggregation, offering a promising alternative to conventional approaches.

Flipping out: role of arginine in hydrophobic interactions and biological formulation design

Arginine has been a mainstay in biological formulation development for decades. To date, the way arginine modulates protein stability has been widely studied and debated. Here, we employed a hydrophobic polymer to decouple hydrophobic effects from other interactions relevant to protein folding. While existing hypotheses for the effects of arginine can generally be categorized as either direct or indirect, our results indicate that direct and indirect mechanisms of arginine co-exist and oppose each other. At low concentrations, arginine was observed to stabilize hydrophobic polymer folding via a sidechain-dominated direct mechanism, while at high concentrations, arginine stabilized polymer folding via a backbone-dominated indirect mechanism. Upon introducing partially charged polymer sites, arginine destabilized polymer folding. Further, we found arginine-induced destabilization of a model virus similar to direct-mechanism destabilization of the charged polymer and concentration-dependent stabilization of a model protein similar to the indirect mechanism of hydrophobic polymer stabilization. These findings highlight the modular nature of the widely used additive arginine, with relevance in the information-driven design of stable biological formulations.

Whole process of Fab antibody aggregation in intestinal environment and their aggregation regulation: An insight from static and concentration perturbation aggregations

This work revealed the aggregation and aggregation inhibition mechanisms of Fab antibody in a simulated intestinal fluid via static and concentration perturbation aggregations to meet the challenges of oral antibody therapy. Results showed that Fab aggregation was highly concentration dependent, mainly determined by the β-sheet's stacking and amyloid fibers' extension at low (1 mg/mL) and the twine of β-strands' turn at high (20 mg/mL) concentrations. During the incubation of 0-240 min, Fab was continuously aggregating, but with some rearrangements on its spatial conformation: α-helix and β-sheet formation with β-turn and random coil unfolding, which expanded the aggregates' hydrophobic core and extended β-sheet structure through the π-π stacking of aromatic amino acids. The aggregation kinetics indicated that high Fab concentrations promoted high aggregates but the growth of amyloid fibers took a long time, while low to high concentration fluctuation promoted the formation of Fab aggregates. Molecular docking and molecular dynamics simulations suggested that Arg, PEG 10000, and Poloxamer 188 reduced the potential energy; PEG 10000 and Tween 20 enhanced steric hindrance by spontaneously binding through competitive hydrogen bonding without disturbing Fab's conformation. This work can provide promising approaches for our daily health management by facilitating the materialization of Fab-based oral antibody therapy.

Sweet corn phytoglycogen dendrimers as a lyoprotectant for dry-state protein storage

Protein biotherapeutics typically require expensive cold-chain storage to maintain their fold and function. Packaging proteins in the dry state via lyophilization can reduce these cold-chain requirements. However, formulating proteins for lyophilization often requires extensive optimization of excipients that both maintain the protein folded state during freezing and drying (i.e., "cryoprotection" and "lyoprotection"), and form a cake to carry the dehydrated protein. Here we show that sweet corn phytoglycogens, which are glucose dendrimers, can act as both a protein lyoprotectant and a cake-forming agent. Phytoglycogen (PG) dendrimers from 16 different maize sources (PG1-16) were extracted via ethanol precipitation. PG size was generally consistent at ~70-100 nm for all variants, whereas the colloidal stability in water, protein contaminant level, and maximum density of cytocompatibility varied for PG1-16. 10 mg/mL PG1, 2, 9, 13, 15, and 16 maintained the activity of various proteins, including green fluorescent protein, lysozyme, β-galactosidase, and horseradish peroxidase, over a broad range of concentrations, through multiple rounds of lyophilization. PG13 was identified as the lead excipient candidate as it demonstrated narrow dispersity, colloidal stability in phosphate-buffered saline, low protein contaminants, and cytocompatibility up to 10 mg/mL in NIH3T3 cell cultures. All dry protein-PG13 mixtures had a cake-like appearance and all frozen protein-PG13 mixtures had a Tg' of ~ -26°C. The lyoprotection and cake-forming properties of PG13 were density-dependent, requiring a minimum density of 5 mg/mL for maximum activity. Collectively these data establish PG dendrimers as a new class of excipient to formulate proteins in the dry state.

Unraveling the Molecular Jam: How Crowding Shapes Protein Aggregation in Neurodegenerative Disorders

Protein misfolding and aggregation are the hallmarks of neurodegenerative diseases including Huntington's disease, Parkinson's disease, Alzheimer's disease, and prion diseases. A crowded cellular environment plays a crucial role in modulating protein aggregation processes in vivo and the pathological aggregation of proteins linked to different neurodegenerative disorders. Here, we review recent studies examining the effects of various crowding agents, such as polysaccharides, polyethylene glycol, and proteins like BSA and lysozyme on the behaviors of aggregation of several amyloidogenic peptides and proteins, including amylin, huntingtin, tau, α-synuclein, prion, and amyloid-β. We also summarize how the aggregation kinetics, thermodynamic stability, and morphology of amyloid fibrils are altered significantly in the presence of crowding agents. In addition, we also discuss the molecular basis underlying the modulation of amyloidogenic aggregation, focusing on changes in the protein conformation, and the nucleation mechanism. The molecular understanding of the effects of macromolecular crowding on amyloid aggregation is essential for revealing disease pathologies and identifying possible therapeutic targets. Thus, this review offers a perspective on the complex interplay between protein aggregation and the crowded cellular environment in vivo and explains the relevance of crowding in the context of neurodegenerative disorders.

Mathematical modeling of optimal coagulant dosage for tofu preparation using MgCl2

To explore the association between the optimal coagulant for tofu and the components of soybeans,30 different kinds of soybeans were selected, and tested for their optimal coagulant MgCl2 content. The optimal amount of coagulant was taken as the dependent variable, and the soybean Composition were taken as independent variables for the correlation analysis. The results showed that there was a positive correlation between the optimal coagulant content and the content of histidine, 7S β-conglycinin, B1aB1bB2B3B4 of 11 s glycincin, and α'-subunit of 7S β-conglycinin, negative correlation with lysine. The regression formula is y = -1.186 + 3.457*B1aB1bB2B3B4 + 2.304*7S + 0.351*histidine - 0.084*lysine + 4.696*α', and the model is validated to be within 10 % of the error value and has a high degree of confidence. This study provides theoretical support for realizing the green production of traditional soybean products.

Effects of Amino Acid Additives on Protein Stability during Electrothermal Supercharging in ESI-MS

The surprising formation of highly charged protein ions from aqueous ammonium bicarbonate solution is a fascinating phenomenon referred to as electrothermal supercharging (ETS). Although the precise mechanism involved is not clearly understood, previous studies predominantly suggest that ETS is due to native protein destabilization in the presence of bicarbonate anion inside the electrospray ionization droplets under high temperatures and spray voltages. To evaluate existing hypotheses surrounding the underlying mechanism of ETS, the effects of several additives on protein charging under ETS conditions were investigated. The changes in the protein charge state distributions were compared by measuring the ratios between the intensities of highest intensity charge states of native and unfolded protein envelopes and shifts in the lowest and highest observed charge states. This study demonstrated that source temperature plays a more important role in ETS compared to spray voltage, especially when using a nebulized microelectrospray ionization source. Moreover, the effect of amino acids on ETS were generally in good agreement with the extensive literature available on the stabilization or destabilization of proteins by these additives in bulk solution. Among the natural amino acids, protein supercharging was significantly reduced by proline and glycine; however, imidazole provided the highest degree of noncovalent complex stabilization against ETS, outperforming the amino acids. Overall, our study shows that the simple addition of stabilizing reagents such as proline and imidazole can reduce the extent of apparent protein unfolding and supercharging in ammonium bicarbonate solution and provide evidence against the roles of charge depletion and thermal unfolding during ETS.

Structure of Cellulose Ether Affected by Ionic Surfactant and Solvent: A Small-Angle Neutron Scattering Investigation

Polysaccharides and their derivatives are commonly used in pharmaceutical and agricultural formulations as rheology modifiers. Their performance is related to their conformation in solution, which in turn is affected by other ingredients present in the formulation. This study focuses on modulating the conformation of relatively rigid cellulose chains in aqueous solutions. In particular, we have investigated the nonionic cellulose derivative ethyl(hydroxyethyl)cellulose (EHEC) in water in the presence of the ionic surfactant sodium dodecyl sulfate (SDS) and/or ethanol acting as modulating agents. We have used small angle neutron scattering (SANS) with contrast variation to determine the EHEC chain conformation in the presence of (but not masked by) ethanol and SDS. In dilute and semidilute aqueous solutions, EHEC exhibits worm-like chain conformation due to the rigid cellulose backbone. Addition of ethanol does not impact the polymer conformation to a great extent. Addition of SDS alters the EHEC chain conformation, resulting in polyelectrolyte-like scattering behavior due to repulsive interactions between bound charged micelles which show similar structure as the free SDS micelles in solution (in the absence of polymers). Ethanol affects the polymer + surfactant system primarily by acting on the surfactant (bound on polymer) which, in turn, affects the polymer conformation. At higher ethanol concentrations (20 wt %), EHEC regains the worm-like chain conformation because of the detachment of the bound SDS micelles. To the best of our knowledge, this is the only study providing details on chain conformation of the rigid polymer EHEC in dilute or semidilute aqueous solutions in the presence of surfactant and alcohol and one of very few papers utilizing SANS for the characterization of polymer + surfactant + water + alcohol interactions. Such fundamental understanding of interactions and structure in multicomponent mixtures supports the design of industrial formulations.

Ultrasensitive Detection of Aqueous Uranyl Based on Uranyl-Triggered Protein Photocleavage

The detection of environmental uranyl is attracting increasing attention. However, the available detection strategies mainly depend on the selective recognition of uranyl, which is subject to severe interference by coexisting metal ions. Herein, based on the unique uranyl-triggered photocleavage property, the protein BSA is labelled with fluorescent molecules that exhibit an aggregation-induced emission effect for uranyl detection. Uranyl-triggered photocleavage causes the separation of the fluorescent-molecule-labelled protein fragments, leading to attenuation of the emission fluorescence, which is used as a signal for uranyl detection. This detection strategy shows high selectivity for uranyl and an ultralow detection limit of 24 pM with a broad detection range covering five orders of magnitude. The detection method also shows high reliability and stability, making it a promising technique for practical applications in diverse environments.

Predicting the Activities of Drug Excipients on Biological Targets using One-Shot Learning

Excipients are major components of drugs and are used to improve drug attributes such as stability and appearance. Excipients approved by the U.S. Food and Drug Administration (FDA) are regarded as safe for humans in allowed concentrations, but their potential interactions with drug targets have not been investigated systematically, which might influence a drug's efficacy. Deep learning models have been used for the identification of ligands that could bind to the drug targets. However, due to the limited available data, it is challenging to reliably estimate the likelihood of a ligand-protein interaction. One-shot learning techniques provide a potential approach to address this low data problem as these techniques require only one or a few examples to classify the new data. In this study, we apply one-shot learning models to data sets that include ligands binding to G-protein-coupled receptors (GPCRs) and kinases. The predicted results suggest that one-shot learning could be used for predicting ligand-protein interactions, and the models attain better performance when protein targets contain conserved binding pockets. The trained models are also used to predict interactions between excipients and drug targets, which provides a potential efficient strategy to explore the activities of drug excipients. We find that a large number of drug excipients could interact with biological targets and influence their function. The results demonstrate how one-shot learning can be used to make accurate predictions for excipient-protein interactions, and these methods could be used for selecting excipients with limited drug-protein interactions.

Effects of amino acid additives on protein solubility - insights from desorption and direct electrospray ionization mass spectrometry

Naturally occurring amino acids have been broadly used as additives to improve protein solubility and inhibit aggregation. In this study, improvements in protein signal intensity obtained with the addition of L-serine, and structural analogs, to the desorption electrospray ionization mass spectrometry (DESI-MS) spray solvent were measured. The results were interpreted at the hand of proposed mechanisms of solution additive effects on protein solubility and dissolution. DESI-MS allows for these processes to be studied efficiently using dilute concentrations of additives and small amounts of proteins, advantages that represent real benefits compared to classical methods of studying protein stability and aggregation. We show that serine significantly increases the protein signal in DESI-MS when native proteins are undergoing unfolding during the dissolution process with an acidic solvent system (p-value = 0.0001), or with ammonium bicarbonate under denaturing conditions for proteins with high isoelectric points (p-value = 0.001). We establish that a similar increase in the protein signal cannot be observed with direct ESI-MS, and the observed increase is therefore not related to ionization processes or changes in the physical properties of the bulk solution. The importance of the presence of serine during protein conformational changes while undergoing dissolution is demonstrated through comparisons between the analyses of proteins deposited in native or unfolded states and by using native state-preserving and denaturing desorption solvents. We hypothesize that direct, non-covalent interactions involving all three functional groups of serine are involved in the beneficial effect on protein solubility and dissolution. Supporting evidence for a direct interaction include a reduction in efficacy with D-serine or the racemic mixture, indicating a non-bulk-solution physical property effect; insensitivity to the sample surface type or relative placement of serine addition; and a reduction in efficacy with any modifications to the serine structure, most notably the carboxyl functional group. An alternative hypothesis, also supported by some of our observations, could involve the role of serine clusters in the mechanism of solubility enhancement. Our study demonstrates the capability of DESI-MS together with complementary ESI-MS experiments as a novel tool for understanding protein solubility and dissolution and investigating the mechanism of action for solubility-enhancing additives.

Understanding molecular mechanisms of biologics drug delivery and stability from NMR spectroscopy

Protein therapeutics carry inherent limitations of membrane impermeability and structural instability, despite their predominant role in the modern pharmaceutical market. Effective formulations are needed to overcome physiological and physicochemical barriers, respectively, for improving bioavailability and stability. Knowledge of membrane affinity, cellular internalization, encapsulation, and release of drug-loaded carrier vehicles uncover the structural basis for designing and optimizing biopharmaceuticals with enhanced delivery efficiency and therapeutic efficacy. Understanding stabilizing and destabilizing interactions between protein drugs and formulation excipients provide fundamental mechanisms for ensuring the stability and quality of biological products. This article reviews the molecular studies of biologics using solution and solid-state NMR spectroscopy on structural attributes pivotal to drug delivery and stability. In-depth investigation of the structure-function relationship of drug delivery systems based on cell-penetrating peptides, lipid nanoparticles and polymeric colloidal, and biophysical and biochemical stability of peptide, protein, monoclonal antibody, and vaccine, as the integrative efforts on drug product design, will be elaborated.

Spray-Dried Inhalable Powder Formulations of Therapeutic Proteins and Peptides

Respiratory diseases are among the leading causes of morbidity and mortality worldwide. Innovations in biochemical engineering and understanding of the pathophysiology of respiratory diseases resulted in the development of many therapeutic proteins and peptide drugs with high specificity and potency. Currently, protein and peptide drugs are mostly administered by injections due to their large molecular size, poor oral absorption, and labile physicochemical properties. However, parenteral administration has several limitations such as frequent dosing due to the short half-life of protein and peptide in blood, pain on administration, sterility requirement, and poor patient compliance. Among various noninvasive routes of administrations, the pulmonary route has received a great deal of attention and is a better alternative to deliver protein and peptide drugs for treating respiratory diseases and systemic diseases. Among the various aerosol dosage forms, dry powder inhaler (DPI) systems appear to be promising for inhalation delivery of proteins and peptides due to their improved stability in solid state. This review focuses on the development of DPI formulations of protein and peptide drugs using advanced spray drying. An overview of the challenges in maintaining protein stability during the drying process and stabilizing excipients used in spray drying of proteins and peptide drugs is discussed. Finally, a summary of spray-dried DPI formulations of protein and peptide drugs, their characterization, various DPI devices used to deliver protein and peptide drugs, and current clinical status are discussed.

Interfacial Properties of β-Lactoglobulin at the Oil/Water Interface: Influence of Starch Conversion Products with Varying Dextrose Equivalents

In spray dried emulsions, frequently milk proteins are used as interfacial active components and starch conversion products are added as matrix material at high concentrations. To characterize interfacial properties at the oil/water interface by commonly applied methods, low protein, and carbohydrate concentrations from 1 to 2% are usually analyzed. The impact of a higher concentration of starch conversion products was not investigated so far. Therefore, the formation and rheological properties of β-lactoglobulin (β-LG) stabilized films at the oil/water interface were investigated via short and long-time adsorption behavior using pendant drop tensiometry as well as dilatational and interfacial shear rheology. Suitability of the applied methods to the chosen samples with higher concentrations >1–2% was verified by calculation of selected key numbers like capillary number and by detailed reviewing of the results which is summarized further on as key indicators. It is hypothesized, that the increase in concentration via presence of starch conversion products will delay interfacial stabilization as a result of increased bulk viscosity with decreasing degree of degradation (dextrose equivalent) of the starch. Furthermore, this increase in concentration leads to more stable interfacial films due to thermodynamic incompatibility effects between protein and starch conversion products which results in increases of local protein concentration. Key indicators proved a general suitability of applied methods for the evaluation of the investigated samples. Moreover, results showed an increase in interfacial film stability and elastic properties alongside a decreased interfacial tension if starch conversion products were present in a high concentration.

Protein-protein interactions and water activity coefficients can be used to aid a first excipient choice in protein formulations

With respect to all biopharmaceuticals marketed to date, monoclonal antibodies represent the largest fraction with more than 48% market share (2012). However, the development of biopharmaceutical formulations is a challenging task, and time-consuming and cost-intensive high-throughput screenings are still state-of-the-art in formulation design. These screening techniques are almost exclusively based on heuristic decisions thus the benefit in terms of mechanistic understanding is often unclear. It requires novel, physical-sound methods to enhance/optimize future formulation development, ideally by understanding molecular interactions in these complex solutions. A suitable and evaluated measure-of-choice to characterize protein-protein interactions in aqueous protein solutions is the second osmotic virial coefficient B₂₂ which can be measured using static light scattering techniques. Furthermore B₂₂ can be modeled/predicted via the extended mxDLVO model for protein-protein interactions in the presence of single excipients and excipient-mixtures. Building up on this approach, giving an additional insight into water-water and water-excipient interactions, the thermodynamic equation-of-state ePC-SAFT is used to calculate water activity coefficients in the presence of excipient-mixtures. Immunoglobulin G (IgG) was chosen as a model protein to predict B₂₂-values for IgG in the presence of model excipient-mixtures (trehalose-NaCl, l-histidine-trehalose, l-histidine-NaCl). The combination of water activity coefficients and B₂₂ allows to quickly identify a first guess on suitable formulation conditions that then can be further evaluated with existing methods/knowledge.

Protein-Protein Interactions of Highly Concentrated Monoclonal Antibody Solutions via Static Light Scattering and Influence on the Viscosity

The ability to design and formulate mAbs to minimize attractive interactions at high concentrations is important for protein processing, stability, and administration, particularly in subcutaneous delivery, where high viscosities are often challenging. The strength of protein-protein interactions (PPIs) of an IgG1 and IgG4 monoclonal antibody (mAb) from low to high concentration was determined by static light scattering (SLS) and used to understand viscosity data. The PPI were tuned using NaCl and five organic ionic co-solutes. The PPI strength was quantified by the normalized structure factor S(0)/ S(0)_HS and Kirkwood-Buff integral G₂₂/ G_22,HS (HS = hard sphere) determined from the SLS data and also by fits with (1) a spherical Yukawa potential and (2) an interacting hard sphere (IHS) model, which describes attraction in terms of hypothetical oligomers. The IHS model was better able to capture the scattering behavior of the more strongly interacting systems (mAb and/or co-solute) than the spherical Yukawa potential. For each descriptor of PPI, linear correlations were obtained between the viscosity at high concentration (200 mg/mL) and the interaction strengths evaluated both at low (20 mg/mL) and high concentrations (200 mg/mL) for a given mAb. However, the only parameter that provided a correlation across both mAbs was the oligomer mass ratio ( m_oligomer/ m_{monomer+dimer}) from the IHS model, indicating the importance of self-association (in addition to the direct influence of the attractive PPI) on the viscosity.

Tuning the Balance between Fibrillation and Oligomerization of α-Synuclein in the Presence of Dopamine

The aggregates of α-synuclein bear a close connection with Parkinson's disease, which is largely characterized by the loss of the dopaminergic neurons. Dopamine promotes the formation of undesirable sodium dodecyl sulfate (SDS)-resistant oligomers of α-synuclein. In this study, we have shown that the inhibition of fibrillation by an additive may not always be the ultimate deciding factor in the context of its potential as a successful additive. Copper promotes the fibrillation of α-synuclein in buffer alone but inhibits the formation of SDS-resistant oligomers in the presence of dopamine. Glycerol, on the other hand, increases the population of such dopamine-mediated SDS-resistant oligomers. We speculate such an effect to be a manifestation of the distinct oxidation pathway of dopamine in the presence of copper.

An Evaluation of the Potential of NMR Spectroscopy and Computational Modelling Methods to Inform Biopharmaceutical Formulations

Protein-based therapeutics are considered to be one of the most important classes of pharmaceuticals on the market. The growing need to prolong stability of high protein concentrations in liquid form has proven to be challenging. Therefore, significant effort is being made to design formulations which can enable the storage of these highly concentrated protein therapies for up to 2 years. Currently, the excipient selection approach involves empirical high-throughput screening, but does not reveal details on aggregation mechanisms or the molecular-level effects of the formulations under storage conditions. Computational modelling approaches have the potential to elucidate such mechanisms, and rapidly screen in silico prior to experimental testing. Nuclear Magnetic Resonance (NMR) spectroscopy can also provide complementary insights into excipient–protein interactions. This review will highlight the underpinning principles of molecular modelling and NMR spectroscopy. It will also discuss the advancements in the applications of computational and NMR approaches in investigating excipient–protein interactions.

Retracted: Molecular characterization of excipients' preferential interactions with therapeutic monoclonal antibodies

Retraction: Molecular characterization of excipients' preferential interactions with therapeutic monoclonal antibodies by Jehoon Kim, Mark R. H. Krebs and Bernhardt L. Trout The above article from the Journal of Pharmacy and Pharmacology, first published online on 4 August 2017 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors, the journal Editor-in-Chief, Professor David Jones, and John Wiley & Sons Ltd. The authors discovered that the analysis of simulations was faulty making the data incorrect. Reference Kim J et al. Molecular characterization of excipients' preferential interactions with therapeutic monoclonal antibodies. J Pharm Pharmacol 2017. https://doi.org/10.1111/jphp.12787.

The importance of handling high-value biologicals: Physico-chemical instability and immunogenicity of monoclonal antibodies

The present review specifies the various chemical and physical factors that can influence drug stability and immunogenicity, and the treatment outcomes of antibody biologicals. Although monoclonal antibodies (mAbs) are known to be more resistant to environmental changes compared with other proteins, the molecules themselves can be subjected to chemical and physical processes that promote their degradation and transformation into their specific amino-acid moieties. With increasing use of medicinal products that contain mAbs, and their self-administration by the patients, the issue of the correct manipulation of these drugs is of increasing importance. This review summarises the correct handling of mAb biologicals from the point of view of the pharmacist, clinical biochemist and patient, as is supported by relevant cases from the literature and our own data and experience. In particular, if there is a break in the cold chain, both healthcare professionals and patients need to be aware of the potential pharmacokinetics and pharmacodynamics alterations to these biologicals. Furthermore, any alterations in the protein structure can induce harmful immune reactions, including anaphylaxis and cytokine storms, or result in the production of neutralising or blocking Abs. Overall, considering also that treatment costs usually remain high, drug stability can have a tremendous effect on the clinical, humanistic and economic outcomes of such treatments.

A New Mixed All-Atom/Coarse-Grained Model: Application to Melittin Aggregation in Aqueous Solution

We introduce a new mixed resolution, all-atom/coarse-grained approach (AACG), for modeling peptides in aqueous solution and apply it to characterizing the aggregation of melittin. All of the atoms in peptidic components are represented, while a single site is used for each water molecule. With the full flexibility of the peptide retained, our AACG method achieves speedups by a factor of 3-4 for CPU time reduction and another factor of roughly 7 for diffusion. An Ewald treatment permits the inclusion of long-range electrostatic interactions. These characteristics fit well with the requirements for studying peptide association and aggregation, where the system sizes and time scales require considerable computational resources with all-atom models. In particular, AACG is well suited for biologics since changes in peptide shape and long-range electrostatics may play an important role. The application of AACG to melittin, a 26-residue peptide with a well-known propensity to aggregate in solution, serves as an initial demonstration of this technology for studying peptide aggregation. We observed the formation of melittin aggregates during our simulations and characterized the time-evolution of aggregate size distribution, buried surface areas, and residue contacts. Key interactions including π-cation and π-stacking involving TRP19 were also examined. Our AACG simulations demonstrated a clear salt effect and a moderate temperature effect on aggregation and support the molten globule model of melittin aggregates. As a showcase, this work illustrates the useful role for AACG in investigations of peptide aggregation and its potential to guide formulation and design of biologics.

A change in the aggregation pathway of bovine serum albumin in the presence of arginine and its derivatives

Chemical chaperones including arginine and its derivatives are widely used by biochemists working on the design of agents, which are able to efficiently suppress protein aggregation. To elucidate the mechanisms of anti-aggregation activity of chemical chaperones, methods based on registration of the increment in light scattering intensity must be supplemented with methods for direct detection of the portion of aggregated protein (γ_agg). For this purpose asymmetric flow field-flow fractionation was used in the present work. It was shown that heat-induced aggregation of bovine serum albumin (BSA) followed the kinetics of the reaction of the second order (0.1 M sodium phosphate buffer, pH 7.0, 70 °C). It was proposed to use R_hvs γ_agg plots to characterize the aggregation pathway (R_h is the hydrodynamic radius of the protein aggregates, which was calculated from the dynamic light scattering data). The changes in the shape of R_hvs γ_agg plots in the presence of arginine, arginine amide and arginine ethyl ester are indicative of the changes in the aggregation pathway of BSA aggregation. A conclusion has been made that larger aggregates are formed in the presence of arginine hydrochloride and its derivatives.

Application of Hidden Markov Models in Biomolecular Simulations

Hidden Markov models (HMMs) provide a framework to analyze large trajectories of biomolecular simulation datasets. HMMs decompose the conformational space of a biological molecule into finite number of states that interconvert among each other with certain rates. HMMs simplify long timescale trajectories for human comprehension, and allow comparison of simulations with experimental data. In this chapter, we provide an overview of building HMMs for analyzing bimolecular simulation datasets. We demonstrate the procedure for building a Hidden Markov model for Met-enkephalin peptide simulation dataset and compare the timescales of the process.

Second Virial Coefficient As Determined from Protein Phase Behavior

We quantitatively link the macroscopic phase behavior of protein solutions to protein-protein interactions based on a coarse-grained colloidal approach. We exploit the extended law of corresponding states and apply the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory in order to infer the second virial coefficient b₂, an integral measure of the interaction potential, from the phase behavior, namely, cloud-point temperature (CPT) measurements under conditions favoring protein crystallization. This determination of b₂ yields values that quantitatively agree with the results of static light scattering (SLS) experiments. The strength of the attractions is quantified in terms of an effective Hamaker constant, which accounts for van der Waals attractions as well as non-DLVO forces, such as hydration and hydrophobic interactions. Our approach based on simple lab experiments to determine the CPT in combination with the DLVO theory is expected to facilitate further biophysical research on protein-protein interactions in complex solution environments.

Overexpression and purification of folded domain of prostate cancer related proteins MSMB and PSA

Overexpression of domains of a human protein using recombinant DNA technology has been challenging because individual domains intend to accumulate as non-soluble aggregate when expressed separately. Studies on identifying right sequences for a domain to be able to fold independently may help understand the folding pattern and underlying protein-engineering events to isolate the functional domains of a protein. In this report, individual domains of prostate cancer related biomarkers; MSMB and PSA were overexpressed in bacterial system and purified in their folded forms using affinity chromatography. The western blotting experiment using domain specific antibodies further confirmed these proteins. The designed nucleotide sequences domains were truncated using fold index software and folding were predicted by phyre2 and I-TASSER software. Other parameters were optimized for their overexpression and purification using Co-NTA affinity chromatography. Purified domains of each protein showed secondary structures such as α + β type for PSA, α/β and β type for the each domains of PSA and MSMB respectively. This is the first report on producing PSA and MSMB individual domains in functional folded forms. This study may help produce the folded domain of many such proteins to be used for better diagnostic purpose.

Tuning protein-protein interactions using cosolvents: specific effects of ionic and non-ionic additives on protein phase behavior

Cosolvents are routinely used to modulate the (thermal) stability of proteins and, hence, their interactions with proteins have been studied intensely. However, less is known about their specific effects on protein-protein interactions, which we characterize in terms of the protein phase behavior. We analyze the phase behavior of lysozyme solutions in the presence of sodium chloride (NaCl), guanidine hydrochloride (GuHCl), glycerol, and dimethyl sulfoxide (DMSO). We experimentally determined the crystallization boundary (XB) and, in combination with data on the cloud-point temperatures (CPTs), the crystallization gap. In agreement with other studies, our data indicate that the additives might affect the protein phase behavior through electrostatic screening and additive-specific contributions. At high salt concentrations, where electrostatic interactions are screened, both the CPT and the XB are found to be linear functions of the additive concentration. Their slopes quantify the additive-specific changes of the phase behavior and thus of the protein-protein interactions. While the specific effect of NaCl is to induce attractions between proteins, DMSO, glycerol and GuHCl (with increasing strength) weaken attractions and/or induce repulsions. Except for DMSO, changes of the CPT are stronger than those of the XB. Furthermore, the crystallization gap widens in the case of GuHCl and glycerol and narrows in the case of NaCl. We relate these changes to colloidal interaction models, namely square-well and patchy interactions.

Preventing Aggregation of Recombinant Interferon beta-1b in Solution by Additives: Approach to an Albumin-Free Formulation

PURPOSE

Aggregation suppressing additives have been used to stabilize proteins during manufacturing and storage. Interferonβ-1b is prone to aggregation because of being non-glycosylated. Aggregation behavior of albumin-free formulations of recombinant IFNβ-1b was explored using additives such as n-dodecyl-β-D-maltoside, Tween 20, arginine, glycine, trehalose and sucrose at different pH.

METHODS

Fractional factorial design was applied to select major factors affecting aggregation in solutions. Box-Behnken technique was used to optimize the best concentration of additives and protein.

RESULTS

Quadratic model was the best fitted model for particle size, OD350 and OD280/OD260. The optimal conditions of 0.2% n-Dodecyl-β-D-maltoside, 70 mM arginine, 189 mM trehalose and protein concentration of 0.50 mg/ml at pH 4 were achieved. A potency value of 91% ± 5% was obtained for the optimized formulation.

CONCLUSION

This study shows that the combination of n-Dodecyl-β-D-maltoside, arginine and trehalose would demonstrate a significant stabilizing and anti-aggregating effect on the liquid formulation of interferonβ-1b. It can not only reduce the manufacturing costs but will also ease patient compliance.