Chemometrics in Protein Formulation: Stability Governed by Repulsion and Protein Unfolding.

Therapeutic proteins can be challenging to develop due to their complexity and the requirement of an acceptable formulation to ensure patient safety and efficacy. To date, there is no universal formulation development strategy that can identify optimal formulation conditions for all types of proteins in a fast and reliable manner. In this work, high-throughput characterization, employing a toolbox of five techniques, was performed on 14 structurally different proteins formulated in 6 different buffer conditions and in the presence of 4 different excipients. Multivariate data analysis and chemometrics were used to analyze the data in an unbiased way. First, observed changes in stability were primarily determined by the individual protein. Second, pH and ionic strength are the two most important factors determining the physical stability of proteins, where there exists a significant statistical interaction between protein and pH/ionic strength. Additionally, we developed prediction methods by partial least-squares regression. Colloidal stability indicators are important for prediction of real-time stability, while conformational stability indicators are important for prediction of stability under accelerated stress conditions at 40 °C. In order to predict real-time storage stability, protein-protein repulsion and the initial monomer fraction are the most important properties to monitor.

Multivalent binding kinetics resolved by fluorescence proximity sensing.

Multivalent protein interactors are an attractive modality for probing protein function and exploring novel pharmaceutical strategies. The throughput and precision of state-of-the-art methodologies and workflows for the effective development of multivalent binders is currently limited by surface immobilization, fluorescent labelling and sample consumption. Using the gephyrin protein, the master regulator of the inhibitory synapse, as benchmark, we exemplify the application of Fluorescence proximity sensing (FPS) for the systematic kinetic and thermodynamic optimization of multivalent peptide architectures. High throughput synthesis of +100 peptides with varying combinatorial dimeric, tetrameric, and octameric architectures combined with direct FPS measurements resolved on-rates, off-rates, and dissociation constants with high accuracy and low sample consumption compared to three complementary technologies. The dataset and its machine learning-based analysis deciphered the relationship of specific architectural features and binding kinetics and thereby identified binders with unprecedented protein inhibition capacity; thus, highlighting the value of FPS for the rational engineering of multivalent inhibitors.

pH- and concentration-dependent supramolecular assembly of a fungal defensin plectasin variant into helical non-amyloid fibrils.

Self-assembly and fibril formation play important roles in protein behaviour. Amyloid fibril formation is well-studied due to its role in neurodegenerative diseases and characterized by refolding of the protein into predominantly ß-sheet form. However, much less is known about the assembly of proteins into other types of supramolecular structures. Using cryo-electron microscopy at a resolution of 1.97 Å, we show that a triple-mutant of the anti-microbial peptide plectasin, PPI42, assembles into helical non-amyloid fibrils. The in vitro anti-microbial activity was determined and shown to be enhanced compared to the wildtype. Plectasin contains a cysteine-stabilised α-helix-ß-sheet structure, which remains intact upon fibril formation. Two protofilaments form a right-handed protein fibril. The fibril formation is reversible and follows sigmoidal kinetics with a pH- and concentration dependent equilibrium between soluble monomer and protein fibril. This high-resolution structure reveals that α/ß proteins can natively assemble into fibrils.

A New Spectral Shift-Based Method to Characterize Molecular Interactions.

There are many fluorescence-based applications that can be used to characterize molecular interactions. However, available methods often depend on site-specific labeling techniques or binding-induced changes in conformation or size of the probed target molecule. To overcome these limitations, we applied a ratiometric dual-emission approach that quantifies ligand-induced spectral shifts with sub-nanometer sensitivity. The use of environment-sensitive near-infrared dyes with the method we describe enables affinity measurements and thermodynamic characterization without the explicit need for site-specific labeling or ligand-induced conformational changes. We demonstrate that in-solution spectral shift measurements enable precise characterization of molecular interactions for a variety of biomolecules, including proteins, antibodies, and nucleic acids. Thereby, the described method is not limited to a subset of molecules since even the most challenging samples of research and drug discovery projects like membrane proteins and intrinsically disordered proteins can be analyzed.

Self-Interactions of Two Monoclonal Antibodies: Small-Angle X-ray Scattering, Light Scattering, and Coarse-Grained Modeling.

Using light scattering (LS), small-angle X-ray scattering (SAXS), and coarse-grained Monte Carlo (MC) simulations, we studied the self-interactions of two monoclonal antibodies (mAbs), PPI03 and PPI13. With LS measurements, we obtained the osmotic second virial coefficient, B22, and the molecular weight, Mw, of the two mAbs, while with SAXS measurements, we studied the mAbs' self-interaction behavior in the high protein concentration regime up to 125 g/L. Through SAXS-derived coarse-grained representations of the mAbs, we performed MC simulations with either a one-protein or a two-protein model to predict B22. By comparing simulation and experimental results, we validated our models and obtained insights into the mAbs' self-interaction properties, highlighting the role of both ion binding and charged patches on the mAb surfaces. Our models provide useful information about mAbs' self-interaction properties and can assist the screening of conditions driving to colloidal stability.

Combination of high throughput and structural screening to assess protein stability - A screening perspective.

High throughput screening for measuring the stability of industrially relevant proteins and their variants is necessary for quality assessment in the development process. Advances in automation, measurement time and sample consumption for many techniques allow rapid measurements with minimal amount of protein. However, many methods include automated data analysis, potentially neglecting important aspects of the protein's behavior in certain conditions. In this study we implement small angle X-ray scattering (SAXS), typically not used to assess protein behavior in industrial screening, in a high throughput screening workflow to address problems of contradicting results and reproducibility among different high throughput methods. As a case study we use the lipases of Thermomyces lanuginosus and Rhizomucor miehei, widely used industrial biocatalysts. We show that even the initial analysis of the SAXS data without performing any time-consuming modelling provide valuable information on interparticle interactions. We conclude that recent advances in automation and data processing, have enabled SAXS to be used more widely as a tool to gain in-depth knowledge highly useful for protein formulation development. This is especially relevant in light of increasing accessibility to SAXS due to the commercial availability of benchtop instruments.

Electrostatics Drive Oligomerization and Aggregation of Human Interferon Alpha-2a.

Aggregation is a common phenomenon in the field of protein therapeutics and can lead to function loss or immunogenic patient responses. Two strategies are currently used to reduce aggregation: (1) finding a suitable formulation, which is labor-intensive and requires large protein quantities, or (2) engineering the protein, which requires extensive knowledge about the protein aggregation pathway. We present a biophysical characterization of the oligomerization and aggregation processes by Interferon alpha-2a (IFNα-2a), a protein drug with antiviral and immunomodulatory properties. This study combines experimental high throughput screening with detailed investigations by small-angle X-ray scattering and analytical ultracentrifugation. Metropolis Monte Carlo simulations are used to gain insight into the underlying intermolecular interactions. IFNα-2a forms soluble oligomers that are controlled by a fast pH and concentration-dependent equilibrium. Close to the isoelectric point of 6, IFNα-2a forms insoluble aggregates which can be prevented by adding salt. We show that monomer attraction is driven mainly by molecular anisotropic dipole-dipole interactions that increase with increasing pH. Repulsion is due to monopole-monopole interactions and depends on the charge of IFNα-2a. The study highlights how combining multiple methods helps to systematically dissect the molecular mechanisms driving oligomer formation and to design ultimately efficient strategies for preventing detrimental protein aggregation.

Development of a fast screening method for selecting excipients in formulations using MD simulations, NMR and microscale thermophoresis.

Development of peptide therapeutics generally involves screening of excipients that inhibit peptide-peptide interactions, hence aggregation, and improve peptide stability. We used the therapeutic peptide plectasin to develop a fast screening method that combines microscale thermophoresis titration assays and molecular dynamics simulations to relatively rank the excipients with respect to binding affinity and to study key peptide-excipient interaction hotspots on a molecular level, respectively. Additionally, 1H-13C-HSQC NMR titration experiments were performed to validate the fast screening approach. The NMR results are in qualitative agreement with results from the fast screening method demonstrating that this approach can be reliably applied to other peptides and proteins as a fast screening method to relatively rank excipients and predict possible excipient binding sites.

Small angle X-ray scattering and molecular dynamic simulations provide molecular insight for stability of recombinant human transferrin.

Transferrin is an attractive candidate for drug delivery due to its ability to cross the blood brain barrier. However, in order to be able to use it for therapeutic purposes, it is important to investigate how its stability depends on different formulation conditions. Combining high-throughput thermal and chemical denaturation studies with small angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations, it was possible to connect the stability of transferrin with its conformational changes. Lowering pH induces opening of the transferrin N-lobe, which results in a negative effect on the stability. Presence of NaCl or arginine at low pH enhances the opening and has a negative impact on the overall protein stability. STATEMENT OF SIGNIFICANCE: Protein-based therapeutics have become an essential part of medical treatment. They are highly specific, have high affinity and fewer off-target effects. However, stabilization of proteins is critical, time-consuming, and expensive, and it is not yet possible to predict the behavior of proteins under different conditions. The current work is focused on a molecular understanding of the stability of human serum transferrin; a protein which is abundant in blood serum, may pass the blood brain barrier and therefore with high potential in drug delivery. Combination of high throughput unfolding techniques and structural studies, using small angle X-ray scattering and molecular dynamic simulations, allows us to understand the behavior of transferrin on a molecular level.

The Effect of Point Mutations on the Biophysical Properties of an Antimicrobial Peptide: Development of a Screening Protocol for Peptide Stability Screening.

Therapeutic peptides and proteins show enormous potential in the pharmaceutical market, but high costs in discovery and development are limiting factors so far. Single or multiple point mutations are commonly introduced in protein drugs to increase their binding affinity or selectivity. They can also induce adverse properties, which might be overlooked in a functional screen, such as a decreased colloidal or thermal stability, leading to problems in later stages of the development. In this study, we address the effect of point mutations on the stability of the 4.4 kDa antimicrobial peptide plectasin, as a case study. We combined a systematic high-throughput biophysical screen of the peptide thermal and colloidal stability using dynamic light scattering and differential scanning calorimetry with structure-based methods including small-angle X-ray scattering, analytical ultracentrifugation, and nuclear magnetic resonance spectroscopy. Additionally, we applied molecular dynamics simulations to link obtained protein stability parameters to the protein's molecular structure. Despite their predicted structural similarities, all four plectasin variants showed substantially different behavior in solution. We observed an increasing propensity of plectasin to aggregate at a higher pH, and the introduced mutations influenced the type of aggregation. Our strategy for systematically assessing the stability and aggregation of protein drugs is generally applicable and is of particular relevance, given the increasing number of protein drugs in development.

Albumin-neprilysin fusion protein: understanding stability using small angle X-ray scattering and molecular dynamic simulations.

Fusion technology is widely used in protein-drug development to increase activity, stability, and bioavailability of protein therapeutics. Fusion proteins, like any other type of biopharmaceuticals, need to remain stable during production and storage. Due to the high complexity and additional intramolecular interactions, it is not possible to predict the behavior of fusion proteins based on the behavior the individual proteins. Therefore, understanding the stability of fusion proteins on the molecular level is crucial for the development of biopharmaceuticals. The current study on the albumin-neprilysin (HSA-NEP) fusion protein uses a combination of thermal and chemical unfolding with small angle X-ray scattering and molecular dynamics simulations to show a correlation between decreasing stability and increasing repulsive interactions, which is unusual for most biopharmaceuticals. It is also seen that HSA-NEP is not fully flexible: it is present in both compact and extended conformations. Additionally, the volume fraction of each conformation changes with pH. Finally, the presence of NaCl and arginine increases stability at pH 6.5, but decreases stability at pH 5.0.

Characterization of Native Reversible Self-Association of a Monoclonal Antibody Mediated by Fab-Fab Interaction.

The native reversible self-association of monoclonal antibodies has been associated with high viscosity, liquid-liquid, and liquid-solid phase separation. We investigated the native reversible self-association of an IgG1, which exerts this association even at low protein concentrations, in detail to gain further understanding of this phenomenon by extensive characterization of the association as a function of multiple factors, namely pH, temperature, salt concentration, and protein concentration. The nature of the self-association of the full-length IgG1 as well as the corresponding Fab and Fc fragment was studied by viz. size exclusion chromatography combined with multiangle light scattering, batch dynamic and static light scattering, analytical ultracentrifugation, small angle X-ray scattering, asymmetric flow field flow fractionation coupled with multiangle light scattering, and intrinsic fluorescence. We rationalized the self-association as a combination of hydrophobic and electrostatic interactions driven by the Fab fragments. Finally, we investigated the long-term stability of the IgG1 molecule.

Advancing Therapeutic Protein Discovery and Development through Comprehensive Computational and Biophysical Characterization.

Therapeutic protein candidates should exhibit favorable properties that render them suitable to become drugs. Nevertheless, there are no well-established guidelines for the efficient selection of proteinaceous molecules with desired features during early stage development. Such guidelines can emerge only from a large body of published research that employs orthogonal techniques to characterize therapeutic proteins in different formulations. In this work, we share a study on a diverse group of proteins, including their primary sequences, purity data, and computational and biophysical characterization at different pH and ionic strength. We report weak linear correlations between many of the biophysical parameters. We suggest that a stability comparison of diverse therapeutic protein candidates should be based on a computational and biophysical characterization in multiple formulation conditions, as the latter can largely determine whether a protein is above or below a certain stability threshold. We use the presented data set to calculate several stability risk scores obtained with an increasing level of analytical effort and show how they correlate with protein aggregation during storage. Our work highlights the importance of developing combined risk scores that can be used for early stage developability assessment. We suggest that such scores can have high prediction accuracy only when they are based on protein stability characterization in different solution conditions.

Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry.

In biotherapeutic protein research, an estimation of the studied protein's thermal stability is one of the important steps that determine developability as a function of solvent conditions. Differential Scanning Fluorimetry (DSF) can be applied to measure thermal stability. Label-free DSF measures amino acid fluorescence as a function of temperature, where conformational changes induce observable peak deformation, yielding apparent melting temperatures. The estimation of the stability parameters can be hindered in the case of multidomain, multimeric or aggregating proteins when multiple transitions partially coincide. These overlapping protein unfolding transitions are hard to evaluate by the conventional methodology, as peak maxima are shifted by convolution. We show how non-linear curve fitting of intrinsic fluorescence DSF can deconvolute highly overlapping transitions in formulation screening in a semi-automated process. The proposed methodology relies on synchronous, constrained fits of the fluorescence intensity, ratio and their derivatives, by combining linear baselines with generalized logistic transition functions. The proposed algorithm is applied to data from three proteins; a single transition, a double separated transition and a double overlapping transition. Extracted thermal stability parameters; apparent melting temperatures Tm,1, Tm,2 and melting onset temperature Tonset are obtained and compared with reference software analysis. The fits show R2 = 0.94 for single and R2 = 0.88 for separated transitions. Obtaining values and trends for Tonset in a well-described and automated way, will aid protein scientist to better evaluate the thermal stability of proteins.

Application of interpretable artificial neural networks to early monoclonal antibodies development.

The development of a new protein drug typically starts with the design, expression and biophysical characterization of many different protein constructs. The initially high number of constructs is radically reduced to a few candidates that exhibit the desired biological and physicochemical properties. This process of protein expression and characterization to find the most promising molecules is both expensive and time-consuming. Consequently, many companies adopt and implement philosophies, e.g. platforms for protein expression and formulation, computational approaches, machine learning, to save resources and facilitate protein drug development. Inspired by this, we propose the use of interpretable artificial neuronal networks (ANNs) to predict biophysical properties of therapeutic monoclonal antibodies i.e. melting temperature Tm, aggregation onset temperature Tagg, interaction parameter kD as a function of pH and salt concentration from the amino acid composition. Our ANNs were trained with typical early-stage screening datasets achieving high prediction accuracy. By only using the amino acid composition, we could keep the ANNs simple which allows for high general applicability, robustness and interpretability. Finally, we propose a novel "knowledge transfer" approach, which can be readily applied due to the simple algorithm design, to understand how our ANNs come to their conclusions.

Conformational Stability Study of a Therapeutic Peptide Plectasin Using Molecular Dynamics Simulations in Combination with NMR.

Plectasin is a small, cysteine-rich peptide antibiotic which belongs to the class of antimicrobial peptides and has potential antibacterial activity against various Gram-positive bacteria. In the current study, the effect of pH and ionic strength (NaCl) on the conformational stability of plectasin variants has been investigated. At all physiochemical conditions, peptide secondary structures are intact throughout simulations. However, flexibility increases with pH because of the change in electrostatics around the distinct anionic tetrapeptide (9-12) stretch. Furthermore, plectasin interactions with NaCl were measured by determining the preferential interaction coefficients, Γ23. Generally, wild-type plectasin has higher preference for sodium ions as 9ASP is mutated in other variants. Overall, the Γ23 trend with pH for the two salt conditions remain the same for all variants predominately having accumulation of sodium ions around 10GLU and 12ASP. Insignificant changes in the overall peptide conformational stability are in agreement with the fact that plectasin has three cystines. Thermodynamic integration molecular dynamics simulations supplemented with nuclear magnetic resonance were employed to determine the degree of involvement of three different cystines to the overall structural integrity of the peptide. Both methods show the same order of cystine reduction and complete unfolding is observed only upon reduction of all cystines.

A novel TPR-BEN domain interaction mediates PICH-BEND3 association.

PICH is a DNA translocase required for the maintenance of chromosome stability in human cells. Recent data indicate that PICH co-operates with topoisomerase IIα to suppress pathological chromosome missegregation through promoting the resolution of ultra-fine anaphase bridges (UFBs). Here, we identify the BEN domain-containing protein 3 (BEND3) as an interaction partner of PICH in human cells in mitosis. We have purified full length PICH and BEND3 and shown that they exhibit a functional biochemical interaction in vitro. We demonstrate that the PICH-BEND3 interaction occurs via a novel interface between a TPR domain in PICH and a BEN domain in BEND3, and have determined the crystal structure of this TPR-BEN complex at 2.2 Å resolution. Based on the structure, we identified amino acids important for the TPR-BEN domain interaction, and for the functional interaction of the full-length proteins. Our data reveal a proposed new function for BEND3 in association with PICH, and the first example of a specific protein-protein interaction mediated by a BEN domain.

Characterization of the NTPR and BD1 interacting domains of the human PICH-BEND3 complex.

Chromosome integrity depends on DNA structure-specific processing complexes that resolve DNA entanglement between sister chromatids. If left unresolved, these entanglements can generate either chromatin bridging or ultrafine DNA bridging in the anaphase of mitosis. These bridge structures are defined by the presence of the PICH protein, which interacts with the BEND3 protein in mitosis. To obtain structural insights into PICH-BEND3 complex formation at the atomic level, their respective NTPR and BD1 domains were cloned, overexpressed and crystallized using 1.56 M ammonium sulfate as a precipitant at pH 7.0. The protein complex readily formed large hexagonal crystals belonging to space group P6122, with unit-cell parameters a = b = 47.28, c = 431.58 Šand with one heterodimer in the asymmetric unit. A complete multiwavelength anomalous dispersion (MAD) data set extending to 2.2 Šresolution was collected from a selenomethionine-labelled crystal at the Swiss Light Source.

Structural Analysis of a Complex between Small Ubiquitin-like Modifier 1 (SUMO1) and the ZZ Domain of CREB-binding Protein (CBP/p300) Reveals a New Interaction Surface on SUMO.

We have recently discovered that the ZZ zinc finger domain represents a novel small ubiquitin-like modifier (SUMO) binding motif. In this study we identify the binding epitopes in the ZZ domain of CBP (CREB-binding protein) and SUMO1 using NMR spectroscopy. The binding site on SUMO1 represents a unique epitope for SUMO interaction spatially opposite to that observed for canonical SUMO interaction motifs (SIMs). HADDOCK docking simulations using chemical shift perturbations and residual dipolar couplings was employed to obtain a structural model for the ZZ domain-SUMO1 complex. Isothermal titration calorimetry experiments support this model by showing that the mutation of key residues in the binding site abolishes binding and that SUMO1 can simultaneously and non-cooperatively bind both the ZZ domain and a canonical SIM motif. The binding dynamics of SUMO1 was further characterized using (15)N Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersions, which define the off rates for the ZZ domain and SIM motif and show that the dynamic binding process has different characteristics for the two cases. Furthermore, in the absence of bound ligands SUMO1 transiently samples a high energy conformation, which might be involved in ligand binding.

Conformation-specific anti-Mad2 monoclonal antibodies for the dissection of checkpoint signaling.

The spindle assembly checkpoint (SAC) ensures accurate chromosome segregation during mitosis by delaying the activation of the anaphase-promoting complex/cyclosome (APC/C) in response to unattached kinetochores. The Mad2 protein is essential for a functional checkpoint because it binds directly to Cdc20, the mitotic co-activator of the APC/C, thereby inhibiting progression into anaphase. Mad2 exists in at least 2 different conformations, open-Mad2 (O-Mad2) and closed-Mad2 (C-Mad2), with the latter representing the active form that is able to bind Cdc20. Our ability to dissect Mad2 biology in vivo is limited by the absence of monoclonal antibodies (mAbs) useful for recognizing the different conformations of Mad2. Here, we describe and extensively characterize mAbs specific for either O-Mad2 or C-Mad2, as well as a pan-Mad2 antibody, and use these to investigate the different Mad2 complexes present in mitotic cells. Our antibodies validate current Mad2 models but also suggest that O-Mad2 can associate with checkpoint complexes, most likely through dimerization with C-Mad2. Furthermore, we investigate the makeup of checkpoint complexes bound to the APC/C, which indicate the presence of both Cdc20-BubR1-Bub3 and Mad2-Cdc20-BubR1-Bub3 complexes, with Cdc20 being ubiquitinated in both. Thus, our defined mAbs provide insight into checkpoint signaling and provide useful tools for future research on Mad2 function and regulation.