Silk-protein-based gradient hydrogels with multimode reprogrammable shape changes for biointegrated devices.

Biocompatible and morphable hydrogels capable of multimode reprogrammable, and adaptive shape changes are potentially useful for diverse biomedical applications. However, existing morphable systems often rely on complicated structural designs involving cumbersome and energy-intensive fabrication processes. Here, we report a simple electric-field-activated protein network migration strategy to reversibly program silk-protein hydrogels with controllable and reprogrammable complex shape transformations. The application of a low electric field enables the convergence of net negatively charged protein cross-linking networks toward the anode (isoelectric point plane) due to the pH gradient generated in the process, facilitating the formation of a gradient network structure and systems suitable for three-dimensional shape change. These tunable protein networks can be reprogrammed or permanently fixed by control of the polymorphic transitions. We show that these morphing hydrogels are capable of conformally interfacing with biological tissues by programming the shape changes and a bimorph structure consisting of aligned carbon nanotube multilayers and the silk hydrogels was assembled to illustrate utility as an implantable bioelectronic device for localized low-voltage electrical stimulation of the sciatic nerve in a rabbit.

RNA-dependent proteome solubility maintenance in Escherichia coli lysates analysed by quantitative mass spectrometry: Proteomic characterization in terms of isoelectric point, structural disorder, functional hub, and chaperone network.

Protein aggregation, a consequence of misfolding and impaired proteostasis, can lead to cellular malfunctions such as various proteinopathies. The mechanisms protecting proteins from aggregation in complex cellular environments have long been investigated, often from a protein-centric viewpoint. However, our study provides insights into a crucial, yet overlooked actor: RNA. We found that depleting RNAs from Escherichia coli lysates induces global protein aggregation. Our quantitative mass spectrometry analysis identified over 900 statistically significant proteins from the Escherichia coli proteome whose solubility depends on RNAs. Proteome-wide characterization showed that the RNA dependency is particularly enriched among acidic proteins, intrinsically disordered proteins, and structural hub proteins. Moreover, we observed distinct differences in RNA-binding mode and Gene Ontology categories between RNA-dependent acidic and basic proteins. Notably, the solubility of key molecular chaperones [Trigger factor, DnaJ, and GroES] is largely dependent on RNAs, suggesting a yet-to-be-explored hierarchical relationship between RNA-based chaperone (termed as chaperna) and protein-based chaperones, both of which constitute the whole chaperone network. These findings provide new insights into the RNA-centric role in maintaining healthy proteome solubility in vivo, where proteins associate with a variety of RNAs, either stably or transiently.

Proteome-pI 2.0: proteome isoelectric point database update.

Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point-the pH at which a particular molecule carries no net electrical charge-is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides' isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org.

Reconstruction of TNF-α with specific isoelectric point released from SPIONs basing on variable charge to enhance pH-sensitive controlled-release.

The clinical application of tumor necrosis factor-α (TNF-α) is limited by its short half-life, subeffective concentration in the targeted area and severe systemic toxicity. In this study, the recombinant polypeptide S4-TNF-α was constructed and coupled with chitosan-modified superparamagnetic iron oxide nanoparticles (S4-TNF-α-SPIONs) to achieve pH-sensitive controlled release and active tumor targeting activity. The isoelectric point (pI) of S4-TNF-α was reconstructed to approach the pH of the tumor microenvironment. The negative-charge S4-TNF-α was adsorbed to chitosan-modified superparamagnetic iron oxide nanoparticles (CS-SPIONs) with a positive charge through electrostatic adsorption at physiological pH. The acidic tumor microenvironment endowed S4-TNF-α with a zero charge, which accelerated S4-TNF-α release from CS-SPIONs. Our studies showed that S4-TNF-α-SPIONs displayed an ideal pH-sensitive controlled release capacity and improved antitumor effects. Our study presents a novel approach to enhance the pH-sensitive controlled-release of genetically engineered drugs by adjusting their pI to match the pH of the tumor microenvironment.

Quality evaluation of highly purified human menopausal gonadotropin preparations by means of gel electrophoresis and mass spectrometry.

Human gonadotropins are glycoprotein hormones with a highly complex structure, which demands the application of sophisticated analytical methodologies to assess their quality. The principal objective of this study was a comparative evaluation of gel electrophoretic techniques and mass spectrometry-based methods for the quality study of the two urinary-derived, highly purified, human menopausal gonadotropin preparations, Menopur 75/75 I. U. and Meriofert 75 I. U. Molecular mass (Mr), isoelectric point (pI), and isoform pattern of studied compounds were estimated via SDS-PAGE and 2D gel electrophoresis, whereas matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used for the downstream characterization of peptides obtained after in-gel tryptic digestion of selected protein spots. Additionally, for the estimation of the glycosylation pattern of these biologics, the enzymatic release of oligosaccharides was performed, and the isoform pattern was studied. Gel electrophoresis showed a typical electrophoretic behaviour for protein biotherapeutics medicines consisting of extremely complex spot patterns migrating at different masses and pIs. MS analysis proved to be a powerful tool for the identification and detailed characterization of the gonadotropins and the relevant peptides were identified with high sequence coverages. The results of this study are not only useful for the quality assessment of this class of complex biopharmaceuticals but may also serve as a supporting platform for further development of biopharmaceuticals based on modulation of the glycosylation pattern to enhance efficacy or reduce side effects.

Marker-Free Isoelectric Focusing Patterns for Identification of Meat Samples via Deep Learning.

Isoelectric focusing (IEF) is a powerful tool for resolving complex protein samples, which generates IEF patterns consisting of multiplex analyte bands. However, the interpretation of IEF patterns requires the careful selection of isoelectric point (pI) markers for profiling the pH gradient and a trivial process of pI labeling, resulting in low IEF efficiency. Here, we for the first time proposed a marker-free IEF method for the efficient and accurate classification of IEF patterns by using a convolutional neural network (CNN) model. To verify our method, we identified 21 meat samples whose IEF patterns comprised different bands of meat hemoglobin, myoglobin, and their oxygen-binding variants but no pI marker. Thanks to the high throughput and short assay time of the microstrip IEF, we efficiently collected 1449 IEF patterns to construct the data set for model training. Despite the absence of pI markers, we experimentally introduced the severe pH gradient drift into 189 IEF patterns in the data set, thereby omitting the need for profiling the pH gradient. To enhance the model robustness, we further employed data augmentation during the model training to mimic pH gradient drift. With the advantages of simple preprocessing, a rapid inference of 50 ms, and a high accuracy of 97.1%, the CNN model outperformed the traditional algorithm for simultaneously identifying meat species and cuts of meat of 105 IEF patterns, suggesting its great potential of being combined with microstrip IEF for large-scale IEF analyses of complicated protein samples.

PepAnalyzer: predicting peptide properties using its sequence.

Peptides are short linear molecules consisting of amino acids that play an essential role in most biological processes. They can treat diseases by working as a vaccine or antimicrobial agent and serves as a cancer molecule to deliver the drug to the target site for the treatment of cancer. They have the potential to solve the drawbacks of current medications and can be industrially produced in large quantities at low cost. However, poor chemical and physical stability, short circulating plasma half-life, and solubility are some issues that need solutions before they can be used as therapeutics. PepAnalyzer tool is a user-friendly tool that predicts 15 different properties such as binding potential, half-life, transmembrane patterns, test tube stability, charge, isoelectric point, molecular weights, and molar extinction coefficients only using the sequence. The tool is designed using BioPython utility and has even results with standard tools, such as Expasy, EBI, Genecorner, and Geneinfinity. The tool assists students, researchers, and the pharmaceutical sector. The PepAnalyzer tool's online platform is accessible at the link: http://www.iksmbrlabdu.in/peptool .

Optimizing the physical properties of collagen/hyaluronan hydrogels by inhibition of polyionic complexes formation at pH close to the collagen isoelectric point.

Collagen/hyaluronan hydrogels with physical properties well suited for biomedical applications are challenging to synthesize due to the formation of polyionic complexes (PICs). A systematic physicochemical study was thus performed to determine novel conditions to inhibit the formation of collagen/hyaluronan PICs and obtain composite hydrogels with high physical properties. Using a range of pH from 1 to 5.5 and the addition of NaCl, type I collagen and tyramine-substituted hyaluronic acid (THA) solutions were mixed and analyzed by cryo-scanning electron microscopy and ATR-FTIR. PIC formation was inhibited at pH 1 without salt and at pH 2.5 and 5.5 in the presence of 400 mM NaCl. Interestingly, collagen fibrils were observed in solution at pH 5.5 before mixing with THA. After collagen gelling by pH increase, a homogeneous hydrogel consisting of collagen fibrils was only observed when PICs were inhibited. Then, the THA gelling performed by photo-crosslinking increased the rheological properties by four when hydrogels were formed with collagen/THA mixtures at pH 1 or 5.5 with salt. Taken together, these results show that a pH of 5.5, close to the collagen isoelectric point, enables the formation of collagen fibrils in solution, inhibits the PICs formation, and allows the formation of homogenous collagen/THA composite hydrogels compatible with cell survival.

pIChemiSt ─ Free Tool for the Calculation of Isoelectric Points of Modified Peptides.

The isoelectric point (pI) is a fundamental physicochemical property of peptides and proteins. It is widely used to steer design away from low solubility and aggregation and guide peptide separation and purification. Experimental measurements of pI can be replaced by calculations knowing the ionizable groups of peptides and their corresponding pKa values. Different pKa sets are published in the literature for natural amino acids, however, they are insufficient to describe synthetically modified peptides, complex peptides of natural origin, and peptides conjugated with structures of other modalities. Noncanonical modifications (nCAAs) are ignored in the conventional sequence-based pI calculations, therefore producing large errors in their pI predictions. In this work, we describe a pI calculation method that uses the chemical structure as an input, automatically identifies ionizable groups of nCAAs and other fragments, and performs pKa predictions for them. The method is validated on a curated set of experimental measures on 29 modified and 119093 natural peptides, providing an improvement of R2 from 0.74 to 0.95 and 0.96 against the conventional sequence-based approach for modified peptides for the two studied pKa prediction tools, ACDlabs and pKaMatcher, correspondingly. The method is available in the form of an open source Python library at https://github.com/AstraZeneca/peptide-tools, which can be integrated into other proprietary and free software packages. We anticipate that the pI calculation tool may facilitate optimization and purification activities across various application domains of peptides, including the development of biopharmaceuticals.

Reliable assessment of carbon black nanomaterial of a variety of cell culture media for in vitro toxicity assays by asymmetrical flow field-flow fractionation.

Carbon black nanomaterial (CB-NM), as an industrial product with a large number of applications, poses a high risk of exposure, and its impact on health needs to be assessed. The most common testing platform for engineered (E)NMs is in vitro toxicity assessment, which requires prior ENM dispersion, stabilization, and characterization in cell culture media. Here, asymmetric flow field-flow fractionation (AF4) coupled to UV-Vis and dynamic light scattering (DLS) detectors in series was used for the study of CB dispersions in cell culture media, optimizing instrumental variables and working conditions. It was possible to disperse CB in a non-ionic surfactant aqueous solution due to the steric effect provided by surfactant molecules attached on the CB surface which prevented agglomeration. The protection provided by the surfactant or by culture media alone was insufficient to ensure good dispersion stability needed for carrying out in vitro toxicity studies. On the other hand, cell culture media in combination with the surfactant improved dispersion stability considerably, enabling the generation of shorter particles and a more favourable zeta potential magnitude, leading to greater stability due to electrostatic repulsion. It was demonstrated that the presence of amino acids in the culture media improved the monodisperse nature and stability of the CB dispersions, and resulted in a turn towards more negative zeta potential values when the pH was above the amino acid isoelectric point (IEP). Culture media used in real cell culture scenarios were also tested, and in vitro toxicity assays were developed optimizing the compatible amount of surfactant.

IPC 2.0: prediction of isoelectric point and pKa dissociation constants.

The isoelectric point is the pH at which a particular molecule is electrically neutral due to the equilibrium of positive and negative charges. In proteins and peptides, this depends on the dissociation constant (pKa) of charged groups of seven amino acids and NH+ and COO- groups at polypeptide termini. Information regarding isoelectric point and pKa is extensively used in two-dimensional gel electrophoresis (2D-PAGE), capillary isoelectric focusing (cIEF), crystallisation, and mass spectrometry. Therefore, there is a strong need for the in silico prediction of isoelectric point and pKa values. In this paper, I present Isoelectric Point Calculator 2.0 (IPC 2.0), a web server for the prediction of isoelectric points and pKa values using a mixture of deep learning and support vector regression models. The prediction accuracy (RMSD) of IPC 2.0 for proteins and peptides outperforms previous algorithms: 0.848 versus 0.868 and 0.222 versus 0.405, respectively. Moreover, the IPC 2.0 prediction of pKa using sequence information alone was better than the prediction from structure-based methods (0.576 versus 0.826) and a few folds faster. The IPC 2.0 webserver is freely available at www.ipc2-isoelectric-point.org.

Off-pathway 3D-structure provides protection against spontaneous Asn/Asp isomerization: shielding proteins Achilles heel.

Spontaneous deamidation prompted backbone isomerization of Asn/Asp residues resulting in - most cases - the insertion of an extra methylene group into the backbone poses a threat to the structural integrity of proteins. Here we present a systematical analysis of how temperature, pH, presence of charged residues, but most importantly backbone conformation and dynamics affect isomerization rates as determined by nuclear magnetic resonance in the case of designed peptide-models. We demonstrate that restricted mobility (such as being part of a secondary structural element) may safeguard against isomerization, but this protective factor is most effective in the case of off-pathway folds which can slow the reaction by several magnitudes compared to their on-pathway counterparts. We show that the geometric descriptors of the initial nucleophilic attack of the isomerization can be used to classify local conformation and contribute to the design of stable protein drugs, antibodies or the assessment of the severity of mutations.At any ­Asn/AspGly­ sites in proteins a spontaneous backbone isomerization occurs within days under physiological conditions leading to various forms of proteopathy. This unwanted transformation especially harmful to long-lived proteins (e.g. hemoglobin and crystallins), can be slowed down, though never stopped, by a rigid three-dimensional protein fold, if it can delay in the conformational maze, on-pathway intermediates from occurring.

Abundance, Betweenness Centrality, Hydrophobicity, and Isoelectric Points Are Relevant Factors in the Processing of Parental Proteins of the HLA Class II Ligandome.

Adaptive cellular and humoral immune responses to infectious agents require previous recognition of pathogenic peptides bound to human leukocyte antigen (HLA) class II molecules exposed on the surface of the professional antigen-presenting cells. Knowledge of how these peptide ligands are generated is essential to understand the basis for CD4+ T-cell-mediated immunity and tolerance. In this study, a high-throughput mass spectrometry analysis was used to identify more than 16,000 cell peptides bound to several HLA-DR and -DP class II molecules isolated from large amounts of uninfected and virus-infected human cells (ProteomeXchange accession: PXD028006). The analysis of the 1808 parental proteins containing HLA class II ligands revealed that these cell proteins were more acidic, abundant, and highly connected but less hydrophilic than non-parental proteomes. Therefore, the percentage of acidic residues was increased and hydroxyl and polar residues were decreased in the parental proteins for the HLA class II ligandomes versus the non-parental proteomes. This definition of the properties shared by parental proteins that constitute the source of the HLA class II ligandomes can serve as the basis for the development of bioinformatics tools to predict proteins that are most likely recognized by the immune system through the CD4+ helper T lymphocytes in both autoimmunity and infection.

Nanopore Current Enhancements Lack Protein Charge Dependence and Elucidate Maximum Unfolding at Protein's Isoelectric Point.

Protein sequencing, as well as protein fingerprinting, has gained tremendous attention in the electrical sensing realm of solid-state nanopores and is challenging due to fast translocations and the use of high molar electrolytes. Despite providing an appreciable signal-to-noise ratio, high electrolyte concentrations can have adverse effects on the native protein structure. Herein, we present a thorough investigation of low electrolyte sensing conditions across a broad pH and voltage range generating conductive pulses (CPs) irrespective of protein net charge. We used Cas9 as the model protein and demonstrated that unfolding is noncooperative, represented by the gradual elongation or stretching of the protein, and sensitive to both the applied voltage and pH (i.e., charge state). The magnitude of unfolding and the isoelectric point (pI) of Cas9 was found to be correlated and a critical factor in our experiments. Electroosmotic flow (EOF) was always aligned with the transit direction, whereas electrophoretic force (EPF) was either reinforcing (pH < pI) or opposing (pH > pI) the protein's movement, which led to slower translocations at higher pH values. Further exploration of higher pH values led to slowing down of protein with > 30% of the population being slower than 0.5 ms. Our results would be critical for protein sensing at very low electrolytes and to retard their translocation speed without resorting to high-bandwidth equipment.

Automated Capillary Isoelectric Focusing-Mass Spectrometry with Ultrahigh Resolution for Characterizing Microheterogeneity and Isoelectric Points of Intact Protein Complexes.

Protein complexes are the functional machines in the cell and are heterogeneous due to protein sequence variations and post-translational modifications (PTMs). Here, we present an automated nondenaturing capillary isoelectric focusing-mass spectrometry (ncIEF-MS) methodology for uncovering the microheterogeneity of intact protein complexes. The method exhibited superior separation resolution for protein complexes than conventional native capillary zone electrophoresis (nCZE-MS). In our study, ncIEF-MS achieved liquid-phase separations and MS characterization of seven different forms of a streptavidin homotetramer with variations of N-terminal methionine removal, acetylation, and formylation and four forms of the carbonic anhydrase-zinc complex arising from variations of PTMs (succinimide, deamidation, etc.). In addition, ncIEF-MS resolved different states of an interchain cysteine-linked antibody-drug conjugate (ADC1) as a new class of anticancer therapeutic agents that bears a distribution of varied drug-to-antibody ratio (DAR) species. More importantly, ncIEF-MS enabled precise measurements of isoelectric points (pIs) of protein complexes, which reflect the surface electrostatic properties of protein complexes. We studied how protein sequence variations/PTMs modulate the pIs of protein complexes and how drug loading affects the pIs of antibodies. We discovered that keeping the N-terminal methionine residue of one subunit of the streptavidin homotetramer decreased its pI by 0.1, adding one acetyl group onto the streptavidin homotetramer reduced its pI by nearly 0.4, incorporating one formyl group onto the streptavidin homotetramer reduced its pI by around 0.3, and loading two more drug molecules on one ADC1 molecule increased its pI by 0.1. The data render the ncIEF-MS method a valuable tool for delineating protein complexes.

Antibodies with Weakly Basic Isoelectric Points Minimize Trade-offs between Formulation and Physiological Colloidal Properties.

The widespread interest in antibody therapeutics has led to much focus on identifying antibody candidates with favorable developability properties. In particular, there is broad interest in identifying antibody candidates with highly repulsive self-interactions in standard formulations (e.g., low ionic strength buffers at pH 5-6) for high solubility and low viscosity. Likewise, there is also broad interest in identifying antibody candidates with low levels of non-specific interactions in physiological solution conditions (PBS, pH 7.4) to promote favorable pharmacokinetic properties. To what extent antibodies that possess both highly repulsive self-interactions in standard formulations and weak non-specific interactions in physiological solution conditions can be systematically identified remains unclear and is a potential impediment to successful therapeutic drug development. Here, we evaluate these two properties for 42 IgG1 variants based on the variable fragments (Fvs) from four clinical-stage antibodies and complementarity-determining regions from 10 clinical-stage antibodies. Interestingly, we find that antibodies with the strongest repulsive self-interactions in a standard formulation (pH 6 and 10 mM histidine) display the strongest non-specific interactions in physiological solution conditions. Conversely, antibodies with the weakest non-specific interactions under physiological conditions display the least repulsive self-interactions in standard formulations. This behavior can be largely explained by the antibody isoelectric point, as highly basic antibodies that are highly positively charged under standard formulation conditions (pH 5-6) promote repulsive self-interactions that mediate high colloidal stability but also mediate strong non-specific interactions with negatively charged biomolecules at physiological pH and vice versa for antibodies with negatively charged Fv regions. Therefore, IgG1s with weakly basic isoelectric points between 8 and 8.5 and Fv isoelectric points between 7.5 and 9 typically display the best combinations of strong repulsive self-interactions and weak non-specific interactions. We expect that these findings will improve the identification and engineering of antibody candidates with drug-like biophysical properties.

Minimal Physiologically-based Pharmacokinetic Model to Investigate the Effect of Charge on the Pharmacokinetics of Humanized anti-HCV-E2 IgG Antibodies in Sprague-Dawley Rats.

PURPOSE: To develop a minimal physiologically-based pharmacokinetic (mPBPK) model in quantifying the relationships between the charge and pharmacokinetics (PK) of therapeutic monoclonal IgG antibody (TMAb). METHODS: PK data used in this study were native IgG and five humanized anti-HCVE2-IgG antibodies in rats. Different models that related the effect of charge on interstitial distribution, transcapillary transport, and cellular uptake for FcRn-mediated metabolism were tested. External validation was conducted to assess if the charge-parameter relationships derived from rats could be used to predict the PK of TMAbs in mice. The final mPBPK model was used to construct the relationships between the FcRn binding and charge on the PK of TMAbs. RESULTS: Increasing the isoelectric point (pI) of IgG was associated with higher interstitial space distribution and cellular uptake. The transcapillary transport of IgG from plasma to interstitial space remains constant with pI values below 7.96 and then increased linearly with pI. The model-based simulation results suggested that improving the FcRn binding affinity can overcome the problems of low plasma/interstitial space exposures associated with TMAbs with higher pI values by reducing the FcRn-mediated metabolism and hence increasing drug exposure in the interstitial space that has close contact with many solid tumors. CONCLUSIONS: The final mPBPK model was developed and used to construct complex quantitative relationships between the pI/FcRn binding affinity and PK of TMAbs and such relationships are useful to select the discovery of a "sweet spot" of designing future generation of TMAbs with optimal PK properties to achieve desirable plasma and tissue drug exposures.

Virus Isoelectric Point Estimation: Theories and Methods.

Much of virus fate, both in the environment and in physical/chemical treatment, is dependent on electrostatic interactions. Developing an accurate means of predicting virion isoelectric point (pI) would help to understand and anticipate virus fate and transport, especially for viruses that are not readily propagated in the lab. One simple approach to predicting pI estimates the pH at which the sum of charges from ionizable amino acids in capsid proteins approaches zero. However, predicted pIs based on capsid charges frequently deviate by several pH units from empirically measured pIs. Recently, the discrepancy between empirical and predicted pI was attributed to the electrostatic neutralization of predictable polynucleotide-binding regions (PBRs) of the capsid interior. In this paper, we review models presupposing (i) the influence of the viral polynucleotide on surface charge or (ii) the contribution of only exterior residues to surface charge. We then compare these models to the approach of excluding only PBRs and hypothesize a conceptual electrostatic model that aligns with this approach. The PBR exclusion method outperformed methods based on three-dimensional (3D) structure and accounted for major discrepancies in predicted pIs without adversely affecting pI prediction for a diverse range of viruses. In addition, the PBR exclusion method was determined to be the best available method for predicting virus pI, since (i) PBRs are predicted independently of the impact on pI, (ii) PBR prediction relies on proteome sequences rather than detailed structural models, and (iii) PBR exclusion was successfully demonstrated on a diverse set of viruses. These models apply to nonenveloped viruses only. A similar model for enveloped viruses is complicated by a lack of data on enveloped virus pI, as well as uncertainties regarding the influence of the phospholipid envelope on charge and ion gradients.

Isoelectric point determination by imaged CIEF of commercially available SARS-CoV-2 proteins and the hACE2 receptor.

In order to contribute to the scientific research on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we have investigated the isoelectric points (pI) of several related proteins, which are commercially available: the receptor-binding domain (RBD) with His- and Fc-tag, the S1 subunit with His-tag, the S1/S2 subunits with His-tag and the human angiotensin-converting enzyme 2 (hACE2) with His-tag. First, the theoretical pI values, based on the amino acid (AA) sequences of the proteins, were calculated using the ProtParam tool from the Bioinformatics Resource Portal ExPASy. The proteins were then measured with the Maurice imaged CIEF system (native fluorescence detection), testing various measurement conditions, such as different ampholytes or ampholyte mixtures. Due to isoforms, we get sections with several peaks and not just one peak for each protein. The determined pI range for the RBD/Fc is 8.24-9.32 (theoretical pI: 8.55), for the RBD/His it is 7.36-9.88 (8.91) and for the S1/His it is 7.30-8.37 (7.80). The pI range of the S1/S2/His is 4.41-5.87 (no theoretical pI, AA sequence unknown) and for hACE2/His, the determined global range is 5.19-6.11 (5.60) for all experimental conditions chosen. All theoretically derived values were found within these ranges, usually close to the center. Therefore, we consider theoretical values as useful to make predictions about the isoelectric points of SARS-CoV-2 proteins. The experimental conditions had only a minor influence on the pI ranges obtained and mainly influenced the peak shapes.

Impact of the isoelectric point of model parvoviruses on viral retention in anion-exchange chromatography.

Anion-exchange chromatography (AEX) is used in the downstream purification of monoclonal antibodies to remove impurities and potential viral contamination based on electrostatic interactions. Although the isoelectric point (pI) of viruses is considered a key factor predicting the virus adsorption to the resin, the precise molecular mechanisms involved remain unclear. To address this question, we compared structurally homologous parvoviruses that only differ in their surface charge distribution. A single charged amino acid substitution on the capsid surface of minute virus of mice (MVM) provoked an increased apparent pI (pIapp ) 6.2 compared to wild-type MVM (pIapp = 4.5), as determined by chromatofocusing. Despite their radically different pIapp , both viruses displayed the same interaction profile in Mono Q AEX at different pH conditions. In contrast, the closely related canine parvovirus (pIapp = 5.3) displayed a significantly different interaction at pH 5. The detailed structural analysis of the intricate three-dimensional structure of the capsids suggests that the charge distribution is critical, and more relevant than the pI, in controlling the interaction of a virus with the chromatographic resin. This study contributes to a better understanding of the molecular mechanisms governing virus clearance by AEX, which is crucial to enable robust process design and maximize safety.