Protein charge parameters that influence stability and cellular internalization of polyelectrolyte complex micelles

Proteins are an important class of biologics, but there are several recurring challenges to address when designing protein-based therapeutics. These challenges include: the propensity of proteins to aggregate during formulation, relatively low loading in traditional hydrophobic delivery vehicles, and inefficient cellular uptake. This last criterion is particularly challenging for anionic proteins as they cannot cross the anionic plasma membrane. Here we investigated the complex coacervation of anionic proteins with a block copolymer of opposite charge to form polyelectrolyte complex (PEC) micelles for use as a protein delivery vehicle. Using genetically modified variants of the model protein green fluorescent protein (GFP), we evaluated the role of protein charge and charge localization in the formation and stability of PEC micelles. A neutral-cationic block copolymer, POEGMA79-b-qP4VP175, was prepared via RAFT polymerization for complexation and microphase separation with the panel of engineered anionic GFPs. We found that isotropically supercharged proteins formed micelles at higher ionic strength relative to protein variants with charge localized to a polypeptide tag. We then studied GFP delivery by PEC micelles and found that they effectively delivered the protein cargo to mammalian cells. However, cellular delivery varied as a function of protein charge and charge distribution and we found an inverse relationship between the PEC micelle critical salt concentration and delivery efficiency. This model system has highlighted the potential of polyelectrolyte-complexes to deliver anionic proteins intracellularly as well as the importance of correlating solution structure and desired functional activity.

Relationship between monomer packing and receptor binding domain pocket status in the spike trimer of SARS-CoV-2 variants

Existence of a SARS-CoV-2 spike protein trimer form with closer packing between monomers when receptor binding domains (RBDs) are all down, locked as opposed to closed, has been associated with linoleic acid (LA) binding at neutral pH, or can occur at acidic pH in the absence of LA binding. The relationship between degree of closure of the LA binding pocket of the RBD, and monomer burial in the trimer, is examined for a range of spike protein structures, including those with D614G mutation, and that of the Delta variant (which also carries D614G). Some spike protein structures with this aspartic acid mutation show monomer packing approaching that of the locked form (at neutral pH, without LA binding) for two segments, a third (around the RBD) remains less closely packed. Analysis of other coronavirus RBD structures suggests that mutation of the RBD in spike protein of the Omicron variant could lead to LA binding pocket changes. It is proposed that these changes could lead to one of two consequences for the Omicron variant spike protein (which also has the D614G mutation), at neutral pH and without LA binding, either easier access to a locked form throughout that leads to cooperative transitions between all RBD down and all RBD up, or maintenance of a spike trimer with locked characteristics C-terminal to the RBD at the same time as the RBD is free to transit between down and up states. The situation may also be impacted by spike protein charge mutations in the Omicron lineage that alter pH-dependence around the RBD, in a similar way to the changes induced elsewhere by D614G.

Semicovariance Coefficient Analysis of Spike Proteins from SARS-CoV-2 and Other Coronaviruses for Viral Evolution and Characteristics Associated with Fatality

Complex modeling has received significant attention in recent years and is increasingly used to explain statistical phenomena with increasing and decreasing fluctuations, such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which results in a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID databases, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains from Wuhan, Beijing, New York, German, and the UK variant B.1.1.7) which were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2, which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses, suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolution of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS > SARS-CoV-1 > SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

The Effects of Protein Charge Patterning on Complex Coacervation

The complex coacervation of proteins with other macromolecules has applications in protein encapsulation and delivery and for determining the function of cellular coacervates. Theoretical or empirical predictions for protein coacervates would enable the design of these coacervates with tunable and predictable structure-function relationships; unfortunately, no such theories exist. To help establish predictive models, the impact of protein-specific parameters on complex coacervation were probed in this study. The complex coacervation of sequence-specific, polypeptide-tagged, GFP variants and a strong synthetic polyelectrolyte was used to evaluate the effects of protein charge patterning on phase behavior. Phase portraits for the protein coacervates demonstrated that charge patterning dictates the protein’s binodal phase boundary. Protein concentrations over 100 mg mL^-1 were achieved in the coacervate phase, with concentrations dependent on the polypeptide sequence. In addition to shifting the binodal phase boundary, polypeptide charge patterning provided entropic advantages over isotropically patterned proteins. Together, these results show that modest changes of only a few amino acids alter the coacervation thermodynamics and can be used to tune the phase behavior of polypeptides or proteins of interest.

The Effects of Protein Charge Patterning on Complex Coacervation

The complex coacervation of proteins with other macromolecules has applications in protein encapsulation and delivery and for determining the function of cellular coacervates. Theoretical or empirical predictions for protein coacervates would enable the design of these coacervates with tunable and predictable structure-function relationships; unfortunately, no such theories exist. To help establish predictive models, the impact of protein-specific parameters on complex coacervation were probed in this study. The complex coacervation of sequence-specific, polypeptide-tagged, GFP variants and a strong synthetic polyelectrolyte was used to evaluate the effects of protein charge patterning on phase behavior. Phase portraits for the protein coacervates demonstrated that charge patterning dictates the protein’s binodal phase boundary. Protein concentrations over 100 mg mL^-1 were achieved in the coacervate phase, with concentrations dependent on the polypeptide sequence. In addition to shifting the binodal phase boundary, polypeptide charge patterning provided entropic advantages over isotropically patterned proteins. Together, these results show that modest changes of only a few amino acids alter the coacervation thermodynamics and can be used to tune the phase behavior of polypeptides or proteins of interest.

Semi-Covariance Coefficient Analysis of Spike Proteins from SARS-CoV-2 and other Coronaviruses for Viral Evolution and Characteristics Associated with Fatality

Complex modeling has received significant attention in recent years and is increasingly used to explain the statistical phenomenon with increasing and decreasing fluctuations such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which ends up a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID database, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains of Wuhan, Beijing, New York, German, and UK variant B.1.1.7) were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2 for which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolvement of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS>SARS-CoV-1>SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

The effects of protein charge patterning on complex coacervation

Charge patterned polypeptides modulate the complex coacervation of globular proteins with polymers. These protein coacervates have applications in protein encapsulation and delivery and in determining the function of biomolecular condensates.