Isoelectric points of proteins: theoretical determination

Utility of Cellular Measurements of Non-Specific Endocytosis to Assess the Target-Independent Clearance of Monoclonal Antibodies

Past studies have demonstrated higher clearance for monoclonal antibodies possessing increased rates of non-specific endocytosis. However, this metric is oftentimes evaluated indirectly using biophysical techniques or cell surface binding studies that may not provide insight into the specific rates of cellular turnover. Furthermore, few examples evaluating non-specific endocytosis have been reported for a therapeutic antibody that reached clinical assessment. In the current report, we evaluated a therapeutic human immunoglobulin G2 monoclonal antibody targeted against the interleukin-4 receptor alpha chain (IL-4Rα) that exhibited elevated target independent clearance in previous Phase 1 and 2 studies. We confirmed high non-specific clearance of the anti-IL-4Rα antibody as compared to a reference antibody during pharmacokinetic assessments in wild type mice where target-mediated disposition was absent. We then developed a cell-based method capable of measuring cellular protein endocytosis and demonstrated the anti-IL-4Rα antibody exhibited marked non-specific uptake relative to the reference compound. Antibody homology modeling identified the anti-IL-4Rα antibody possessed positive charge patches whose removal via targeted mutations substantially reduced its non-specific endocytosis. We then expanded the scope of the study by evaluating panels of both preclinical and clinically relevant monoclonal antibodies and demonstrate those with the highest rates of non-specific uptake in vitro exhibited elevated target independent clearance, low subcutaneous bioavailability, or both. Our results support the observation that high non-specific endocytosis is a negative attribute in monoclonal antibody development and demonstrate the utility of a generic cell-based screen as a quantitative tool to measure non-specific endocytosis of protein therapeutics at the single-cell level.

AbMelt: Learning antibody thermostability from molecular dynamics

Antibody thermostability is challenging to predict from sequence and/or structure. This difficulty is likely due to the absence of direct entropic information. Herein, we present AbMelt where we model the inherent flexibility of homologous antibody structures using molecular dynamics simulations at three temperatures and learn the relevant descriptors to predict the temperatures of aggregation (Tagg), melt onset (Tm,on), and melt (Tm). We observed that the radius of gyration deviation of the complementarity determining regions at 400 K is the highest Pearson correlated descriptor with aggregation temperature (rp = -0.68 ± 0.23) and the deviation of internal molecular contacts at 350 K is the highest correlated descriptor with both Tm,on (rp = -0.74 ± 0.04) as well as Tm (rp = -0.69 ± 0.03). Moreover, after descriptor selection and machine learning regression, we predict on a held-out test set containing both internal and public data and achieve robust performance for all endpoints compared with baseline models (Tagg R2 = 0.57 ± 0.11, Tm,on R2 = 0.56 ± 0.01, and Tm R2 = 0.60 ± 0.06). In addition, the robustness of the AbMelt molecular dynamics methodology is demonstrated by only training on <5% of the data and outperforming more traditional machine learning models trained on the entire data set of more than 500 internal antibodies. Users can predict thermostability measurements for antibody variable fragments by collecting descriptors and using AbMelt, which has been made available.

AbLEF: antibody language ensemble fusion for thermodynamically empowered property predictions

MOTIVATION

Pre-trained protein language and/or structural models are often fine-tuned on drug development properties (i.e. developability properties) to accelerate drug discovery initiatives. However, these models generally rely on a single structural conformation and/or a single sequence as a molecular representation. We present a physics-based model, whereby 3D conformational ensemble representations are fused by a transformer-based architecture and concatenated to a language representation to predict antibody protein properties. Antibody language ensemble fusion enables the direct infusion of thermodynamic information into latent space and this enhances property prediction by explicitly infusing dynamic molecular behavior that occurs during experimental measurement.

RESULTS

We showcase the antibody language ensemble fusion model on two developability properties: hydrophobic interaction chromatography retention time and temperature of aggregation (Tagg). We find that (i) 3D conformational ensembles that are generated from molecular simulation can further improve antibody property prediction for small datasets, (ii) the performance benefit from 3D conformational ensembles matches shallow machine learning methods in the small data regime, and (iii) fine-tuned large protein language models can match smaller antibody-specific language models at predicting antibody properties.

AVAILABILITY AND IMPLEMENTATION

AbLEF codebase is available at https://github.com/merck/AbLEF.

The biomolecular gastrointestinal corona in oral drug delivery

The formation of a biomolecular corona on exogenous particles in plasma is well studied and is known to dictate the biodistribution and cellular interactions of nanomedicine formulations. In contrast, while the oral route is the most favorable administration method for pharmaceuticals, little is known about the formation and composition of the corona formed by biomolecules on particles within the gastrointestinal tract. This work reviews the current literature understanding of (1) the formation of drug particles after oral administration, (2) the formation of a biomolecular corona within the gastrointestinal tract ("the gastrointestinal corona"), and (3) the possible implications of the formation of a gastrointestinal corona on the interactions of drug particles with their biological environment. In doing so, this work aims to establish the significance of the formation of a gastrointestinal corona in oral drug delivery to ultimately arrive at new avenues to control the behavior of orally administered pharmaceuticals.

Polyzwitterionic micelles with antimicrobial-conjugation for eradication of drug-resistant bacterial biofilms

The presence of bacterial biofilms has presented a significant challenge to human health. This study presents the development of biofilm microenvironment-responsive polymeric micelles as a novel approach to address the challenges posed by bacterial biofilms. These micelles are composed of two key components: a zwitterionic component, inspired by protein isoelectric points, containing balanced quantities of primary amines and carboxylic groups that undergo a positive charge transformation in acidic microenvironments, and a hydrophobic triclosan conjugate capable of releasing triclosan in the presence of bacterial lipases. Through the synergistic combination of pH-responsiveness and lipase-responsiveness, we have significantly improved drug penetration into biofilms and enhanced its efficacy in killing bacteria. With their remarkable drug-loading capacity and the ability to specifically target and eliminate bacteria within biofilms, these zwitterionic polymeric micelles hold great promise as an effective alternative for treating biofilm-associated infections. Their unique properties enable efficient drug delivery and heightened effectiveness against biofilm-related infections.

An overview of descriptors to capture protein properties - Tools and perspectives in the context of QSAR modeling

Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.

The Ionization of Polymeric Materials Accelerates Protein Deposition on Hydrogel Contact Lens Material

Contact lens materials include polymers that are ionized in the ocular pH condition and are susceptible to protein deposition due to their surface characteristics. Herein, we investigated the effect of the electrostatic state of the contact lens material and protein on protein deposition level using hen egg white lysozyme (HEWL) and bovine serum albumin (BSA) as model proteins and etafilcon A and hilafilcon B as model contact lens materials. Only HEWL deposition on etafilcon A showed a statistically significant pH-dependency (p < 0.05); protein deposition increased with pH. HEWL showed a positive zeta potential at acidic pH, while BSA showed a negative zeta potential at basic pH. Only etafilcon A showed a statistically significant pH-dependent point of zero charge (PZC) (p < 0.05), implying that its surface charge became more negative under basic conditions. This pH-dependency of etafilcon A is attributed to the pH-responsive degree of ionization of its constituent methacrylic acid (MAA). The presence of MAA and its degree of ionization could accelerate protein deposition; more HEWL deposited as pH increased despite the weak positive surface charge of HEWL. The highly negatively charged etafilcon A surface attracted HEWL, even overwhelming weak positive charge of HEWL, increasing the deposition with pH.

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.

Pharmacokinetic Developability and Disposition Profiles of Bispecific Antibodies: A Case Study with Two Molecules

Bispecific antibodies (BsAb) that engage multiple pathways are a promising therapeutic strategy to improve and prolong the efficacy of biologics in complex diseases. In the early stages of discovery, BsAbs often exhibit a broad range of pharmacokinetic (PK) behavior. Optimization of the neonatal Fc receptor (FcRn) interactions and removal of undesirable physiochemical properties have been used to improve the 'pharmacokinetic developability' for various monoclonal antibody (mAb) therapeutics, yet there is a sparsity of such information for BsAbs. The present work evaluated the influence of FcRn interactions and inherent physiochemical properties on the PK of two related single chain variable fragment (scFv)-based BsAbs. Despite their close relation, the two BsAbs exhibit disparate PK in cynomolgus monkeys with BsAb-1 having an aberrant clearance of ~2 mL/h/kg and BsAb-2 displaying a an ~10-fold slower clearance (~0.2 mL/h/kg). Evaluation of the physiochemical characteristics of the molecules, including charge, non-specific binding, thermal stability, and hydrophobic properties, as well as FcRn interactions showed some differences. In-depth drug disposition results revealed that a substantial disparity in the complete release from FcRn at a neutral pH is a primary factor contributing to the rapid clearance of the BsAb-1 while other biophysical characteristics were largely comparable between molecules.

Protein pI and Intracellular Localization

The protein isoelectric point (pI) can be calculated from an amino acid sequence using computational analysis in a good agreement with experimental data. Availability of whole-genome sequences empowers comparative studies of proteome-wide pI distributions. It was found that the whole-proteome distributions of protein pI values are multimodal in different species. It was further hypothesized that the observed multimodality is associated with subcellular localization-specific differences in local pI distributions. Here, we overview the multimodality of proteome-wide pI distributions in different organisms focusing on the relationships between protein pI and subcellular localization. We also discuss the probable factors responsible for variation of the intracellular localization-specific pI profiles.

Impact of IgG subclass on molecular properties of monoclonal antibodies

Immunoglobulin G-based monoclonal antibodies (mAbs) have become a dominant class of biotherapeutics in recent decades. Approved antibodies are mainly of the subclasses IgG1, IgG2, and IgG4, as well as their derivatives. Over the decades, the selection of IgG subclass has frequently been based on the needs of Fc gamma receptor engagement and effector functions for the desired mechanism of action, while the effect on drug product developability has been less thoroughly characterized. One of the major reasons is the lack of systematic understanding of the impact of IgG subclass on the molecular properties. Several efforts have been made recently to compare molecular property differences among these IgG subclasses, but the conclusions from these studies are sometimes obscured by the interference from variable regions. To further establish mechanistic understandings, we conducted a systematic study by grafting three independent variable regions onto human IgG1, an IgG1 variant, IgG2, and an IgG4 variant constant domains and evaluating the impact of subclass and variable regions on their molecular properties. Structural and computational analysis revealed specific molecular features that potentially account for the differential behavior of the IgG subclasses observed experimentally. Our data indicate that IgG subclass plays a significant role on molecular properties, either through direct effects or via the interplay with the variable region, the IgG1 mAbs tend to have higher solubility than either IgG2 or IgG4 mAbs in a common pH 6 buffer matrix, and solution behavior relies heavily on the charge status of the antibody at the desirable pH.

Virtual 2D mapping of the viral proteome reveals host-specific modality distribution of molecular weight and isoelectric point

A proteome-wide study of the virus kingdom based on 1.713 million protein sequences from 19,128 virus proteomes was conducted to construct an overall proteome map of the virus kingdom. Viral proteomes encode an average of 386.214 amino acids per protein with the variation in the number of protein-coding sequences being host-specific. The proteomes of viruses of fungi hosts (882.464) encoded the greatest number of amino acids, while the viral proteome of bacterial host (210.912) encoded the smallest number of amino acids. Viral proteomes were found to have a host-specific amino acid composition. Leu (8.556%) was the most abundant and Trp (1.274%) the least abundant amino acid in the collective proteome of viruses. Viruses were found to exhibit a host-dependent molecular weight and isoelectric point of encoded proteins. The isoelectric point (pI) of viral proteins was found in the acidic range, having an average pI of 6.89. However, the pI of viral proteins of algal (pI 7.08) and vertebrate (pI 7.09) hosts was in the basic range. The virtual 2D map of the viral proteome from different hosts exhibited host-dependent modalities. The virus proteome from algal hosts and archaea exhibited a bimodal distribution of molecular weight and pI, while the virus proteome of bacterial host exhibited a trimodal distribution, and the virus proteome of fungal, human, land plants, invertebrate, protozoa, and vertebrate hosts exhibited a unimodal distribution.

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 (pK_a) of charged groups of seven amino acids and NH⁺ and COO⁻ groups at polypeptide termini. Information regarding isoelectric point and pK_a 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 pK_a values. In this paper, I present Isoelectric Point Calculator 2.0 (IPC 2.0), a web server for the prediction of isoelectric points and pK_a 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 pK_a 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

Neuroinvasiveness of the MR766 strain of Zika virus in IFNAR-/- mice maps to prM residues conserved amongst African genotype viruses

Zika virus (ZIKV) strains are classified into the African and Asian genotypes. The higher virulence of the African MR766 strain, which has been used extensively in ZIKV research, in adult IFNα/β receptor knockout (IFNAR-/-) mice is widely viewed as an artifact associated with mouse adaptation due to at least 146 passages in wild-type suckling mouse brains. To gain insights into the molecular determinants of MR766's virulence, a series of genes from MR766 were swapped with those from the Asian genotype PRVABC59 isolate, which is less virulent in IFNAR-/- mice. MR766 causes 100% lethal infection in IFNAR-/- mice, but when the prM gene of MR766 was replaced with that of PRVABC59, the chimera MR/PR(prM) showed 0% lethal infection. The reduced virulence was associated with reduced neuroinvasiveness, with MR766 brain titers ≈3 logs higher than those of MR/PR(prM) after subcutaneous infection, but was not significantly different in brain titers of MR766 and MR/PR(prM) after intracranial inoculation. MR/PR(prM) also showed reduced transcytosis when compared with MR766 in vitro. The high neuroinvasiveness of MR766 in IFNAR-/- mice could be linked to the 10 amino acids that differ between the prM proteins of MR766 and PRVABC59, with 5 of these changes affecting positive charge and hydrophobicity on the exposed surface of the prM protein. These 10 amino acids are highly conserved amongst African ZIKV isolates, irrespective of suckling mouse passage, arguing that the high virulence of MR766 in adult IFNAR-/- mice is not the result of mouse adaptation.

Identifying biophysical assays and in silico properties that enrich for slow clearance in clinical-stage therapeutic antibodies

Understanding the pharmacokinetic (PK) properties of a drug, such as clearance, is a crucial step for evaluating efficacy. The PK of therapeutic antibodies can be complex and is influenced by interactions with the target, Fc-receptors, anti-drug antibodies, and antibody intrinsic factors. A growing body of literature has linked biophysical properties of antibodies, particularly nonspecific-binding propensity, hydrophobicity and charged regions to rapid clearance in preclinical species and selected human PK studies. A clear understanding of the connection between biophysical properties and their impact on PK would allow for early selection and optimization of antibodies and reduce costly attrition during clinical trials due to sub-optimal human clearance. Due to the difficulty in obtaining large and unbiased human PK data, previous studies have focused mostly on preclinical PK. For this study, we obtained and curated the most comprehensive clinical PK dataset to date and calculated accurate estimates of linear clearance for 64 monoclonal antibodies ranging from investigational candidates in Phase 2 trials to marketed products. This allows for the first time a deep analysis of the influence of biophysical and sequence-based in silico properties directly on human clearance. We use statistical analysis and a Random Forest classifier to identify properties that have the greatest influence in our dataset. Our findings indicate that in vitro poly-specificity assay and in silico estimated isoelectric point can discriminate fast and slow clearing antibodies, extending previous observations on preclinical clearance. This provides a simple yet powerful approach to select antibodies with desirable PK during early-stage screening.

Coupling of RAFT polymerization and chemoselective post-modifications of elastin-like polypeptides for the synthesis of gene delivery hybrid vectors

Hybrid cationic ELPs for nucleic acids transport and delivery were synthetized through the coupling of RAFT polymerization and biorthogonal chemistry of ELPs, introducing a specific number of positive charges to the ELP backbone.

Preparation, characterization, and Cd(II) sorption of/on cysteine-montmorillonite composites synthesized at various pH

Montmorillonite-cysteine could be used as the immobilizer, detector, and detoxifier of heavy metals. To further the understanding and the application, the interaction between the montmorillonite and cysteine and the adsorption of cysteine on montmorillonite and characterization of the composites need to be studied further. In present work, the effects of pH, contact time and initial concentration of cysteine on the adsorption, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Cd(II) adsorption on the composites were conducted to characterize the composites synthesized at different pH conditions. The results showed that the adsorption amount of cysteine on montmorillonite decreased with the increase of pH in the range of 2.4-8.0, reached equilibrium in about 1 min and increased with the initial concentration of cysteine and reached the maximum at 160 mg/g. The adsorption data fitted with Langmuir better than Freundlich, fitted with first-order and second-order better than the intraparticle diffusion model. XRD patterns and FTIR spectra showed that the interlayer spacing of the composite synthesized in the range of pH 2.4-4.3 was larger than that at pH 4.5-8.0 and the bonding of cysteine and montmorillonite mainly depended on the action of the amino group. Adsorption of Cd(II) on composites indicated more cysteine loaded (pH < 4.5) composite had greater capacity for Cd(II). The above results demonstrated that the composite synthesized under lower pH could retain more active cysteine, which might be beneficial to its various applications.

Accurate Estimation of pKb Values for Amino Groups from Surface Electrostatic Potential (VS,min) Calculations: The Isoelectric Points of Amino Acids as a Case Study

Theoretical calculation of equilibrium dissociation constants is a very computationally demanding and time-consuming process since it requires an extremely accurate computation of the solvation free energy changes for each of the species involved. By correlating the minimum surface electrostatic potential (V_S,min) on the nitrogen atom of several aliphatic amino groups-calculated at the density functional theory (DFT) ωB97X-D/cc-pVDZ level of theory-we obtained regression models for each kind of substitution pattern from which we interpolate their corresponding pK_b values with remarkable accuracy: primary R² = 0.9519; secondary R² = 0.9112; and tertiary R² = 0.8172 (N = 20 for each family). These models were validated with tests sets (N = 5) with mean absolute error (MAE) values of 0.1213 (primary), 0.4407 (secondary), and 0.3057 (tertiary). Combining this ansatz with another previously reported by our group to estimate pK_a values [Caballero-García, G.; et al. Molecules 2019, 24(1), 79] we are able to reproduce the isoelectric points of 13 amino acids with no titrable side chains with MAE = 0.4636 pI units.

Electrostatic Surface Potential of Macrophages Correlates with Their Functional Phenotype

Macrophages exist in various functional phenotypes, which could be identified by specific surface molecules. Previous studies have shown that modulation of surface charges could alter the phagocytic function of macrophages. In this study, we show that activation of both human peripheral blood monocyte and THP-1-derived macrophages with lipopolysaccharide (LPS) or IL-1β resulted in a significant decrease in the zeta potential compared to freshly isolated monocytes and unstimulated macrophages. Interestingly, interaction with bacteria significantly increased the zeta potential of such cells irrespective of activation conditions. Similarly, IFNγ-treated pro-inflammatory macrophages showed lesser negative zeta potential compared to untreated control. A moderate reduction was also seen in IL-4-treated anti-inflammatory subtype. Additionally, in an LPS-induced systemic inflammation model, bone marrow cells isolated after 2 h of LPS injection showed significant reduction in zeta potential compared to naïve cells. Furthermore, electrostatic potential measurement of surface proteins associated with pro-inflammatory and anti-inflammatory macrophages, using in silico modeling under physiological and protonation conditions, showed that the average electrostatic potential of pro-inflammatory type surface proteins was less negative than anti-inflammatory subtype. These data suggest that the expression of different protein molecules on macrophages under different environments may contribute to the zeta potential and that this quick and low-cost technique could be used in monitoring macrophage functional phenotypes.

Effect of Stabilizers on Encapsulation Efficiency and Release Behavior of Exenatide-Loaded PLGA Microsphere Prepared by the W/O/W Solvent Evaporation Method

The aim of this study was to investigate the effects of various stabilizers on the encapsulation efficiency and release of exenatide-loaded PLGA (poly(lactic-co-glycolic acid)) microspheres prepared by the water-in-oil-in-water (W/O/W) solvent evaporation (SE) method. It was shown that the stabilizers affected exenatide stability in aqueous solutions, at water/dichloromethane interfaces, on PLGA surfaces, or during freeze-thawing and freeze-drying procedures. Sucrose predominantly reduces instability generated during freeze-thawing and freeze-drying. Phenylalanine prevents the destabilization at the water-dichloromethane (DCM) interface through decreased adsorption. Poloxamer 188 enhances stability in aqueous solutions and prevents adsorption to PLGA. Proline and lysine decrease adsorption on PLGA surfaces. Fourier transform infra-red spectroscopy (FT-IR) was used to find the molecular interaction of additives with exenatide or PLGA. Additives used in stability assessments were then added stepwise into the inner or outer water phase of the W/O/W double emulsion, and exenatide-loaded microspheres were prepared using the solvent evaporation method. The effect of each stabilizer on the encapsulation efficiency and release behavior of microspheres correlated well with the stability assessment results, except for the negative effect of poloxamer 188. Particle size analysis using laser diffractometry, scanning electron microscopy (SEM), water vapor sorption analysis, differential scanning calorimetry (DSC), and circular dichroism (CD) spectroscopy were also employed to characterize the prepared exenatide-loaded PLGA microsphere. This study demonstrated that an adequate formulation can be obtained by the study about the effect of stabilizers on peptide stability at the preformulation step. In addition, it can help to overcome various problems that can cause the destabilization of a peptide during the microsphere-manufacturing process and sustained drug release.

Insights into the behavior of six rationally designed peptides based on Escherichia coli's OmpA at the water-dodecane interface

The Escherichia coli's membrane protein OmpA has been identified as a potential biosurfactant due to their amphiphilic nature, and their capacity to stabilize emulsions of dodecane in water. In this study, the influence of surfactant type, concentration, preservation time and droplet size on the crystallization of n-dodecane and water, in oil-in-water emulsions stabilized with six rationally designed Escherichia coli's OmpA-based peptides was investigated. A differential scanning calorimetry (DSC) protocol was established using emulsions stabilized with Tween 20® and Tween 80®. A relationship between the surfactant concentration and the crystallization temperatures of n-dodecane and water was observed, where the crystallization temperatures seem to be dependent on the preservation time. A deconvolution analysis shows that the peak morphology possibly depends on the interactions at the interface because the enthalpic contributions of each Gaussian peak remained similar in emulsions stabilized with the same peptide. Adsorption results show that the main driver for adsorption and thus stabilization of emulsions is polar interactions (e.g. H-bonding) through the hydrophilic parts of the peptides. Those peptides with a preponderance of polar interaction groups distribution (i.e. NH2, COOH, imidazole) showed the highest interfacial activity under favorable pH conditions. This suggests that custom-made peptides whose hydrophilic/hydrophobic regions can be fine-tuned depending on the application can be easily produced with the additional advantage of their biodegradable nature.

The molecular mass and isoelectric point of plant proteomes

Background

Cell contain diverse array of proteins with different molecular weight and isoelectric point (pI). The molecular weight and pI of protein play important role in determining the molecular biochemical function. Therefore, it was important to understand the detail regarding the molecular weight and pI of the plant proteins.

Results

A proteome-wide analysis of plant proteomes from 145 species revealed a pI range of 1.99 (epsin) to 13.96 (hypothetical protein). The spectrum of molecular mass of the plant proteins varied from 0.54 to 2236.8 kDa. A putative Type-I polyketide synthase (22244 amino acids) in Volvox carteri was found to be the largest protein in the plant kingdom. However, Type-I polyketide synthase was not found in higher plant species. Titin (806.46 kDa) and misin/midasin (730.02 kDa) were the largest proteins identified in higher plant species. The pI and molecular weight of the plant proteins showed a trimodal distribution. An acidic pI (56.44% of proteins) was found to be predominant over a basic pI (43.34% of proteins) and the abundance of acidic pI proteins was higher in unicellular algae species relative to multicellular higher plants. In contrast, the seaweed, Porphyra umbilicalis, possesses a higher proportion of basic pI proteins (70.09%). Plant proteomes were also found to contain selenocysteine (Sec), amino acid that was found only in lower eukaryotic aquatic plant lineage. Amino acid composition analysis showed Leu was high and Trp was low abundant amino acids in the plant proteome. Additionally, the plant proteomes also possess ambiguous amino acids Xaa (unknown), Asx (asparagine or aspartic acid), Glx (glutamine or glutamic acid), and Xle (leucine or isoleucine) as well.

Conclusion

The diverse molecular weight and isoelectric point range of plant proteome will be helpful to understand their biochemical and functional aspects. The presence of selenocysteine proteins in lower eukaryotic organism is of interest and their expression in higher plant system can help us to understand their functional role.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5983-8) contains supplementary material, which is available to authorized users.

Marginal protein stability drives subcellular proteome isoelectric point

There exists a positive correlation between the pH of subcellular compartments and the median isoelectric point (pI) for the associated proteomes. Proteins in the human lysosome-a highly acidic compartment in the cell-have a median pI of ∼6.5, whereas proteins in the more basic mitochondria have a median pI of ∼8.0. Proposed mechanisms reflect potential adaptations to pH. For example, enzyme active site general acid/base residue pKs are likely evolved to match environmental pH. However, such effects would be limited to a few residues on specific proteins, and might not affect the proteome at large. A protein model that considers residue burial upon folding recapitulates the correlation between proteome pI and environmental pH. This correlation can be fully described by a neutral evolution process; no functional selection is included in the model. Proteins in acidic environments incur a lower energetic penalty for burying acidic residues than basic residues, resulting in a net accumulation of acidic residues in the protein core. The inverse is true under alkaline conditions. The pI distributions of subcellular proteomes are likely not a direct result of functional adaptations to pH, but a molecular spandrel stemming from marginal stability.

The Prismatic Layer of Pinna: A Showcase of Methodological Problems and Preconceived Hypotheses

The prismatic layer of Pinna (Mollusca) is one of the most studied models for the understanding of the biomineralization mechanisms, but our knowledge of the organic components of this layer is limited to the proteins of the soluble organic matrices. The interplay of the mineral and organic matrices is studied using scanning electron and atomic force microscopy, infra-red spectrometry, thermogravimetric analyses, aminoacids analyses, thin layer chromatography (TLC), X-ray fluorescence, X-ray Absorption near Edge Structure (XANES) and time-of-flight secondary ion mass spectrometry (TOF-SIMS). Proteins, polysaccharides and lipids are detected within the prisms and their envelopes. The role of the technical choices to study calcareous biominerals is evidenced, showing that a single analysis is not enough to decipher complex biominerals.

Design of a software for calculating isoelectric point of a polypeptide according to their net charge using the graphical programming language LabVIEW

A software to calculate the net charge and to predict the isoelectric point (pI) of a polypeptide is developed in this work using the graphical programming language LabVIEW. Through this instrument the net charges of the ionizable residues of the polypeptide chains of the proteins are calculated at different pH values, tabulated, pI is predicted and an Excel (-xls) type file is generated. In this work, the experimental values of the pIs (pI) of different proteins are compared with the values of the pIs (pI) calculated graphically, achieving a correlation coefficient (R) of 0.934746 which represents a good reliability for a p < 0.01. In this way the generated program can constitute an instrument applicable in the laboratory, facilitating the calculation to graduate students and junior researchers. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):39-46, 2018.

TAI vacuolar invertase orthologs: the interspecific variability in tomato plants (Solanum section Lycopersicon)

Understanding the genetic mechanisms underlying carbohydrate metabolism can promote the development of biotechnological advances in fruit plants. The flesh tomato fruit represents an ideal system for examining the role of sucrose cleavage enzymes in fruit development, and wild tomato species differing in storage sugars serve as an excellent research material for this purpose. Plant vacuolar invertase is a key enzyme of sucrose metabolism in the sink organs. In the present study, we identified complete gene sequences encoding the TAI vacuolar invertase in 11 wild and one cultivated tomato accessions of the Solanum section Lycopersicon. The average level of interspecific polymorphism in TAI genes was 8.58%; however, in the green-fruited tomatoes, the TAI genes contained 100 times more SNPs than those in the red-fruited accessions. The TAI proteins demonstrated 8% variability, whereas the red-fruited species had none. A TAI-based phylogenetic tree revealed two main clusters containing self-compatible and self-incompatible species, which concurs with the previous crossability-based division and demonstrates that the TAI genes reflect the evolutionary relationships between the red- and green-fruited tomatoes. Furthermore, we detected differential expression patterns of the TAI genes in the fruits of wild and cultivated tomatoes, which corresponded to sugar composition. The polymorphism analysis of the TAI acid invertases of Solanum section Lycopersicon species will contribute to the understanding of the genetic potential of TAI genes to impact tomato breeding through genetic engineering of the carbohydrate composition in the fruit.

Proteome-pI: proteome isoelectric point database

Proteome-pI is an online database containing information about predicted isoelectric points for 5029 proteomes calculated using 18 methods. 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, especially for 2D gel electrophoresis (2D-PAGE), capillary isoelectric focusing, liquid chromatography–mass spectrometry and X-ray protein crystallography. The database, available at http://isoelectricpointdb.org allows the retrieval of virtual 2D-PAGE plots and the development of customised fractions of proteome based on isoelectric point and molecular weight. Moreover, Proteome-pI facilitates statistical comparisons of the various prediction methods as well as biological investigation of protein isoelectric point space in all kingdoms of life. For instance, using Proteome-pI data, it is clear that Eukaryotes, which evolved tight control of homeostasis, encode proteins with pI values near the cell pH. In contrast, Archaea living frequently in extreme environments can possess proteins with a wide range of isoelectric points. The database includes various statistics and tools for interactive browsing, searching and sorting. Apart from data for individual proteomes, datasets corresponding to major protein databases such as UniProtKB/TrEMBL and the NCBI non-redundant (nr) database have also been precalculated and made available in CSV format.

IPC - Isoelectric Point Calculator

BACKGROUND

Accurate estimation of the isoelectric point (pI) based on the amino acid sequence is useful for many analytical biochemistry and proteomics techniques such as 2-D polyacrylamide gel electrophoresis, or capillary isoelectric focusing used in combination with high-throughput mass spectrometry. Additionally, pI estimation can be helpful during protein crystallization trials.

RESULTS

Here, I present the Isoelectric Point Calculator (IPC), a web service and a standalone program for the accurate estimation of protein and peptide pI using different sets of dissociation constant (pKa) values, including two new computationally optimized pKa sets. According to the presented benchmarks, the newly developed IPC pKa sets outperform previous algorithms by at least 14.9 % for proteins and 0.9 % for peptides (on average, 22.1 % and 59.6 %, respectively), which corresponds to an average error of the pI estimation equal to 0.87 and 0.25 pH units for proteins and peptides, respectively. Moreover, the prediction of pI using the IPC pKa's leads to fewer outliers, i.e., predictions affected by errors greater than a given threshold.

CONCLUSIONS

The IPC service is freely available at http://isoelectric.ovh.org Peptide and protein datasets used in the study and the precalculated pI for the PDB and some of the most frequently used proteomes are available for large-scale analysis and future development.

REVIEWERS

This article was reviewed by Frank Eisenhaber and Zoltán Gáspári.

Critical Evaluation and Compilation of Physicochemical Determinants and Membrane Interactions of MMGP1 Antifungal Peptide

A growing issue of pathogen resistance to antibiotics has fostered the development of innovative approaches for novel drug development. Here, we report the physicochemical and biological properties of an antifungal peptide, MMGP1, based on computational analysis. Computation of physicochemical properties has revealed that the natural biological activities of MMGP1 are coordinated by its intrinsic properties such as net positive charge (+5.04), amphipathicity, high hydrophobicity, low hydrophobic moment, and higher isoelectric point (11.915). Prediction of aggregation hot spots in MMGP1 had revealed the presence of potentially aggregation-prone segments that can nucleate in vivo aggregation (on the membrane), whereas no aggregating regions were predicted for in vitro aggregation (in solutions) of MMGP1. This ability of MMGP1 to form oligomeric aggregates on membrane further substantiates its direct-cell penetrating potency. Monte Carlo simulation of the interactions of MMGP1 in the aqueous phase and different membrane environments revealed that increasing the proportion of acidic lipids on membrane had led to increase in the peptide helicity. Furthermore, the peptide adopts energetically favorable transmembrane configuration, by inserting peptide loop and helix termini into the membrane containing >60% of anionic lipids. The charged lipid-based insertion of MMGP1 into membrane might be responsible for the selectivity of peptide toward fungal cells. Additionally, MMGP1 possessed DNA-binding property. Computational docking has identified DNA-binding residues (TRP3, SER4, MET7, ARG8, PHE10, ALA11, GLY20, THR21, ARG22, MET23, TRP34, and LYS36) in MMGP1 crucial for its DNA-binding property. Furthermore, computational mutation analysis revealed that aromatic amino acids are crucial for in vivo aggregation, membrane insertion, and DNA-binding property of MMGP1. These data provide new insight into the molecular determinants of MMGP1 antifungal activity and also serves as the template for the design of novel peptide antibiotics.

Modelling the electrophoretic migration behaviour of peptides and glycopeptides from glycoprotein digests in capillary electrophoresis-mass spectrometry

In this study, the classical semiempirical relationships between the electrophoretic mobility and the charge-to-mass ratio (me vs. q/M(α)) were used to model the migration behaviour of peptides and glycopeptides originated from the digestion of recombinant human erythropoietin (rhEPO), a biologically and therapeutically relevant glycoprotein. The Stoke's law (α=1/3), the classical polymer model (α=1/2) and the Offord's surface law (α=2/3) were evaluated to predict migration of peptides and glycopeptides, with and without sialic acids (SiA), in rhEPO digested with trypsin and trypsin-neuraminidase. The Stoke's law resulted in better correlations for the set of peptides used to evaluate the models, while glycopeptides fitted better with the classical polymer model. Once predicted migration times with both models, it was easy to simulate their separation electropherogram. Results were later validated predicting migration and simulating separation of a different set of rhEPO glycopeptides and also human transferrin (Tf) peptides and glycopeptides. The excellent agreement between the experimental and the simulated electropherograms with rhEPO and Tf digests confirmed the potential applicability of this simple strategy to predict, in general, the peptide-glycopeptide electrophoretic map of any digested glycoprotein.

PIP-DB: the Protein Isoelectric Point database

A protein's isoelectric point or pI corresponds to the solution pH at which its net surface charge is zero. Since the early days of solution biochemistry, the pI has been recorded and reported, and thus literature reports of pI abound. The Protein Isoelectric Point database (PIP-DB) has collected and collated these data to provide an increasingly comprehensive database for comparison and benchmarking purposes. A web application has been developed to warehouse this database and provide public access to this unique resource. PIP-DB is a web-enabled SQL database with an HTML GUI front-end. PIP-DB is fully searchable across a range of properties.

AVAILABILITY AND IMPLEMENTATION

The PIP-DB database and documentation are available at http://www.pip-db.org.

Influence of hydrophilic amino acids and GC-content on expression of recombinant proteins used in vaccines against foot-and-mouth disease virus in Escherichia coli

Epitope-based protein expression in Escherichia coli can be improved by adjusting its amino acid composition and encoding genes. To that end, we analyzed 24 recombinant epitope proteins (rEPs) that carry multiple epitopes derived from VP1 protein of foot-and-mouth disease virus. High level expression of the rEPs was attributed to a high content of Arg, Asn, Asp and Thr, a low content of Gln, Pro and Lys, a high content of hydrophilic amino acids and a higher isoelectric point value resulting from abundant Arg. It is also attributed to the appropriate guanine and cytosine content in the encoding genes. The data provide a reference for adjusting the amino acid composition in designing epitope-based proteins used in vaccines and for adjusting the synonymous codons to improve their expressions in E. coli.

Control of aragonite deposition in colonial corals by intra-skeletal macromolecules

Scleractinian coral skeletons are composed mainly of aragonite in which a small percentage of organic matrix (OM) molecules is entrapped. It is well known that in corals the mineral deposition occurs in a biological confined nucleation site, but it is still unclear to what extent the calcification is controlled by OM molecules. Hence, the shape, size and organization of skeletal crystals from the fiber level through the colony architecture, were also attributed to factors as diverse as nucleation site mineral supersaturation and environmental factors in the habitat. In this work the OMs were extracted from the skeleton of three colonial corals, Acropora digitifera, Lophelia pertusa and Montipora caliculata. A. digitifera has a higher calcification rate than the other two species. OM molecules were characterized and their CaCO3 mineralization activity was evaluated by experiments of overgrowth on coral skeletons and of precipitation from solutions containing OM soluble and insoluble fractions and magnesium ions. The precipitates were characterized by spectroscopic and microscopic techniques. The results showed that the OM molecules of the three coral share similar features, but differ from those associated with mollusk shells. However, A. digitifera OM shows peculiarities from those from L. pertusa and M. caliculata. The CaCO3 overgrowth and precipitation experiments confirm the singularity of A. digitifera OM molecules as mineralizers. Moreover, their comparison indicates that only specific molecules are involved in the polymorphism control and suggests that when the whole extracted materials are used the OM's main effect is on the control of particles' shape and morphology.

Computational methods to predict therapeutic protein aggregation

Protein based biotherapeutics have emerged as a successful class of pharmaceuticals. However, these macromolecules endure a variety of physicochemical degradations during manufacturing, shipping, and storage, which may adversely impact the drug product quality. Of these degradations, the irreversible self-association of therapeutic proteins to form aggregates is a major challenge in the formulation of these molecules. Tools to predict and mitigate protein aggregation are, therefore, of great interest to biopharmaceutical research and development. In this chapter, a number of such computational tools developed to understand and predict the various steps involved in protein aggregation are described. These tools can be grouped into three general classes: unfolding kinetics and native state thermal stability, colloidal stability, and sequence/structure based aggregation liabilities. Chapter sections introduce each class by discussing how these predictive tools provide insight into the molecular events leading to protein aggregation. The computational methods are then explained in detail along with their advantages and limitations.

Coupling of T161 and T14 phosphorylations protects cyclin B-CDK1 from premature activation

Mitosis is triggered by the abrupt dephosphorylation of inhibitory Y15 and T14 residues of cyclin B1-bound cyclin-dependent kinase (CDK)1 that is also phosphorylated at T161 in its activation loop. The sequence of events leading to the accumulation of fully phosphorylated cyclin B1-CDK1 complexes remains unclear. Two-dimensional gel electrophoresis allowed us to determine whether T14, Y15, and T161 phosphorylations occur on same CDK1 molecules and to characterize the physiological occurrence of their seven phosphorylation combinations. Intriguingly, in cyclin B1-CDK1, the activating T161 phosphorylation never occurred without the T14 phosphorylation. This strict association could not be uncoupled by a substantial reduction of T14 phosphorylation in response to Myt1 knockdown, suggesting some causal relationship. However, T14 phosphorylation was not directly required for T161 phosphorylation, because Myt1 knockdown did uncouple these phosphorylations when leptomycin B prevented cyclin B1-CDK1 complexes from accumulating in cytoplasm. The coupling mechanism therefore depended on unperturbed cyclin B1-CDK1 traffic. The unexpected observation that the activating phosphorylation of cyclin B1-CDK1 was tightly coupled to its T14 phosphorylation, but not Y15 phosphorylation, suggests a mechanism that prevents premature activation by constitutively active CDK-activating kinase. This explained the opposite effects of reduced expression of Myt1 and Wee1, with only the latter inducing catastrophic mitoses.

Genetic analysis of cysteine-poor prolamin polypeptides reduced in the endosperm of the rice esp1 mutant

The esp1 mutant CM21 specifically exhibits reduced levels of cysteine-poor (CysP) prolamin bands with pIs of 6.65, 6.95, 7.10, and 7.35 in rice seed. Matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis demonstrated that the bands with pIs 6.65, 6.95, and 7.35 are encoded by different structural genes. These results suggest that the Esp1 locus encodes a regulatory factor involved in the synthesis and/or accumulation of CysP prolamin molecules. Isoelectric focusing (IEF) analysis of CysP prolamins in chromosome substitution lines showed that structural genes for bands with pI values of 6.95, 7.10, and 7.35, which are reduced in esp1 mutant lines, are located as a gene cluster in the 44.2 cM region on chromosome 5.

What drives amyloid molecules to assemble into oligomers and fibrils?

We develop a theory for three states of equilibrium of amyloid peptides: the monomer, oligomer, and fibril. We assume that the oligomeric state is a disordered micellelike collection of a few peptide chains held together loosely by hydrophobic interactions into a spherical hydrophobic core. We assume that fibrillar amyloid chains are aligned and further stabilized by steric zipper interactions-hydrogen bonding, steric packing, and specific hydrophobic side-chain contacts. The model makes a broad set of predictions that are consistent with experimental results: 1), Similar to surfactant micellization, amyloid oligomerization should increase with peptide concentration in solution. 2), The onset of fibrillization limits the concentration of oligomers in the solution. 3), The extent of Aβ fibrillization increases with peptide concentration. 4), The predicted average fibril length versus monomer concentration agrees with data on α-synuclein. 5), Full fibril length distributions agree with data on α-synuclein. 6), Denaturants should melt out fibrils. And finally, 7), added salt should stabilize fibrils by reducing repulsions between amyloid peptide chains. It is of interest that small changes in solvent conditions can tip the equilibrium balance between oligomer and fibril and cause large changes in rates through effects on the transition-state barrier. This model may provide useful insights into the physical processes underlying amyloid diseases.

Calibrative approaches to protein solubility modeling of a mutant series using physicochemical descriptors

A set of physicochemical properties describing a protein of known structure is employed for a calibrative approach to protein solubility. Common hydrodynamic and electrophoretic properties routinely measured in the bio-analytical laboratory such as zeta potential, dipole moment, the second osmotic virial coefficient are first estimated in silico as a function a pH and solution ionic strength starting with the protein crystal structure. The utility of these descriptors in understanding the solubility of a series of ribonuclease Sa mutants is investigated. A simple two parameter model was trained using solubility data of the wild type protein measured at a restricted number of solution pHs. Solubility estimates of the mutants demonstrate that zeta potential and dipole moment may be used to rationalize solubility trends over a wide pH range. Additionally a calibrative model based on the protein's second osmotic virial coefficient, B₂₂ was developed. A modified DVLO type potential along with a simplified representation of the protein allowed for efficient computation of the second viral coefficient. The standard error of prediction for both models was on the order of 0.3 log S units. These results are very encouraging and demonstrate that these models may be trained with a small number of samples and employed extrapolatively for estimating mutant solubilities.

Isoelectric point, electric charge, and nomenclature of the acid-base residues of proteins

The main object of this work is to present the pedagogical usefulness of the theoretical methods, developed in this laboratory, for the determination of the isoelectric point (pI) and the net electric charge of proteins together with some comments on the naming of the acid-base residues of proteins.