Methods of calculating protein hydrophobicity and their application in developing correlations to predict hydrophobic interaction chromatography retention

A Comparative Analysis of SARS-CoV-2 Variants of Concern (VOC) Spike Proteins Interacting with hACE2 Enzyme

In late 2019, the emergence of a novel coronavirus led to its identification as SARS-CoV-2, precipitating the onset of the COVID-19 pandemic. Many experimental and computational studies were performed on SARS-CoV-2 to understand its behavior and patterns. In this research, Molecular Dynamic (MD) simulation is utilized to compare the behaviors of SARS-CoV-2 and its Variants of Concern (VOC)-Alpha, Beta, Gamma, Delta, and Omicron-with the hACE2 protein. Protein structures from the Protein Data Bank (PDB) were aligned and trimmed for consistency using Chimera, focusing on the receptor-binding domain (RBD) responsible for ACE2 interaction. MD simulations were performed using Visual Molecular Dynamics (VMD) and Nanoscale Molecular Dynamics (NAMD2), and salt bridges and hydrogen bond data were extracted from the results of these simulations. The data extracted from the last 5 ns of the 10 ns simulations were visualized, providing insights into the comparative stability of each variant's interaction with ACE2. Moreover, electrostatics and hydrophobic protein surfaces were calculated, visualized, and analyzed. Our comprehensive computational results are helpful for drug discovery and future vaccine designs as they provide information regarding the vital amino acids in protein-protein interactions (PPIs). Our analysis reveals that the Original and Omicron variants are the two most structurally similar proteins. The Gamma variant forms the strongest interaction with hACE2 through hydrogen bonds, while Alpha and Delta form the most stable salt bridges; the Omicron is dominated by positive potential in the binding site, which makes it easy to attract the hACE2 receptor; meanwhile, the Original, Beta, Delta, and Omicron variants show varying levels of interaction stability through both hydrogen bonds and salt bridges, indicating that targeted therapeutic agents can disrupt these critical interactions to prevent SARS-CoV-2 infection.

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.

Characterization and exploration of an artifact in the reducing capillary electrophoresis-sodium dodecyl sulfate analysis of the 'me-too' drug zuberitamab related to rituximab

For monoclonal antibody (mAb) drugs, the 'me-too' drug is a pharmacologically active compound that is structurally similar to the first-in-class drugs, acting on the same target and is used for the same therapeutic purposes, but it may differ in drug-drug interactions and adverse drug reactions. Capillary electrophoresis-sodium dodecyl sulfate (CE-SDS) has been widely used for quality evaluation of mAb drugs. The properties of the detected substances can interfere with the credibility and accuracy of the method. In the routine comparison analysis for both innovator rituximab and 'me-too' drug zuberitamab samples, an uncommon artifact related to the heavy chain (HC) of zuberitamab was observed in reducing CE-SDS and interfered with our identification of the purity of samples. In this work, the overall hydrophobicity of the HCs of rituximab, zuberitamab, and several other common mAbs was characterized and determined by reversed-phase high-performance liquid chromatography. Additionally, the local hydrophobicity and surface charge were compared using Expasy ProtScale and PyMOL software simulations. We concluded that noncovalent protein aggregation can be related to strong hydrophobicity and low electrostatic repulsion of local amino acid regions, which complicates drug quality control. These findings shed light on the relationship between protein aggregation and the local hydrophobicity region, and broaden the way to analyze the detection 'artifacts' in reducing CE-SDS studies of therapeutic proteins.

Hidden hydrophobicity impacts polymer immunogenicity

Antibodies against poly(ethylene glycol) (PEG) have been found to be the culprit of side reactions and efficacy loss of a number of PEGylated drugs. Fundamental mechanisms of PEG immunogenicity and design principles for PEG alternatives still have not been fully explored. By using hydrophobic interaction chromatography (HIC) under varied salt conditions, we reveal the "hidden" hydrophobicity of those polymers which are generally considered as hydrophilic. A correlation between the hidden hydrophobicity of a polymer and its polymer immunogenicity is observed when this polymer is conjugated with an immunogenic protein. Such a correlation of hidden hydrophobicity vs. immunogenicity for a polymer also applies to corresponding polymer-protein conjugates. Atomistic molecular dynamics (MD) simulation results show a similar trend. Based on polyzwitterion modification and with this HIC technique, we are able to produce extremely low-immunogenic protein conjugates as their hydrophilicity is pushed to the limit and their hydrophobicity is eliminated, breaking the current barriers of eliminating anti-drug and anti-polymer antibodies.

Nano-liquid chromatography with monolithic stationary phase based on naphthyl monomer for proteomics analysis

Monolithic poly(2-vinylnaphthalene-co-divinylbenzene) columns were introduced, for the first time, and were evaluated as the separation media for nano-liquid chromatography (nano-LC). These columns were prepared by in-situ polymerization of 2-vinylnaphthalene (2-VNA) as the functional monomer and divinylbenzene (DVB) as the crosslinker in a fused silica capillary column of 50 µm i.d. Various porogenic solvents, including tetrahydrofuran (THF), dodecanol and toluene were used for morphology optimization. Final monolithic column (referred to as VNA column) was characterized by using scanning electron microscopy (SEM) and chromatographic analyses. Alkylbenzenes (ABs), and polyaromatic hydrocarbons (PAHs) were separated using the VNA column while the column offered excellent hydrophobic and π-π interactions under reversed-phase conditions. Theoretical plates number up to 41,200 plates/m in isocratic mode for ethylbenzene could be achieved. The potential of the final VNA column was demonstrated with a gradient elution in the  separation of six intact proteins, including ribonuclease A (RNase A), cytochrome C (Cyt C), lysozyme (Lys), β-lactoglobulin (β-lac), myoglobin (My) and α-chymotrypsinogen (α-chym) in nano LC system. The column was then applied to the peptide analysis of trypsin digested cytochrome C, allowing a high peak capacity up to 1440 and the further proteomics analysis of COS-7 cell line was attempted applying the final monolithic column in nano-LC UV system.

Investigating the cellular antioxidant and anti-inflammatory effects of the novel peptides in lingzhi mushrooms

The lingzhi mushroom (Ganoderma lucidum) is well known for its medicinal properties and has long played a role in traditional oriental medicine due to its health-giving benefits and potential to extend life expectancy. The mushroom contains a number of highly bioactive compounds and can also act as an excellent source of protein. This research investigated the peptides obtained from the protein hydrolysates of lingzhi mushrooms to assess their free radical scavenging abilities. These peptides were acquired via different proteases (Alcalase, Neutrase, papain, and pepsin-pancreatin) and were tested at a range of different concentrations (1.0%, 2.5%, and 5.0% w/v). The highest levels of 2,2′-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS), 2,2-diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) radical scavenging activities were presented by lingzhi mushroom hydrolysate using 2.5% (w/v) pepsin-pancreatin after 6 h of digestion. The hydrolysate was then fractionated using 10, 5, 3, and 0.65 kDa molecular weight cut-off membranes. The results showed that the MW 0.65 kDa fraction had the highest level of free radical scavenging activity. Further analysis of this MW 0.65 kDa fraction began with another RP-HPLC fractionation technique to obtain three further sub-fractions. De novo peptide sequencing using electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-Q-TOF-MS/MS) was chosen as the optimum method for studying the F₃ sub-fraction. DRVSIYGWG and ALLSISSF were discovered as new peptides with different antioxidant properties. Adenocarcinoma colon (Caco-2) cells showed the antioxidant action of these synthesized peptides. This activity was linked to peptide concentration. The peptides and their pure synthetic counterparts were found to reduce NO generation by RAW 264.7 macrophages without causing cytotoxicity. The results of gene expression reveal that the DRVSIYGWG and ALLSISSF peptides were able to cut the expression of the proinflammatory cytokine genes iNOS, IL-6, TNF-α, and COX-2 in the context of RAW 264.7 macrophages.

Comparison of hydrophobicity scales for predicting biophysical properties of antibodies

While antibody-based therapeutics have grown to be one of the major classes of novel medicines, some antibody development candidates face significant challenges regarding expression levels, solubility, as well as stability and aggregation, under physiological and storage conditions. A major determinant of those properties is surface hydrophobicity, which promotes unspecific interactions and has repeatedly proven problematic in the development of novel antibody-based drugs. Multiple computational methods have been devised for in-silico prediction of antibody hydrophobicity, often using hydrophobicity scales to assign values to each amino acid. Those approaches are usually validated by their ability to rank potential therapeutic antibodies in terms of their experimental hydrophobicity. However, there is significant diversity both in the hydrophobicity scales and in the experimental methods, and consequently in the performance of in-silico methods to predict experimental results. In this work, we investigate hydrophobicity of monoclonal antibodies using hydrophobicity scales. We implement several scoring schemes based on the solvent-accessibility and the assigned hydrophobicity values, and compare the different scores and scales based on their ability to predict retention times from hydrophobic interaction chromatography. We provide an overview of the strengths and weaknesses of several commonly employed hydrophobicity scales, thereby improving the understanding of hydrophobicity in antibody development. Furthermore, we test several datasets, both publicly available and proprietary, and find that the diversity of the dataset affects the performance of hydrophobicity scores. We expect that this work will provide valuable guidelines for the optimization of biophysical properties in future drug discovery campaigns.

SSH2.0: A Better Tool for Predicting the Hydrophobic Interaction Risk of Monoclonal Antibody

Therapeutic antibodies play a crucial role in the treatment of various diseases. However, the success rate of antibody drug development is low partially because of unfavourable biophysical properties of antibody drug candidates such as the high aggregation tendency, which is mainly driven by hydrophobic interactions of antibody molecules. Therefore, early screening of the risk of hydrophobic interaction of antibody drug candidates is crucial. Experimental screening is laborious, time-consuming, and costly, warranting the development of efficient and high-throughput computational tools for prediction of hydrophobic interactions of therapeutic antibodies. In the present study, 131 antibodies with hydrophobic interaction experiment data were used to train a new support vector machine-based ensemble model, termed SSH2.0, to predict the hydrophobic interactions of antibodies. Feature selection was performed against CKSAAGP by using the graph-based algorithm MRMD2.0. Based on the antibody sequence, SSH2.0 achieved the sensitivity and accuracy of 100.00 and 83.97%, respectively. This approach eliminates the need of three-dimensional structure of antibodies and enables rapid screening of therapeutic antibody candidates in the early developmental stage, thereby saving time and cost. In addition, a web server was constructed that is freely available at http://i.uestc.edu.cn/SSH2/.

Pocket2Drug: An Encoder-Decoder Deep Neural Network for the Target-Based Drug Design

Computational modeling is an essential component of modern drug discovery. One of its most important applications is to select promising drug candidates for pharmacologically relevant target proteins. Because of continuing advances in structural biology, putative binding sites for small organic molecules are being discovered in numerous proteins linked to various diseases. These valuable data offer new opportunities to build efficient computational models predicting binding molecules for target sites through the application of data mining and machine learning. In particular, deep neural networks are powerful techniques capable of learning from complex data in order to make informed drug binding predictions. In this communication, we describe Pocket2Drug, a deep graph neural network model to predict binding molecules for a given a ligand binding site. This approach first learns the conditional probability distribution of small molecules from a large dataset of pocket structures with supervised training, followed by the sampling of drug candidates from the trained model. Comprehensive benchmarking simulations show that using Pocket2Drug significantly improves the chances of finding molecules binding to target pockets compared to traditional drug selection procedures. Specifically, known binders are generated for as many as 80.5% of targets present in the testing set consisting of dissimilar data from that used to train the deep graph neural network model. Overall, Pocket2Drug is a promising computational approach to inform the discovery of novel biopharmaceuticals.

Influence of high-intensity ultrasound on physicochemical and functional properties of a guamuchil Pithecellobium dulce (Roxb.) seed protein isolate

In this study, the influence of ultrasound on the physicochemical and functional properties of guamuchil seed protein isolate (GSPI) was investigated. The GSPI was prepared by alkaline extraction and isoelectric precipitation method followed by treating with ethanol (95%), from defatted guamuchil seed flour. GSPI suspensions (10%) were sonicated with a probe (20 kHz) at 3 power levels (200 W, 400 W, 600 W) for 15 and 30 min, in addition, to control treatment without ultrasound. Moisture content, water activity, bulk and compact densities and the L*, a* and b* color parameters of the GSPI decreased due to the ultrasound. Glutelin (61.1%) was the main protein fraction in GSPI. Results through Fourier transform infrared and fluorescence spectroscopy showed that ultrasound modified the secondary and tertiary protein structures of GSPI, which increased the surface hydrophobicity, molecular flexibility and in vitro digestibility of GSPI proteins by up to 114.8%, 57.3% and 12.5%, respectively. In addition, maximum reductions of 11.9% in particle size and 55.2% in turbidity of GSPI suspensions, as well as larger and more porous aggregates in GSPI lyophilized powders were observed by ultrasound impact. These structural and physicochemical changes had an improvement of up to 115.5% in solubility, 39.8% in oil absorption capacity, while the increases for emulsifying, foaming, gelling, flow and cohesion properties of GSPI were 87.4%, 74.2%, 40.0%, 44.4%, and 8.9%, respectively. The amelioration of the functional properties of GSPI by ultrasound could represent an alternative for its possible use as a food ingredient in industry.

Bulk phase behaviour vs interface adsorption: Effects of anions and isotopes on β-lactoglobulin (BLG) interactions

HYPOTHESIS

Protein adsorption is highly relevant in numerous applications ranging from food processing to medical implants. In this context, it is important to gain a deeper understanding of protein-protein and protein-surface interactions. Thus, the focus of this investigation is on the interplay of bulk properties and surface properties on protein adsorption. It was hypothesised that the type of solvent and ions in solution should significantly influence the protein's bulk and interface behaviour, which has been observed in literature and previous work for other net negatively charged, globular proteins such as bovine serum albumin (BSA).

EXPERIMENTS

The phase behaviour of β-lactoglobulin (BLG) with lanthanum chloride (LaCl₃) and iodide (LaI₃) in normal water H₂O(l) and heavy water (D₂O(l)) was established via optical microscopy and ultraviolet-visible spectroscopy. The formation of an adsorption layer and its properties such as thickness, density, structure, and hydration was investigated via neutron reflectivity, quartz-crystal microbalance with dissipation, and infra-red measurements.

FINDINGS

β-lactoglobulin does not show significant anion-induced or isotope-induced effects - neither in bulk nor at the solid-liquid interface, which deviates strongly from the behaviour of bovine serum albumin. We also provide a comprehensive discussion and comparison of protein-specific bulk and interface behaviour between bovine serum albumin and β-lactoglobulin dependent on anion, cation, solvent, and substrate properties. These findings pave the way for understanding the transition from adsorption to crystallisation.

SSH: A Tool for Predicting Hydrophobic Interaction of Monoclonal Antibodies Using Sequences

Therapeutic antibodies are one of the most important parts of the pharmaceutical industry. They are widely used in treating various diseases such as autoimmune diseases, cancer, inflammation, and infectious diseases. Their development process however is often brought to a standstill or takes a longer time and is then more expensive due to their hydrophobicity problems. Hydrophobic interactions can cause problems on half-life, drug administration, and immunogenicity at all stages of antibody drug development. Some of the most widely accepted and used technologies for determining the hydrophobic interactions of antibodies include standup monolayer adsorption chromatography (SMAC), salt-gradient affinity-capture self-interaction nanoparticle spectroscopy (SGAC-SINS), and hydrophobic interaction chromatography (HIC). However, to measure SMAC, SGAC-SINS, and HIC for hundreds of antibody drug candidates is time-consuming and costly. To save time and money, a predictor called SSH is developed. Based on the antibody's sequence only, it can predict the hydrophobic interactions of monoclonal antibodies (mAbs). Using the leave-one-out crossvalidation, SSH achieved 91.226% accuracy, 96.396% sensitivity or recall, 84.196% specificity, 87.754% precision, 0.828 Mathew correlation coefficient (MCC), 0.919 f-score, and 0.961 area under the receiver operating characteristic (ROC) curve (AUC).

Predictive chromatography of peptides and proteins as a complementary tool for proteomics

In the last couple of decades, considerable effort has been focused on developing methods for quantitative and qualitative proteome characterization. The method of choice in this characterization is mass spectrometry used in combination with sample separation. One of the most widely used separation techniques at the front end of a mass spectrometer is high performance liquid chromatography (HPLC). A unique feature of HPLC is its specificity to the amino acid sequence of separated peptides and proteins. This specificity may provide additional information about the peptides or proteins under study which is complementary to the mass spectrometry data. The value of this information for proteomics has been recognized in the past few decades, which has stimulated significant effort in the development and implementation of computational and theoretical models for the prediction of peptide retention time for a given sequence. Here we review the advances in this area and the utility of predicted retention times for proteomic applications.

Generic approach to the method development of intact protein separations using hydrophobic interaction chromatography

We describe a liquid chromatography method development approach for the separation of intact proteins using hydrophobic interaction chromatography. First, protein retention was determined as function of the salt concentration by isocratic measurements and modeled using linear regression. The error between measured and predicted retention factors was studied while varying gradient time (between 15 and 120 min) and gradient starting conditions, and ranged between 2 and 15%. To reduce the time needed to develop optimized gradient methods for hydrophobic interaction chromatography separations, retention-time estimations were also assessed based on two gradient scouting runs, resulting in significantly improved retention-time predictions (average error < 2.5%) when varying gradient time. When starting the scouting gradient at lower salt concentrations (stronger eluent), retention time prediction became inaccurate in contrast to predictions based on isocratic runs. Application of three scouting runs and a nonlinear model, incorporating the effects of gradient duration and mobile-phase composition at the start of the gradient, provides accurate results (improved fitting compared to the linear solvent-strength model) with an average error of 1.0% and maximum deviation of -8.3%. Finally, gradient scouting runs and retention-time modeling have been applied for the optimization of a critical-pair protein isoform separation encountered in a biotechnological sample.

Prediction of protein retention times in hydrophobic interaction chromatography by robust statistical characterization of their atomic-level surface properties

The correlation between the dimensionless retention times (DRT) of proteins in hydrophobic interaction chromatography (HIC) and their surface properties were investigated. A ternary atomic-level hydrophobicity scale was used to calculate the distribution of local average hydrophobicity across the proteins surfaces. These distributions were characterized by robust descriptive statistics to reduce their sensitivity to small changes in the three-dimensional structure. The applicability of these statistics for the prediction of protein retention behaviour was looked into. A linear combination of robust statistics describing the central tendency, heterogeneity and frequency of highly hydrophobic clusters was found to have a good predictive capability (R2  = 0.78), when combined a factor to account for protein size differences. The achieved error of prediction was 35% lower than for a similar model based on a description of the protein surface on an amino acid level. This indicates that a robust and mathematically simple model based on an atomic description of the protein surface can be used for the prediction of the retention behaviour of conformationally stable globular proteins with a well determined 3D structure in HIC. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:372-381, 2016.

Composite cryogels for lysozyme purification

Beads-embedded novel composite cryogel was synthesized to purify lysozyme (Lyz) from chicken egg white. The poly(hydroxyethyl methacrylate-N-methacryloyl-L-phenylalanine) (PHEMAPA) beads of smaller than 5 µm size were synthesized by suspension polymerization and then embedded into a poly(hydroxyethyl methacrylate) (PHEMA)-based cryogel column. The PHEMAPA bead-embedded cryogel (BEC) column was characterized by swelling tests, scanning electron microscopy (SEM), surface area measurements by the Brunauer-Emmett-Teller (BET) method, elemental analysis, and flow dynamics. The specific surface area of the PHEMAPA BEC was found as 41.2 m(2) /g using BET measurements. Lyz-binding experiments were performed using aqueous solutions in different conditions such as initial Lyz concentration, pH, flow rate, temperature, and NaCl concentration of an aqueous medium. The PHEMAPA BEC column could be used after 10 adsorption-desorption studies without any significant loss in adsorption capacity of Lyz. The PHEMAPA BEC column was used to purify Lyz from chicken egg white, and gel electrophoresis was used to estimate the purity of Lyz. The chromatographic application of the PHEMAPA BEC column was also performed using fast protein liquid chromatography.

Semi-automated hydrophobic interaction chromatography column scouting used in the two-step purification of recombinant green fluorescent protein

Background

Hydrophobic interaction chromatography (HIC) most commonly requires experimental determination (i.e., scouting) in order to select an optimal chromatographic medium for purifying a given target protein. Neither a two-step purification of untagged green fluorescent protein (GFP) from crude bacterial lysate using sequential HIC and size exclusion chromatography (SEC), nor HIC column scouting elution profiles of GFP, have been previously reported.

Methods and Results

Bacterial lysate expressing recombinant GFP was sequentially adsorbed to commercially available HIC columns containing butyl, octyl, and phenyl-based HIC ligands coupled to matrices of varying bead size. The lysate was fractionated using a linear ammonium phosphate salt gradient at constant pH. Collected HIC eluate fractions containing retained GFP were then pooled and further purified using high-resolution preparative SEC. Significant differences in presumptive GFP elution profiles were observed using in-line absorption spectrophotometry (A₃₉₅) and post-run fluorimetry. SDS-PAGE and western blot demonstrated that fluorometric detection was the more accurate indicator of GFP elution in both HIC and SEC purification steps. Comparison of composite HIC column scouting data indicated that a phenyl ligand coupled to a 34 µm matrix produced the highest degree of target protein capture and separation.

Conclusions

Conducting two-step protein purification using the preferred HIC medium followed by SEC resulted in a final, concentrated product with >98% protein purity. In-line absorbance spectrophotometry was not as precise of an indicator of GFP elution as post-run fluorimetry. These findings demonstrate the importance of utilizing a combination of detection methods when evaluating purification strategies. GFP is a well-characterized model protein, used heavily in educational settings and by researchers with limited protein purification experience, and the data and strategies presented here may aid in development other of HIC-compatible protein purification schemes.

Comparison of polymer induced and solvent induced trypsin denaturation: the role of hydrophobicity

Trypsin adsorption from aqueous buffer by various copolymers of allyl glycidyl ether-ethylene glycol dimethacrylate (AGE-EGDM) copolymer with varying crosslink density increases with increasing crosslink density and the effect slowly wears off after reaching a plateau at 50% crosslink density. The copolymer with 25% crosslink density was reacted with different amines with alkyl/aryl side chains to obtain a series of copolymers with 1,2-amino alcohol functional groups and varying hydrophobicity. Trypsin binding capacity again increases with hydrophobicity of the reacting amine and a good correlation between logPoctanol of the amine and protein binding is observed. The bound trypsin is denatured to the extent of 90% in spite of the presence of hydrophilic hydroxyl and amino groups. The behavior was comparable to that in mixtures of aqueous buffer and water-miscible organic co-solvents where the solvent concentration required to deactivate 50% of the enzyme (C50) is dependent on logPoctanol of the co-solvent.

Preparative purification of recombinant proteins: current status and future trends

Advances in fermentation technologies have resulted in the production of increased yields of proteins of economic, biopharmaceutical, and medicinal importance. Consequently, there is an absolute requirement for the development of rapid, cost-effective methodologies which facilitate the purification of such products in the absence of contaminants, such as superfluous proteins and endotoxins. Here, we provide a comprehensive overview of a selection of key purification methodologies currently being applied in both academic and industrial settings and discuss how innovative and effective protocols such as aqueous two-phase partitioning, membrane chromatography, and high-performance tangential flow filtration may be applied independently of or in conjunction with more traditional protocols for downstream processing applications.

Structural role of exon-coded fragment of polypeptide chains in selected enzymes

This paper discusses the structural role of fragments encoded by individual exons in proteins. Selected enzymes (hydrolases, transferases, ligases) reveal the presence of at least one exon fragment whose contribution to the protein's hydrophobic core is in line with theoretical expectations. This phenomenon is confirmed by quantitative analysis of the hydrophobicity density distribution in protein molecules. Results are compared with a 3D Gaussian function, treated as an "idealized" distribution of hydrophobicity density, with the highest values observed near the center of the molecule and near-zero values on its surface. At least one accordant exon fragment has been identified in each of the proteins subjected to analysis. On the basis of these results the authors propose that accordant exons are responsible for tertiary structural stabilization of proteins by ensuring the generation of a stable hydrophobic core.

Practical considerations in analysing neuropeptides, calcitonin gene-related peptide and vasoactive intestinal peptide, by nano-electrospray ionisation and quadrupole time-of-flight mass spectrometry: monitoring multiple protonations

We investigated the pre-electrospray ionisation (pre-ESI) factors; analyte concentration (1-2500  ng/mL), concentration of formic acid (FA) in the mobile phase (0.01, 0.1 and 1%), concentration of the organic modifier (acetonitrile 50-90%) and flow rate (<10  μL/min) on the number of multiple protonations and ESI response for two neuropeptides (of ~3.3  kDa molecular mass); calcitonin gene-related peptide (CGRP) and vasoactive intestinal peptide (VIP). A pH of 3.23 (0.1% FA), nano-flow rate range of 350-750  nL/min and acetonitrile concentration of 50% were optimum for both neuropeptides where the highest intensities were observed. An inverse relationship between decreasing flow rate and ESI response for both peptides was also observed. The quadruply charged ([M+4H](4+)) ion was dominant for CGRP at all analyte concentrations, and also for VIP, but only at the higher analyte concentrations (250-2500  ng/mL); none of the [M+4H](4+), [M+5H](5+) or [M+6H](6+) ions were dominant at the lower concentrations. Linear correlations were obtained for the protonated states and ESI response at analyte concentrations (1-750  ng/mL). Acetonitrile concentration was critical; severe ion suppression was observed for VIP when the concentration of acetonitrile was ≥60%. Ion suppression was also observed for both peptides in an equimolar mixture, with the extent of ion suppression more severe for VIP. Our study concludes that it is important to monitor several protonated species when a single protonated state does not dominate, especially during label-free peptide quantitations.

Hydrophilicity matching - a potential prerequisite for the formation of protein-protein complexes in the cell

A binding event between two proteins typically consists of a diffusional search of binding partners for one another, followed by a specific recognition of the compatible binding sites resulting in the formation of the complex. However, it is unclear how binding partners find each other in the context of the crowded, constantly fluctuating, and interaction-rich cellular environment. Here we examine the non-specific component of protein-protein interactions, which refers to those physicochemical properties of the binding partners that are independent of the exact details of their binding sites, but which can affect their localization or diffusional search for one another. We show that, for a large set of high-resolution experimental 3D structures of binary, transient protein complexes taken from the DOCKGROUND database, the binding partners display a surprising, statistically significant similarity in terms of their total hydration free energies normalized by a size-dependent variable. We hypothesize that colocalization of binding partners, even within individual cellular compartments such as the cytoplasm, may be influenced by their relative hydrophilicity, potentially in response to local hydrophilic gradients.