Hydropathy Research Articles

Common structural features in some of the sequentially distant neurotransmitter transporters N-termini

The N-terminal regions of SLC6 transporters are sequentially unrelated, and the majority of such transporters contain only relatively short peptide N-terminal extensions. Currently, it is not clear if a diversity of N-terminal sequences represents diverse functions among the transporters or if there are common functions hidden behind similar, as yet unidentified, structures. Using alignment of amino acid sequences with the hydropathy plot, disorder prediction, and calpain recognition sites, we show that common structural features among the N-termini of some transporters might exist.We previously showed that polymeric neurotransmitter transporter N-termini exhibit very similar profiles of dynamic, time-dependent 465-595-350-750 nm absorbance metachromasia in the Bradford assay. Here we report that under certain mild denaturing conditions, filamentous aggregation of glutathione S-transferase (GST) protein results in similar near-infrared metachromasia. This effect was eliminated by further GST protein denaturation and solubilization. The results suggest that aggregation of partially denatured GST stabilizes Coomassie dye docking sites, producing a near-infrared absorbance shift similar to that observed in the polymeric unstructured N-termini of transporters.

Electromembrane extraction of peptides based on charge, hydrophobicity, and size - A large-scale fundamental study of the extraction window.

This study investigated the capability of electromembrane extraction (EME) as a general technique for peptides, by extracting complex pools of peptides comprising in total of 5953 different substances, varying in size from seven to 16 amino acids. Electromembrane extraction was conducted from a sample adjusted to pH 3.0 and utilized a liquid membrane consisting of 2-nitrophenyl octyl ether and carvacrol (1:1 w/w), containing 2% (w/w) di(2-ethylhexyl) phosphate. The acceptor phase was 50mM phosphoric acid (pH 1.8), the extraction time was 45 min, and 10 V was used. High extraction efficiency, defined as a higher peptide signal in the acceptor than the sample after extraction, was achieved for 3706 different peptides. Extraction efficiencies were predominantly influenced by the hydrophobicity of the peptides and their net charge in the sample. Hydrophobic peptides were extracted with a net charge of +1, while hydrophilic peptides were extracted when the net charge was +2 or higher. A computational model based on machine learning was developed to predict the extractability of peptides based on peptide descriptors, including the grand average of hydropathy index and net charge at pH 3.0 (sample pH). This research shows that EME has general applicability for peptides and represents the first steps toward in silico prediction of extraction efficiency.

Microphase Separation Produces Interfacial Environment within Diblock Biomolecular Condensates.

The phase separation of intrinsically disordered proteins is emerging as an important mechanism for cellular organization. However, efforts to connect protein sequences to the physical properties of condensates, i.e., the molecular grammar, are hampered by a lack of effective approaches for probing high-resolution structural details. Using a combination of multiscale simulations and fluorescence lifetime imaging microscopy experiments, we systematically explored a series of systems consisting of diblock elastin-like polypeptides (ELP). The simulations succeeded in reproducing the variation of condensate stability upon amino acid substitution and revealed different microenvironments within a single condensate, which we verified with environmentally sensitive fluorophores. The interspersion of hydrophilic and hydrophobic residues and a lack of secondary structure formation result in an interfacial environment, which explains both the strong correlation between ELP condensate stability and interfacial hydrophobicity scales, as well as the prevalence of protein-water hydrogen bonds. Our study uncovers new mechanisms for condensate stability and organization that may be broadly applicable.

Phospholipid Membrane Interactions of Model Ac-WL-X-LL-OH Peptides Investigated by Solid-State Nuclear Magnetic Resonance.

The role of aromatic amino acids in peripheral protein membrane binding has been reported to involve cation-π interactions with choline lipids. In this study, we have investigated the interactions of the model pentapeptide Ac-WL-X-LL-OH (where X = L, Y, F, or W) with the phospholipid membrane using solid-state NMR. The effect of guest residue X on the peptide-lipid interactome was complementary to the seminal report on the interfacial hydrophobicity scale by Wimley and White. We found that the phospholipids retained a lamellar phase in the presence of each of the peptides with an aromatic X residue, whereas the Leu peptide perturbed the bilayer to an extent where an additional isotropic phase was observed. The solid-state NMR 13C and 31P data provide additional information on the influence of these short peptides on the membrane that has not been previously reported. The magnitude of membrane perturbation was in the order of guest residue X = L > Y~F > W, which is consistent with the relative amino acid interfacial affinity reported by Wimley and White. Further work is, however, required to uncover the behavior of the peptide and localization in the membrane domain due to ambiguity of the 13C NMR data. We have launched efforts in this regard for the objective of better understanding the role of aromatic amino acids in peripheral membrane protein binding.

Varicose veins: A systematic review of the diagnosis and treatment of varicose veins

VARICOSE VEINS is clinical class of chronic venous disease. Varicose veins also known as varicosities. Varicose veins are tortuous, twisted, enlarged veins, dilated veins most commonly located on the lower extremities. The diseases also show various associated symptoms which worsens the condition of the varicose veins. The ascendancy of varicose veins vary. This review articles deals with brief introduction regarding the etiopathogesis of varicose veins associated with key word cause symptoms, treatment, risks factors, management, complications, conclusion and reference. Varicose veins in the lower limb are affect at least a third (30%) of the population. such a condition that increases pressure on the legs veins such as obese, lack of exercise, pregnancy, hormonal fluctuation, smoking etc. Researchers report that a mild care of varicose veins does not usually require a doctor care, discomfort can be relieved with at home treatment and various alternative remedies, such as color therapy, diet and supplements, herbal therapy exercises, yoga, homeopathy and hydro therapy etc.

From PDB files to protein features: a comparative analysis of PDB bind and STCRDAB datasets.

Understanding protein structures is crucial for various bioinformatics research, including drug discovery, disease diagnosis, and evolutionary studies. Protein structure classification is a critical aspect of structural biology, where supervised machine learning algorithms classify structures based on data from databases such as Protein Data Bank (PDB). However, the challenge lies in designing numerical embeddings for protein structures without losing essential information. Although some effort has been made in the literature, researchers have not effectively and rigorously combined the structural and sequence-based features for efficient protein classification to the best of our knowledge. To this end, we propose numerical embeddings that extract relevant features for protein sequences fetched from PDB structures from popular datasets such as PDB Bind and STCRDAB. The features are physicochemical properties such as aromaticity, instability index, flexibility, Grand Average of Hydropathy (GRAVY), isoelectric point, charge at pH, secondary structure fracture, molar extinction coefficient, and molecular weight. We also incorporate scaling features for the sliding windows (e.g., k-mers), which include Kyte and Doolittle (KD) hydropathy scale, Eisenberg hydrophobicity scale, Hydrophilicity scale, Flexibility of the amino acids, and Hydropathy scale. Multiple-feature selection aims to improve the accuracy of protein classification models. The results showed that the selected features significantly improved the predictive performance of existing embeddings.

Implicit model to capture electrostatic features of membrane environment.

Membrane protein structure prediction and design are challenging due to the complexity of capturing the interactions in the lipid layer, such as those arising from electrostatics. Accurately capturing electrostatic energies in the low-dielectric membrane often requires expensive Poisson-Boltzmann calculations that are not scalable for membrane protein structure prediction and design. In this work, we have developed a fast-to-compute implicit energy function that considers the realistic characteristics of different lipid bilayers, making design calculations tractable. This method captures the impact of the lipid head group using a mean-field-based approach and uses a depth-dependent dielectric constant to characterize the membrane environment. This energy function Franklin2023 (F23) is built upon Franklin2019 (F19), which is based on experimentally derived hydrophobicity scales in the membrane bilayer. We evaluated the performance of F23 on five different tests probing (1) protein orientation in the bilayer, (2) stability, and (3) sequence recovery. Relative to F19, F23 has improved the calculation of the tilt angle of membrane proteins for 90% of WALP peptides, 15% of TM-peptides, and 25% of the adsorbed peptides. The performances for stability and design tests were equivalent for F19 and F23. The speed and calibration of the implicit model will help F23 access biophysical phenomena at long time and length scales and accelerate the membrane protein design pipeline.

Low-temperature FTIR spectroscopy of the L/Q switch of proteorhodopsin.

Rhodopsins are photoreceptive membrane proteins containing a retinal chromophore, and the color tuning mechanism in rhodopsins is one of the important topics. Color switch is a color-determining residue at the same position, where replacement of red- and blue-shifting amino acids in two wild-type rhodopsins causes spectral blue- and red-shifts, respectively. The first and most famous color switch in microbial rhodopsins is the L/Q switch in proteorhodopsins (PRs). Green- or blue-absorbing PR (GPR or BPR) contains Leu and Gln at position 105 of the C-helix (TM3), respectively, and their replacement converted absorbing colors. The L/Q switch enables bacteria to absorb green or blue light in shallow or deep ocean waters, respectively. Although Gln and Leu are hydrophilic and hydrophobic residues, respectively, a comprehensive mutation study of position 105 in GPR revealed that the λmax correlated with the volume of residues, not the hydropathy index. To gain structural insights into the mechanism, we applied low-temperature FTIR spectroscopy of L105Q GPR, and the obtained spectra were compared with those of GPR and BPR. The difference FTIR spectra of L105Q GPR were similar to those of BPR, not GPR, implying that the L/Q switch converts the GPR structure into a BPR structure in terms of the local environments of the retinal chromophore. It includes retinal skeletal vibration, hydrogen-bonding strength of the protonated Schiff base, amide-A vibration (peptide backbone), and protein-bound water molecules. Consequently color is switched accompanying such structural alterations, and known as the L/Q switch.

Structural, electronic, intermolecular interaction, reactivity, vibrational spectroscopy, charge transfer, Hirshfeld surface analysis, pharmacological and hydropathy plot on 5-Bromo nicotinic acid – Antiviral study (Hepatitis A, B, and C)

The therapeutic properties of 5-Bromonicotinatic acid (5BNA) were studied for antiviral illnesses like Hepatitis A, Hepatitis B and Hepatitis C and the influence of electron-donating and electron-withdrawing properties of functional groups on the nicotinic acid was evaluated and represented in this study using the DFT approach. The molecular parameters were determined for both gases as well as for various solvent phases. The reactive areas in the compound are examined utilising Fukui analysis. The molecular interactions are accomplished by recognising the different types of bonding found in the compound using the AIM, ELF, LOL, RDG and IRI. Solvation investigations were demonstrated to have an influence on molecular orbital energy, ESP, UV–Vis and NLO analyses. Electron-hole, NBO and Hirshfeld investigations are used to investigate the transfer of charges and interactions inside the molecule. The method of vibrational spectroscopy (IR and Raman) is used to differentiate and identify the various types of vibrations displayed by the compound. The hydropathy plots for the proteins 2A4O, 6CWD and 2OC8 associated with Hepatitis A, Hepatitis B and Hepatitis C illustrate the disquiet and attraction of the amino acids towards the water.

The role of leucine and isoleucine in tuning the hydropathy of class A GPCRs.

Leucine and Isoleucine are two amino acids that differ only by the positioning of one methyl group. This small difference can have important consequences in α-helices, as the β-branching of Ile results in helix destabilization. We set out to investigate whether there are general trends for the occurrences of Leu and Ile residues in the structures and sequences of class A GPCRs (G protein-coupled receptors). GPCRs are integral membrane proteins in which α-helices span the plasma membrane seven times and which play a crucial role in signal transmission. We found that Leu side chains are generally more exposed at the protein surface than Ile side chains. We explored whether this difference might be attributed to different functions of the two amino acids and tested if Leu tunes the hydrophobicity of the transmembrane domain based on the Wimley-White whole-residue hydrophobicity scales. Leu content decreases the variation in hydropathy between receptors and correlates with the non-Leu receptor hydropathy. Both measures indicate that hydropathy is tuned by Leu. To test this idea further, we generated protein sequences with random amino acid compositions using a simple numerical model, in which hydropathy was tuned by adjusting the number of Leu residues. The model was able to replicate the observations made with class A GPCR sequences. We speculate that the hydropathy of transmembrane domains of class A GPCRs is tuned by Leu (and to some lesser degree by Lys and Val) to facilitate correct insertion into membranes and/or to stably anchor the receptors within membranes.

Amino Acid- and Dipeptide Amphiphile-Based Supramolecular Eutectogels: Soft Materials for Drug Entrapment–Release and Wastewater Treatment

Supramolecular gels prepared in solvents of extreme polarities have received widespread importance across scientific disciplines. In this regard, soft materials based on deep eutectic solvents (DESs) have been receiving notable attention owing to their low toxicity, low volatility, and ability to solubilize hydrophobic drugs and natural products. A DES is a mixture of two or more compounds having a melting point lower than that of the individual components. Reports on supramolecular eutectogels derived from small molecules are very few and serendipitous. Therefore, designing a low-molecular-weight eutectogelator (LMWEG) remains challenging and demands comprehensive structure–property correlation. To this end, we have developed amino acid- and dipeptide amphiphile-based LMWEGs that immobilized choline chloride/phenylacetic acid-based DES with a minimum gelation concentration (MGC) of 0.5–10.0%, w/v. Variation of amino acids, protecting groups at the N-terminal, and hydrophobic chain length of the gelator delineated the crucial influence of the hydropathy index of amino acids and thereby the hydrophilic–lipophilic balance in eutectogelation. Replacement of the aromatic moiety in the gelator and/or in the DES with an aliphatic one ascertained the optimal necessity of aromaticity for efficient eutectogelation. Eutectogels were thermoreversible and showed considerable thermal stability (Tgel ∼ 50–70 °C). Spectroscopic and microscopic studies confirmed the fiber-like morphology of the eutectogels and the participation of hydrogen bonding in eutectogelation. Newly derived eutectogels exhibited considerably good mechanical strength (γc ∼ 7.5–16.5%) and interesting injectable as well as thixotropic properties. The ability to adsorb cationic and anionic dyes by the eutectogels ensured their potential in wastewater treatment. Importantly, these supramolecular eutectogels can be used in drug delivery owing to their ability to entrap the hydrophobic drug curcumin and subsequently its pH-dependent sustained release.

Whole Exome Sequencing Identified Two Single Nucleotide Polymorphisms of Human Leukocyte Antigen-DRB5 in Familial Sarcoidosis in China.

Sarcoidosis is a multisystem granulomatous disorder whose etiology is related to genetic and immunological factors. Familial aggregation and ethnic prevalence suggest a genetic predisposition and inherited susceptibility to sarcoidosis. This study aimed to identify suspected risk loci for familial sarcoidosis patients. We conducted whole exome sequencing on two sarcoidosis patients and five healthy family members in a Chinese family for a case-control study. The two sarcoidosis patients were siblings who showed chronic disease. The Gene Ontology results showed single nucleotide polymorphisms in three genes, including human leukocyte antigen (HLA)-DRB1, HLA-DRB5, and KIR2DL4, associated with both 'antigen processing and presentation' and 'regulation of immune response.' Sanger sequencing verified two nonsynonymous mutations in HLA-DRB5 (rs696318 and rs115817940) located on 6p21.3 in the major histocompatibility complex (MHC) class II beta 1 region. The structural model simulated on Prot- Param protein analysis by the Expert Protein Analysis System predicted that the hydropathy index changed at two mutation sites (rs696318: p.F96L, -1.844 to -1.656 and rs115817940: p.T106N, -0.322 to -0.633), which indicated the probability of changes in peptide-binding selectivity. Our results indicated that two nonsynonymous mutations of HLA-DRB5 have been identified in two sarcoidosis siblings, while their healthy family members do not have the mutations. The two HLA-DRB5 alleles may influence genetic susceptibility and chronic disease progression through peptide mutations on the MHC class II molecule among the two affected family members.

UNILIPID, a Methodology for Energetically Accurate Prediction of Protein Insertion into Implicit Membranes of Arbitrary Shape.

The insertion of proteins into membranes is crucial for understanding their function in many biological processes. In this work, we present UNILIPID, a universal implicit lipid-protein description as a methodology for dealing with implicit membranes. UNILIPID is independent of the scale of representation and can be applied at the level of all atoms, coarse-grained particles down to the level of a single bead per amino acid. We provide example implementations for these scales and demonstrate the versatility of our approach by accurately reflecting the free energy of transfer for each amino acid. In addition to single membranes, we describe the analytical implementation of double membranes and show that UNILIPID is well suited for modeling at multiple scales. We generalize to membranes of arbitrary shape. With UNILIPID, we provide a methodological framework for a simple and general parameterization tuned to reproduce a selected reference hydrophobicity scale. The software we provide along with the methodological description is optimized for specific user features such as real-time response, live visual analysis, and virtual reality experiences.

Coarse-grained intrinsically disordered protein simulations with explicit ions parameterized by salting-out constants.

Implicit solvent coarse-grained models have emerged as an effective method for simulating intrinsically disordered proteins (IDPs) due to the long length and time-scale need to effectively simulate their equilibrium behavior. These coarse-grained methods typically rely on Debye-Hückel theory to explain the effects of salt in the simulations. However, Debye-Hückel electrostatics are only accurate over a limited range of ionic strengths and are also unable to capture ion-type specific effects, typically called Hofmeister effects that arise at higher salt concentrations. To address this, we developed an explicit ion model of potassium chloride that can interface with the otherwise implicit solvent hydrophobicity scale model for intrinsically disordered protein. Parameters for the explicit ion model were determined by matching the salting-out constants of several small peptide-like molecules. Salting-out constants were determined in the simulation by creating a system with an ion concentration gradient via an external potential and performing umbrella sampling along the concentration gradient. The remaining amino acids for which there is no data for the salting-out constant are determined using a scaled Kapcha-Rosky hydrophobicity scale determined from the umbrella sampling simulations. The parameters are validated against a set FRET data from a diverse set of linker peptides at several salt concentrations. This explicit ion model is able to capture the changes in protein expansion as a function of salt concentration at concentration above 0.5 M where Debye-Hückel screened electrostatics predict no change in protein expansion.

Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range.

The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.

Protein-Protein Interaction Sites Prediction Based on an Under-Sampling Strategy and Random Forest Algorithm.

The computational methods of protein-protein interaction sites prediction can effectively avoid the shortcomings of high cost and time in traditional experimental approaches. However, the serious class imbalance between interface and non-interface residues on the protein sequences limits the prediction performance of these methods. This work therefore proposed a new strategy, NearMiss-based under-sampling for unbalancing datasets and Random Forest classification (NM-RF), to predict protein interaction sites. Herein, the residues on protein sequences were represented by the PSSM-derived features, hydropathy index (HI) and relative solvent accessibility (RSA). In order to resolve the class imbalance problem, an under-sampling method based on NearMiss algorithm is adopted to remove some non-interface residues, and then the random forest algorithm is used to perform binary classification on the balanced feature datasets. Experiments show that the accuracy of NM-RF model reaches 87.6% and 84.3% on Dtestset72 and PDBtestset164 respectively, which demonstrate the effectiveness of the proposed NM-RF method in differentiating the interface or non-interface residues.

Effect of hydrocarbon condensation on fouling and heat exchange efficiency in EGR cooler

Based on the self-established experiment and test platform and evaluation system, we studied the effects of hydrocarbon condensation on mass, hydrophilicity, color, and micromorphology of fouling and heat transfer efficiency in exhaust gas recirculation (EGR) coolers. The results show that hydrocarbon condensation converts low mass, hydrophobic, solid black, and fluffy scales into larger mass, hydrophilic, white and yellow, and compact scales of fouling. When Total Hydrocarbons (THC) are 590 ppmC, 411 ppmC, and 359 ppmC, the temperatures to the demarcation points of the rapid condensation enhancement and stability stage are 100 °C, 120 °C, and 135 °C, respectively. However, when the temperature exceeds 160 °C, hydrocarbons' condensation is substantially suppressed, and the heat exchange efficiency is the worst. Hydrocarbons condensation will increase the fouling density, improving the heat exchange efficiency; the highest heat exchange efficiency will be achieved when the condensation is stable. Hydrocarbon and particulate matter (PM) together determine the composition and structure of the fouling, which in turn determines the heat transfer efficiency.

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.

Total free energy analysis of fully hydrated proteins.

The total free energy of a hydrated biomolecule and its corresponding decomposition of energy and entropy provides detailed information about regions of thermodynamic stability or instability. The free energies of four hydrated globular proteins with different net charges are calculated from a molecular dynamics simulation, with the energy coming from the system Hamiltonian and entropy using multiscale cell correlation. Water is found to be most stable around anionic residues, intermediate around cationic and polar residues, and least stable near hydrophobic residues, especially when more buried, with stability displaying moderate entropy-enthalpy compensation. Conversely, anionic residues in the proteins are energetically destabilized relative to singly solvated amino acids, while trends for other residues are less clear-cut. Almost all residues lose intraresidue entropy when in the protein, enthalpy changes are negative on average but may be positive or negative, and the resulting overall stability is moderate for some proteins and negligible for others. The free energy of water around single amino acids is found to closely match existing hydrophobicity scales. Regarding the effect of secondary structure, water is slightly more stable around loops, of intermediate stability around strands and turns, and least stable around helices. An interesting asymmetry observed is that cationic residues stabilize a residue when bonded to its N-terminal side but destabilize it when on the C-terminal side, with a weaker reversed trend for anionic residues.

Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range

The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.