Enthalpic and Entropic Contributions to Hydrophobicity

Carbon fixation via volatile fatty acids recovery from sewage sludge through electrochemical-pretreatment-based anaerobic digestion

Capturing the carbon in volatile fatty acids (VFA) produced from the anaerobic digestion (AD) of sewage sludge has the potential to not only provide economic benefits but also reduce greenhouse gas production. This study demonstrates a chemical-free method to collect VFA from an AD instead of methane that involves electrochemical pretreatment (EPT) of sludge. Experimental results show that applying 15 V EPT for 45 min enhances acidogenesis and selectively inhibits methanogenesis, leading to a substantial VFA accumulation (2563.1 ± 307.9 mg COD/L) and achieving 2.5 times more carbon fixation than via methane production. Interfacial thermodynamic analysis shows that EPT induces a decrease in both the repulsive electrostatic energy (from 152.9 kT to 12.2 kT) and the energy barrier (from 57.0 kT to 2.6 kT) in the sludge, leading to increased sludge aggregation and entrapment of microorganisms. Molecular docking sheds lights on how the methanogens interacts with the organic matter released from EPT (e.g., alanine-tRNA ligase), showing that these interactions potentially interfere with the proteins that are associated with the activities of the methanogens and the electron transfer pathways, thereby impeding methanogenesis. Integrating EPT into AD therefore facilitates the recovery of valuable VFA and the capture of carbon from freshwater sludge, providing notable economic and environmental benefits in sewage sludge treatment.

Molecular engineering of insulin for recombinant expression in yeast

Since the first administration of insulin to a person with diabetes in 1922, scientific contributions from academia and industry have improved insulin therapy and access. The pharmaceutical need for insulin is now more than 40 tons annually, half of which is produced by recombinant secretory expression in Saccharomyces cerevisiae. We discuss how, in this yeast species, adaptation of insulin precursors by removable structural elements is pivotal for efficient secretory expression. The technologies reviewed have been implemented at industrial scale and are seminal for the supply of human insulin and insulin analogues to people with diabetes now and in the future. Engineering of a target protein with removable structural elements may provide a general approach to yield optimisation.

An Affordable Topography-Based Protocol for Assigning a Residue's Character on a Hydropathy (PARCH) Scale

The hydropathy of proteins or quantitative assessment of protein-water interactions has been a topic of interest for decades. Most hydropathy scales use a residue-based or atom-based approach to assign fixed numerical values to the 20 amino acids and categorize them as hydrophilic, hydroneutral, or hydrophobic. These scales overlook the protein's nanoscale topography, such as bumps, crevices, cavities, clefts, pockets, and channels, in calculating the hydropathy of the residues. Some recent studies have included protein topography in determining hydrophobic patches on protein surfaces, but these methods do not provide a hydropathy scale. To overcome the limitations in the existing methods, we have developed a Protocol for Assigning a Residue's Character on the Hydropathy (PARCH) scale that adopts a holistic approach to assigning the hydropathy of a residue. The parch scale evaluates the collective response of the water molecules in the protein's first hydration shell to increasing temperatures. We performed the parch analysis of a set of well-studied proteins that include the following─enzymes, immune proteins, and integral membrane proteins, as well as fungal and virus capsid proteins. Since the parch scale evaluates every residue based on its location, a residue may have very different parch values inside a crevice versus a surface bump. Thus, a residue can have a range of parch values (or hydropathies) dictated by the local geometry. The parch scale calculations are computationally inexpensive and can compare hydropathies of different proteins. The parch analysis can affordably and reliably aid in designing nanostructured surfaces, identifying hydrophilic and hydrophobic patches, and drug discovery.

Regulating Electrostatic Interactions toward Thermoresponsive Hydrogels with Low Critical Solution Temperature

Low critical solution temperature (LCST) of commonly used thermoresponsive polymers in water is basically dominated by hydrophobic interactions. Herein, a novel thermoresponsive system based on electrostatic interactions is reported. By simply loading aluminum chloride (AlCl3 ) into non-responsive poly(2-hydroxyethyl acrylate) (PHEA) hydrogels, PHEA-Al gels turn to have reversible thermoresponsive behavior between transparent and opaque without any volume change. Further investigations by changing metal ion-polymer compositions unravel the necessity of specific electrostatic interactions, namely, cation-dipole bonding interactions between hydroxy groups and trivalent metal ions. The thermoresponsive hydrogel demonstrates high transparency (≈95%), excellent luminous modulation capability (>98%), and cyclic reliability, suggesting great potential as an energy-saving material. Although LCST control by salt addition is widely known, salt-induced expression of thermoresponsiveness has barely been discussed before. This design provides a new approach of easy fabrication, low cost, and scalability to develop stimuli-responsive materials.

Significance of the Disulfide Bridge in the Structure and Stability of Metalloprotein Azurin

Metalloproteins make up a class of proteins that incorporate metal ions into their structures, enabling them to perform essential functions in biological systems, such as catalysis and electron transport. Azurin is one such metalloprotein with copper cofactor, having a β-barrel structure with exceptional thermal stability. The copper metal ion is coordinated at one end of the β-barrel structure, and there is a disulfide bond at the opposite end. In this study, we explore the effect of this disulfide bond in the high thermal stability of azurin by analyzing both the native S-S bonded and S-S nonbonded (S-S open) forms using temperature replica exchange molecular dynamics (REMD). Similar to experimental observations, we find a 35 K decrease in denaturation temperature for S-S open azurin compared to that of the native holo form (420 K). As observed in the case of native holo azurin, the unfolding process of the S-S open form also started with disruptions of the α-helix. The free energy surfaces of the unfolding process revealed that the denaturation event of the S-S open form progresses through different sets of conformational ensembles. Subsequently, we compared the stabilities of individual β-sheet strands of both the S-S bonded and the S-S nonbonded forms of azurin. Further, we examined the contacts between individual residues for the central structures from the free energy surfaces of the S-S nonbonded form. The microscopic origin of the lowering in the denaturation temperature is further supplemented by thermodynamic analysis.

Discovery of Novel Inhibitors of BRD4 for Treating Prostate Cancer: A Comprehensive Case Study for Considering Water Networks in Virtual Screening and Drug Design

Androgen receptor (AR) is the primary target for treating prostate cancer (PCa), which inevitably progresses due to drug-resistant mutations. Bromodomain-containing protein 4 (BRD4) has been a new potential drug target for PCa treatment. Herein, we report the rational design and discovery of novel BRD4 inhibitors through computer-aided drug design (CADD), and a hit compound SQ-1 (IC50 = 676 nM) was identified by structure-based virtual screening (SBVS) with the conserved water network. To optimize the structure of SQ-1, the free energy landscape was constructed, and the binding mechanism was explored by characterizing the water profile and the dissociation mechanism. Finally, the compound SQ-17 with improved inhibitory activity (IC50 < 100 nM) was discovered, which showed potent antiproliferative activity against LNCaP. These data highlighted a successful attempt to identify and optimize a small molecule by comprehensive CADD application and provided essential clues for developing novel therapeutics for PCa treatment.

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity, and Antibody Developability

The electrostatic properties of proteins arise from the number and distribution of polar and charged residues. Electrostatic interactions in proteins play a critical role in numerous processes such as molecular recognition, protein solubility, viscosity, and antibody developability. Thus, characterizing and quantifying electrostatic properties of a protein are prerequisites for understanding these processes. Here, we present PEP-Patch, a tool to visualize and quantify the electrostatic potential on the protein surface in terms of surface patches, denoting separated areas of the surface with a common physical property. We highlight its applicability to elucidate protease substrate specificity and antibody-antigen recognition and predict heparin column retention times of antibodies as an indicator of pharmacokinetics.

A Heteronuclear NMR Study of Aqueous Lithium Salt Solutions of l-Alanine: Revealing Solute Hydrophobic Association through the NMR B' Coefficient

In the present study, a set of heteronuclear NMR approaches has been adopted to investigate the solution behavior of a small hydrophobic solute l-alanine in the presence of lithium (Li) salts. The presence of salts plays a major role in determining the structure and solvation of biomolecules. It therefore evokes interest to understand the effect of Li salts on amino acids (alanine), the building block of biomolecules. The ionic solute dynamics in the present case has been probed using 1H, 7Li, and 13C nuclei available in the aqueous Li salt solution of l-alanine. Nuclear longitudinal spin relaxation of alanine protons was examined at a variable concentration range of three lithium salts, i.e., LiCl, Li2SO4 and LiClO4, to introduce the NMR B' coefficient for each salt defining ionic solute/solvent interaction in the solution. Analysis of the active relaxation mechanism of 7Li spin-lattice relaxation further revealed the presence of alanine in the solvation shell of Li ion depending on the anionic counterpart.

Tailoring the Amphiphilicity of Fluorescent Protein Chromophores to Detect Intracellular Proteome Aggregation in Diverse Biological Samples

The formation of amorphous misfolded and aggregated proteins is a hallmark of proteome stress in diseased cells. Given its lack of defined targeting sites, the rational design of intracellular proteome aggregation sensors has been challenging. Herein, we modulate the amphiphilicity of fluorescent protein chromophores to enable selective detection of aggregated proteins in different biological samples, including recombinant proteins, stressed live cells, intoxicated mouse liver tissue, and human hepatocellular carcinoma tissue. By tuning the number of hydroxyl groups, we optimize the selectivity of fluorescent protein chromophores toward aggregated proteins in these biological samples. In recombinant protein applications, the most hydrophobic P0 (cLogP = 5.28) offers the highest fold change (FC = 31.6), sensitivity (LLOD = 0.1 μM), and brightness (Φ = 0.20) upon binding to aggregated proteins. In contrast, P4 of balanced amphiphilicity (cLogP = 2.32) is required for selective detection of proteome stresses in live cells. In mouse and human liver histology tissues, hydrophobic P1 exhibits the best performance in staining the aggregated proteome. Overall, the amphiphilicity of fluorescent chromophores governs the sensor's performance by matching the diverse nature of different biological samples. Together with common extracellular amyloid sensors (e.g., Thioflavin T), these sensors developed herein for intracellular amorphous aggregation complement the toolbox to study protein aggregation.

Computation of entropy values for non-electrolyte solute molecules in solution based on semi-empirical corrections to a polarized continuum model

A simple heuristic model was developed for estimating the entropy of a solute molecule in an ideal solution based on quantum mechanical calculations with polarizable continuum models (QM/PCMs). A translational term was incorporated that included free-volume compensation for the Sackur-Tetrode equation and a rotational term was modeled based on the restricted rotation of a dipole in an electrostatic field. The configuration term for the solute at a given concentration was calculated using a simple lattice model that considered the number of configurations of the solute within the lattice. The configurational entropy was ascertained from this number based on Boltzmann's principle. Standard entropy values were determined for 41 combinations of solutes and solvents at a set concentration of 1 mol dm^-3 using the proposed model, and the computational values were compared with experimental data. QM/PCM calculations were conducted at the ωB97X-D/6-311++G(d,p)/IEF-PCM level using universal force field van der Waals radii scaled by 1.2. The proposed model accurately reproduced the entropy values reported for solutes in non-aqueous solvents within a mean absolute deviation of 9.2 J mol^-1 K^-1 for 33 solutions. This performance represents a considerable improvement relative to that obtained using the method based on the ideal gas treatment that is widely utilized in commercially available computation packages. In contrast, computations for aqueous molecules overestimated the entropies because hydrophobic effects that decrease the entropy of aqueous solutions were not included in the present model.

Thermostabilizing mechanisms of canonical single amino acid substitutions at a GH1 β-glucosidase probed by multiple MD and computational approaches

β-glucosidases play a pivotal role in second-generation biofuel (2G-biofuel) production. For this application, thermostable enzymes are essential due to the denaturing conditions on the bioreactors. Random amino acid substitutions have originated new thermostable β-glucosidases, but without a clear understanding of their molecular mechanisms. Here, we probe by different molecular dynamics simulation approaches with distinct force fields and submitting the results to various computational analyses, the molecular bases of the thermostabilization of the Paenibacillus polymyxa GH1 β-glucosidase by two-point mutations E96K (TR1) and M416I (TR2). Equilibrium molecular dynamic simulations (eMD) at different temperatures, principal component analysis (PCA), virtual docking, metadynamics (MetaDy), accelerated molecular dynamics (aMD), Poisson-Boltzmann surface analysis, grid inhomogeneous solvation theory and colony method estimation of conformational entropy allow to converge to the idea that the stabilization carried by both substitutions depend on different contributions of three classic mechanisms: (i) electrostatic surface stabilization; (ii) efficient isolation of the hydrophobic core from the solvent, with energetic advantages at the solvation cap; (iii) higher distribution of the protein dynamics at the mobile active site loops than at the protein core, with functional and entropic advantages. Mechanisms i and ii predominate for TR1, while in TR2, mechanism iii is dominant. Loop A integrity and loops A, C, D, and E dynamics play critical roles in such mechanisms. Comparison of the dynamic and topological changes observed between the thermostable mutants and the wildtype protein with amino acid co-evolutive networks and thermostabilizing hotspots from the literature allow inferring that the mechanisms here recovered can be related to the thermostability obtained by different substitutions along the whole family GH1. We hope the results and insights discussed here can be helpful for future rational approaches to the engineering of optimized β-glucosidases for 2G-biofuel production for industry, biotechnology, and science.

Water-soluble Self-assembled {Pd84 }Ac Polyoxopalladate Nano-wheel as a Supramolecular Host

Polyoxopalladates (POPs) are a class of self-assembling palladium-oxide clusters that span a variety of sizes, shapes and compositions. The largest of this family, {Pd₈₄ }^Ac , is constructed from 14 building units of {Pd₆ } and lined on the inner and outer torus by 28 acetate ligands. Due to its high water solubility, large hydrophobic cavity and distinct ¹ H NMR fingerprint {Pd₈₄ }^Ac is an ideal molecule for exploring supramolecular behaviour with small organic molecules in aqueous media. Molecular visualisation studies highlighted potential binding sites between {Pd₈₄ }^Ac and these species. Nuclear Magnetic Resonance (NMR) techniques, including ¹ H NMR, ¹ H Diffusion Ordered Spectroscopy (DOSY) and Nuclear Overhauser Spectroscopy (NOESY), were employed to study the supramolecular chemistry of this system. Here, we provide conclusive evidence that {Pd₈₄ }^Ac forms a 1 : 7 host-guest complex with benzyl viologen (BV²⁺ ) in aqueous solution.

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 β 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.

Collagen type II-hyaluronan interactions - the effect of proline hydroxylation: a molecular dynamics study

Hyaluronan-collagen composites have been employed in numerous biomedical applications. Understanding the interactions between hyaluronan and collagen is particularly important in the context of joint cartilage function and the treatment of joint diseases. Many factors affect the affinity of collagen for hyaluronan. One of the important factors is the ratio of 3- or 4-hydroxy proline to proline residues. This article presents the results from molecular dynamics calculations of HA-collagen type II interactions with hyaluronan. The applied protocol employed docking and geometry optimization of complexes built using collagen structures with different numbers of hydroxyl groups attached to proline moieties. It was established that the hydroxyproline/proline ratio affects both structural and energetic features of the collagen-hyaluronan complex. Proline hydroxylation was found to significantly influence the number of all identified types of molecular forces, hydrophobic interactions, water bridges and hydrogen bonds, which can be formed between collagen and hyaluronan. Importantly, an increase in the hydroxyproline/proline ratio in the collagen chain increases the binding affinity for hyaluronan. This is illustrated by the linear correlation between the binding free energy and the hydroxylation degree. A comparison of the results obtained for 3 and 4 hydroxylation of proline indicates that the hydroxyl group attachment position plays a minor role in complex stabilization. However, a slightly stronger affinity was observed for 4 hydroxylation. In order to evaluate the effect of the aqueous environment on the collagen-hyaluronan complex stability, the enthalpic and entropic contributions to the free energy of solvation were analyzed.

Mechanistic insights into phenanthrene acropetal translocation via wheat xylem: Separation and identification of transfer proteins

Polycyclic aromatic hydrocarbons (PAHs) have the potential to cause cancer, teratogenicity, and mutagenesis in humans. Long-term plant safe production relies on how PAHs are transported and coordinated across organs. However, the acropetal transfer mechanism of PAHs in staple crop stems, particularly in xylem, a critical path, is unknown. Herein, we first confirmed the presence of specific interaction between the proteins and phenanthrene by employing the magnetic phenanthrene-bound bead immunoassay and label free liquid chromatograph mass spectrometer (LC-MS/MS), suggesting that peroxidase (uniprot accession: A0A3B5XXD0) and unidentified proteins (uniprot accession: A0A3B6LUC6) may function as the carriers to load and acropetally translocate phenanthrene (a model PAH) in wheat xylem. This specified binding of protein-phenanthrene may form through hydrophobic interactions in the conservative binding region, as revealed by protein structural investigations and molecular docking. To further investigate the role of these proteins in phenanthrene solubilization, phenanthrene exposure was conducted: a substantial quantity of peroxidase was produced; an unusually high expression of uncharacterized proteins was observed, indicating their positive effects in the acropetal transfer of phenanthrene in wheat xylem. These data confirmed that the two proteins are crucial in the solubilization of phenanthrene in wheat xylem sap. Our findings provide fresh light on the molecular mechanism of PAH loading in plant xylem and techniques for ensuring the security of staple crops and improving the efficacy of phytoremediation in a PAH-contaminated environment.

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.

Grid inhomogeneous solvation theory for cross-solvation in rigid solvents

Grid Inhomogeneous Solvation Theory (GIST) has proven useful to calculate localized thermodynamic properties of water around a solute. Numerous studies have leveraged this information to enhance structure-based binding predictions. We have recently extended GIST toward chloroform as a solvent to allow the prediction of passive membrane permeability. Here, we further generalize the GIST algorithm toward all solvents that can be modeled as rigid molecules. This restriction is inherent to the method and is already present in the inhomogeneous solvation theory. Here, we show that our approach can be applied to various solvent molecules by comparing the results of GIST simulations with thermodynamic integration (TI) calculations and experimental results. Additionally, we analyze and compare a matrix consisting of 100 entries of ten different solvent molecules solvated within each other. We find that the GIST results are highly correlated with TI calculations as well as experiments. For some solvents, we find Pearson correlations of up to 0.99 to the true entropy, while others are affected by the first-order approximation more strongly. The enthalpy-entropy splitting provided by GIST allows us to extend a recently published approach, which estimates higher order entropies by a linear scaling of the first-order entropy, to solvents other than water. Furthermore, we investigate the convergence of GIST in different solvents. We conclude that our extension to GIST reliably calculates localized thermodynamic properties for different solvents and thereby significantly extends the applicability of this widely used method.

Towards understanding solvation effects on the conformational entropy of non-rigid molecules

The absolute molecular entropy is a fundamental quantity for the accurate description of thermodynamic properties. For non-rigid molecules, a substantial part of the entropy can be attributed to a conformational contribution. Systems and properties where this is relevant, e.g., protein-ligand binding affinities or pK_a values refer usually to the liquid phase. In this work, the influence of solvation on the conformational entropy is investigated. A recently introduced state-of-the-art and automated computational protocol for the computation of conformational entropies [Pracht et al., Chem. Sci., 2021, 12, 6551-6568.] is applied in combination with fast and accurate semiempirical quantum-chemical methods and implicit solvation models for a set of 25 commercially available drug molecules and five transition metal compounds. Computed gas-phase conformational entropies are compared with values obtained in implicit n-hexane and water. It is found that implicit solvation can have a substantial effect of several cal mol^-1 K^-1 on the entropy as a result of large conformational changes in the different phases. We conclude that for flexible molecules chemical accuracy for free energies in solution can only be achieved if solvation effects on the conformational ensemble are considered.

Prediction of molecular interactions and physicochemical properties relevant for vasopressin V2 receptor antagonism

We have developed two ligand- and receptor-based computational approaches to study the physicochemical properties relevant to the biological activity of vasopressin V2 receptor (V2R) antagonist and eventually to predict the expected binding mode to V2R. The obtained quantitative structure activity relationship (QSAR) model showed a correlation of the antagonist activity with the hydration energy (E_H2O), the polarizability (P), and the calculated partial charge on atom N7 (q6) of the common substructure. The first two descriptors showed a positive contribution to antagonist activity, while the third one had a negative contribution. V2R was modeled and further relaxed on a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocoline (POPC) membrane by molecular dynamics simulations. The receptor antagonist complexes were guessed by molecular docking, and the stability of the most relevant structures was also evaluated by molecular dynamics simulations. As a result, amino acid residues Q96, W99, F105, K116, F178, A194, F307, and M311 were identified with the probably most relevant antagonist-receptor interactions on the studied complexes. The proposed QSAR model could explain the molecular properties relevant to the antagonist activity. The contributions to the antagonist-receptor interaction appeared also in agreement with the binding mode of the complexes obtained by molecular docking and molecular dynamics. These models will be used in further studies to look for new V2R potential antagonist molecules.

Molecular modeling of interfacial layer-by-layer assembly towards functionalized capsule materials

Encapsulated nanomaterials, such as polymer-coated nanoemulsions, have highly tunable properties leading to versatile applications. A current lack of understanding of the fundamentals governing the choice of "capsule" materials (polyelectrolyte + surfactant) and its ensuing performance effectively precludes their widespread use. Computational methods can start to redress this by discovering molecule-scale attributes that significantly control the design of capsule materials tuned to fit desired properties. We use molecular dynamics (MD) to carry out the layer-by-layer (LbL) assembly of six unique polyelectrolyte bilayer systems at a surfactant-mediated interface, modeling early-stage capsule synthesis. Monolayer thickness is related to layer density and polyelectrolyte/surfactant interaction energy through polyelectrolyte molecular weight and radius of gyration, respectively, yielding a simple relationship between absorption kinetics and layer structure. For the second monolayer, faster absorption kinetics are observed for pairings of polyelectrolytes with similarly sized functional groups. Surfactants with a more delocalized charge on the head-group catalyze the build-up of ions at the interface, resulting in faster absorption kinetics and greater confinement of the encapsulated material but leading to thicker, less uniform bilayers. These relationships between capsule building block molecules and nanomaterial capsule properties provide a foundation for property prediction and rational design of optimized multi-functional capsule materials.

The impact of the length of alkyl chain on the behavior of benzyl alcohol homologues - the interplay between dispersive and hydrogen bond interactions

In this work, we examined the effect of the length of alkyl chain attached to the benzene ring on the self-assembling phenomena for a series of phenyl alcohol (PhA) derivatives, from phenylmethanol (benzyl alcohol) to 7-phenyl-1-heptanol, by means of X-Ray Diffraction (XRD), Differential Scanning Calorimetry (DSC), Fourier Transform Infrared (FTIR) spectroscopy, and Broadband Dielectric Spectroscopy (BDS) methods. XRD data in the reciprocal and real spaces showed a gradual increase in the local order with the elongation of the alkyl chain. However, the position and full width at half maximum of the main diffraction peak exhibited a non-systematic behavior. To better understand this fact, PhAs were subjected to FTIR spectroscopic studies. These investigations revealed that the association degree and the activation energy of dissociation increase as the alkyl chain length grows. On the other hand, BDS data showed a non-monotonic variation in the Kirkwood correlation factor with increasing length of the alkyl chain, indicating a competition between interactions of the non-polar and polar parts of the molecules in the studied PhAs. Finally, it was also found that the molar surface entropy for PhAs increases with the number of methylene groups, approaching values reported for alkanes, which indicates suppression of the surface order for PhAs with a long alkyl chain. This variability of the various parameters as a function of the length of the side chain shows that the interplay between soft interactions has a strong impact on the local structure and intra and intermolecular dynamics of the studied PhAs.

Chirality affects cholesterol-oxysterol association in water, a computational study

Cholesterol (Chol) is the most prevalent sterol in the animal kingdom and an indispensable component of mammalian cell membranes. Chol content in the membrane is strictly controlled, although the oxidation of phospholipids may change the relative content of membrane Chol. An excess of it results in the formation of pure Chol microdomains in the membrane. It is likely that some Chol molecules detach from the domains and self-assemble in the aqueous environment. This may promote Chol microcrystallisation, which initiates the development of gallstones and atherosclerotic plaque. In this study, the molecular dynamics, free energy perturbation, umbrella sampling and Voronoi diagram methods are used to reveal the details of self-association of Chol and its oxidised forms (oxChol), namely 7α,β-hydroxycholesterol and 7α,β-hydroperoxycholesterol, in water. In the first part of the study the interactions between a sterol monomer and water over a short and longer timescale as well as the energy of hydration of each sterol are analysed. This helps one to understand Chol-Chol and Chol-OxChol with different chirality self-association in water better, which is analysed in the second part of the study. The Voronoi diagram approach is used to determine the relative arrangement of molecules in the dimer and, most importantly, to analyse the dehydration of the contacting surfaces of the assembling molecules. Free energy calculations indicate that Chol and 7β-hydroxycholesterol associate into the most stable dimer and that Chol-Chol is the next most stable of the five dimers studied. Employing different computational methods enables us to obtain an adequate picture of Chol-sterol self-association in water, which includes dynamic, energetic and temporal aspects of the process.

Target SARS-CoV-2: theoretical exploration on clinical suitability of certain drugs

We propose a unique theoretical methodology because of the global high priority rating to search for the repurposed drugs that outfit clinical suitability to SARS-CoV-2. The approach is based on the exploration of structural analysis, computation of biothermodynamics, interactions and the prediction of entropy sign successively via molecular dynamics. We tested this methodology for Favipiravir/Dolutegravir drugs on the apo form of SARS-CoV-2 main protease. This theoretical exploration not only suggested the presence of strong interactions between (SARS-CoV-2 + Favipiravir/Dolutegravir) but also emphasized the clinical suitability of Favipiravir over Dolutegravir to treat SARS-CoV-2 main protease. The supremacy of Favipiravir over Doultegravir is well supported by the results of global clinical trials on SARS-CoV-2 infection. Thus, this work will pave the way for incremental advancement towards future design and development of more specific inhibitors to treat SARS-CoV-2 infection in humans.Communicated by Ramaswamy H. Sarma.

Differential Regulation of Bilastine Affinity for Human Histamine H1 Receptors by Lys 179 and Lys 191 via Its Binding Enthalpy and Entropy

Bilastine, a zwitterionic second-generation antihistamine containing a carboxyl group, has higher selectivity for H₁ receptors than first-generation antihistamines. Ligand-receptor docking simulations have suggested that the electrostatic interaction between the carboxyl group of second-generation antihistamines and the amino group of Lys179^ECL2 and Lys191^5.39 of human H₁ receptors might contribute to increased affinity of these antihistamines to H₁ receptors. In this study, we evaluated the roles of Lys179^ECL2 and Lys191^5.39 in regulating the electrostatic and hydrophobic binding of bilastine to H₁ receptors by thermodynamic analyses. The binding enthalpy and entropy of bilastine were estimated from the van ’t Hoff equation using the dissociation constants. These constants were obtained from the displacement curves against the binding of [³H] mepyramine to membrane preparations of Chinese hamster ovary cells expressing wild-type human H₁ receptors and their Lys179^ECL2 or Lys191^5.39 mutants to alanine at various temperatures. We found that the binding of bilastine to wild-type H₁ receptors occurred by enthalpy-dependent binding forces and, more dominantly, entropy-dependent binding forces. The mutation of Lys179^ECL2 and Lys191^5.39 to alanine reduced the affinity of bilastine to H₁ receptors by reducing enthalpy- and entropy-dependent binding forces, respectively. These results suggest that Lys179^ECL2 and Lys191^5.39 differentially contribute to the increased binding affinity to bilastine via electrostatic and hydrophobic binding forces.

Time-dependent conformational analysis of ALK5-lumican complex in presence of graphene and graphene oxide employing molecular dynamics and MMPBSA calculation

Lumican, an extracellular matrix protein avails wound healing by binding to ALK5 membrane receptor (TGF-beta receptor I). Their interaction enables epithelialization and substantiates rejuvenation of injured tissue. To enrich permanence of ALK5-lumican interaction, we employed graphene and graphene oxide co-factors. Herein, this study explicates concomitancy of graphene and graphene oxide with ALK5-lumican. We performed an in silico approach involving molecular modelling, molecular docking, molecular dynamics for 200 ns, DSSP analysis and MMPBSA calculations. Results of molecular dynamics indicate cofactors influential in altering bioactive site of lumican than ALK5. Similarly, MMPBSA calculations unveiled binding energy of apoenzyme as -108.09 kcal/mol, holoenzyme (G) as -79.20 kcal/mol and holoenzyme (GO) as -114.33 kcal/mol. This concludes graphene oxide lucrative in enhancing binding energy of ALK5-lumican in holoenzyme (GO) via coil formation of Lum C₁₃ domain. In contrast, graphene reduced binding energy of ALK5-lumican in holoenzyme (G) modifying Lum C₁₃ into beta sheets. MMPBSA residual contribution analysis of Lum C₁₃ residues revealed binding energy of -13.9 kcal/mol for apoenzyme, -6.8 kcal/mol for holoenzyme (G) and -19.5 kcal/mol for holoenzyme (GO). This supports coil formation propitious for better ALK5-Lum interaction. Highest SASA energy of -21.05 kcal/mol of holoenzyme (G) assures graphene reasonable for improved ALK5-lumican hydrophobicity. As per the motive of the study, graphene oxide enriches permanence of ALK5-lumican. This provides counsel for plausible exploitation of lumican and graphene oxide as targeted/nano drug delivery system to reinstate acute wounds, chronic wounds, corneal wounds, hypertrophic scars and keloids in near future. Communicated by Ramaswamy H. Sarma.

Target SARS-CoV-2: computation of binding energies with drugs of dexamethasone/umifenovir by molecular dynamics using OPLS-AA force field

Introduction

In recent times, myriads of public have been infected with a novel SARS-CoV-2, and the fatality toll has reached thousands and been mounting step by step, which is a major crisis in the world. The challenge for this burning issue pertinent to repurposed medicines which prevent novel coronavirus is of immense concern for all scientists around the globe until the arrival of the vaccine.

Methods

Because of the global high priority rating on the search for the repurposed drugs which outfits clinical suitability to SARS-CoV-2, a unique theoretical methodology is proposed. The approach is based on explorations of biothermodynamics computed via molecular dynamics, root-mean-square deviation (RMSD), radius of gyration (Rg) and interactions. This unique methodology is tested for umifenovir/dexamethasone drugs on (SARS-CoV-2) main protease.

Results

This theoretical exploration not only suggested the presence of strong interactions between (SARS-CoV-2 + umifenovir/dexamethasone) but also emphasized the clinical suitability of dexamethasone over umifenovir to treat SARS-CoV-2. This supremacy of dexamethasone is well supported by the results of global clinical trials and COVID-19 therapeutic approved management guidelines of countries.

Conclusions

Thus, this work will pave a way for incremental advancement towards future design and development of more specific inhibitors for the treatment of SARS-CoV-2 infection in humans.

Computational and theoretical exploration for clinical suitability of Remdesivir drug to SARS-CoV-2

A methodology for the exploration of clinical suitability of Remdesivir drug to SARS-CoV-2 main protease based on the computational, theoretical analysis pertinent to Gibb's free energy computed from the Molecular Dynamic simulations with OPLS-AA force field at 300 K/atmospheric pressure and the variation of thermodynamic potentials over the entire simulation run of 100 ns. This study emphasized the suitability of Remdesivir drug to SARS-CoV-2 protein and the same is emphasized by the results of global clinical trials. This methodology can be applied for future design, development of more specific repurposed inhibitors for the treatment of SARS-CoV-2 infection.

Selective Affimers Recognise the BCL-2 Family Proteins BCL-xL and MCL-1 through Noncanonical Structural Motifs*

The BCL-2 family is a challenging group of proteins to target selectively due to sequence and structural homologies across the family. Selective ligands for the BCL-2 family regulators of apoptosis are useful as probes to understand cell biology and apoptotic signalling pathways, and as starting points for inhibitor design. We have used phage display to isolate Affimer reagents (non-antibody-binding proteins based on a conserved scaffold) to identify ligands for MCL-1, BCL-xL , BCL-2, BAK and BAX, then used multiple biophysical characterisation methods to probe the interactions. We established that purified Affimers elicit selective recognition of their target BCL-2 protein. For anti-apoptotic targets BCL-xL and MCL-1, competitive inhibition of their canonical protein-protein interactions is demonstrated. Co-crystal structures reveal an unprecedented mode of molecular recognition; where a BH3 helix is normally bound, flexible loops from the Affimer dock into the BH3 binding cleft. Moreover, the Affimers induce a change in the target proteins towards a desirable drug-bound-like conformation. These proof-of-concept studies indicate that Affimers could be used as alternative templates to inspire the design of selective BCL-2 family modulators and more generally other protein-protein interaction inhibitors.

Conformational Ensembles of Antibodies Determine Their Hydrophobicity

A major challenge in the development of antibody biotherapeutics is their tendency to aggregate. One root cause for aggregation is exposure of hydrophobic surface regions to the solvent. Many current techniques predict the relative aggregation propensity of antibodies via precalculated scales for the hydrophobicity or aggregation propensity of single amino acids. However, those scales cannot describe the nonadditive effects of a residue’s surrounding on its hydrophobicity. Therefore, they are inherently limited in their ability to describe the impact of subtle differences in molecular structure on the overall hydrophobicity. Here, we introduce a physics-based approach to describe hydrophobicity in terms of the hydration free energy using grid inhomogeneous solvation theory (GIST). We apply this method to assess the effects of starting structures, conformational sampling, and protonation states on the hydrophobicity of antibodies. Our results reveal that high-quality starting structures, i.e., crystal structures, are crucial for the prediction of hydrophobicity and that conformational sampling can compensate errors introduced by the starting structure. On the other hand, sampling of protonation states only leads to good results when combined with high-quality structures, whereas it can even be detrimental otherwise. We conclude by pointing out that a single static homology model may not be adequate for predicting hydrophobicity.

Solvation Thermodynamics in Different Solvents: Water-Chloroform Partition Coefficients from Grid Inhomogeneous Solvation Theory

Reliable information on partition coefficients plays a key role in drug development, as solubility decisively affects bioavailability. In a physicochemical context, the partition coefficient of a solute between two different solvents can be described as a function of solvation free energies. Hence, substantial scientific efforts have been made toward accurate predictions of solvation free energies in various solvents. The grid inhomogeneous solvation theory (GIST) facilitates the calculation of solvation free energies. In this study, we introduce an extended version of the GIST algorithm, which enables the calculation for chloroform in addition to water. Furthermore, GIST allows localization of enthalpic and entropic contributions. We test our approach by calculating partition coefficients between water and chloroform for a set of eight small molecules. We report a Pearson correlation coefficient of 0.96 between experimentally determined and calculated partition coefficients. The capability to reliably predict partition coefficients between water and chloroform and the possibility to localize their contributions allow the optimization of a compound's partition coefficient. Therefore, we presume that this methodology will be of great benefit for the efficient development of pharmaceuticals.

Thermoresponsive Nanogels Based on Different Polymeric Moieties for Biomedical Applications

Nanogels, or nanostructured hydrogels, are one of the most interesting materials in biomedical engineering. Nanogels are widely used in medical applications, such as in cancer therapy, targeted delivery of proteins, genes and DNAs, and scaffolds in tissue regeneration. One salient feature of nanogels is their tunable responsiveness to external stimuli. In this review, thermosensitive nanogels are discussed, with a focus on moieties in their chemical structure which are responsible for thermosensitivity. These thermosensitive moieties can be classified into four groups, namely, polymers bearing amide groups, ether groups, vinyl ether groups and hydrophilic polymers bearing hydrophobic groups. These novel thermoresponsive nanogels provide effective drug delivery systems and tissue regeneration constructs for treating patients in many clinical applications, such as targeted, sustained and controlled release.

Macrocycle Cell Permeability Measured by Solvation Free Energies in Polar and Apolar Environments

The relation of surface polarity and conformational preferences is decisive for cell permeability and thus bioavailability of macrocyclic drugs. Here, we employ grid inhomogeneous solvation theory (GIST) to calculate solvation free energies for a series of six macrocycles in water and chloroform as a measure of passive membrane permeability. We perform accelerated molecular dynamics simulations to capture a diverse structural ensemble in water and chloroform, allowing for a direct profiling of solvent-dependent conformational preferences. Subsequent GIST calculations facilitate a quantitative measure of solvent preference in the form of a transfer free energy, calculated from the ensemble-averaged solvation free energies in water and chloroform. Hence, the proposed method considers how the conformational diversity of macrocycles in polar and apolar solvents translates into transfer free energies. Following this strategy, we find a striking correlation of 0.92 between experimentally determined cell permeabilities and calculated transfer free energies. For the studied model systems, we find that the transfer free energy exceeds the purely water-based solvation free energies as a reliable estimate of cell permeability and that conformational sampling is imperative for a physically meaningful model. We thus recommend this purely physics-based approach as a computational tool to assess cell permeabilities of macrocyclic drug candidates.

STACKED - Solvation Theory of Aromatic Complexes as Key for Estimating Drug Binding

The use of fragments to biophysically characterize a protein binding pocket and determine the strengths of certain interactions is a computationally and experimentally commonly applied approach. Almost all drug like molecules contain at least one aromatic moiety forming stacking interactions in the binding pocket. In computational drug design, the strength of stacking and the resulting optimization of the aromatic core or moiety is usually calculated using high level quantum mechanical approaches. However, as these calculations are performed in a vacuum, solvation properties are neglected. We close this gap by using Grid Inhomogeneous Solvation Theory (GIST) to describe the properties of individual heteroaromatics and complexes and thereby estimate the desolvation penalty. In our study, we investigated the solvation free energies of heteroaromatics frequently occurring in drug design projects in complex with truncated side chains of phenylalanine, tyrosine, and tryptophan. Furthermore, we investigated the properties of drug-fragments crystallized in a fragment-based lead optimization approach investigating PDE-10-A. We do not only find good correlation for the estimated desolvation penalty and the experimental binding free energy, but our calculations also allow us to predict prominent interaction sites. We highlight the importance of including the desolvation penalty of the respective heteroaromatics in stacked complexes to explain the gain or loss in affinity of potential lead compounds.

Hydration thermodynamics of cytosolic phospholipase A2 GIVA predict its membrane-associated parts and its highly hydrated binding site

During biological events, the water molecules associated with the protein are re-oriented to adapt to the new conditions, inducing changes in the system's free energy. The characterization of water structure and thermodynamics may facilitate the prediction of certain biological events, such as the binding of a ligand and the membrane-associated parts of a protein. In this computational study, we calculated the hydration thermodynamics of cytosolic phospholipase A₂ group IV (GIVA cPLA₂) to study the hydration properties of the protein's surface and binding pocket. Hydrophobicity scales and the Grid Inhomogeneous Solvation Theory (GIST) tool were employed for the calculations. The hydrophobic areas of the protein's surface were predicted more accurately with the GIST method rather than with the hydrophobicity scales. Based on this, a model of the protein-membrane complex was constructed. In addition, the calculation revealed the highly hydrated binding pocket that further contribute to our understanding of the ligands' binding. Communicated by Ramaswamy H. Sarma.

Can the roles of polar and non-polar moieties be reversed in non-polar solvents?

Using thermodynamic integration, we study the solvation free energy of 18 amino acid side chain equivalents in solvents with different polarities, ranging from the most polar water to the most non-polar cyclohexane.

Solvation Free Energy as a Measure of Hydrophobicity: Application to Serine Protease Binding Interfaces

Solvation and hydrophobicity play a key role in a variety of biological mechanisms. In substrate binding, but also in structure-based drug design, the thermodynamic properties of water molecules surrounding a given protein are of high interest. One of the main algorithms devised in recent years to quantify thermodynamic properties of water is the grid inhomogeneous solvation theory (GIST), which calculates these features on a grid surrounding the protein. Despite the inherent advantages of GIST, the computational demand is a major drawback, as calculations for larger systems can take days or even weeks. Here, we present a GPU accelerated version of the GIST algorithm, which facilitates efficient estimates of solvation free energy even of large biomolecular interfaces. Furthermore, we show that GIST can be used as a reliable tool to evaluate protein surface hydrophobicity. We apply the approach on a set of nine different proteases calculating localized solvation free energies on the surface of the binding interfaces as a measure of their hydrophobicity. We find a compelling agreement with the hydrophobicity of their substrates, i.e., peptides, binding into the binding cleft, and thus our approach provides a reliable description of hydrophobicity characteristics of these biological interfaces.

Hydration of Aromatic Heterocycles as an Adversary of π-Stacking

Hydration is one of the key players in the protein-ligand binding process. It not only influences the binding process per se, but also the drug's absorption, distribution, metabolism, and excretion properties. To gain insights into the hydration of aromatic cores, the solvation thermodynamics of 40 aromatic mono- and bicyclic systems, frequently occurring in medicinal chemistry, are investigated. Thermodynamics is analyzed with two different methods: grid inhomogeneous solvation theory (GIST) and thermodynamic integration (TI). Our results agree well with previously published experimental and computational solvation free energies. The influence of adding heteroatoms to aromatic systems and how the position of these heteroatoms impacts the compound's interactions with water is studied. The solvation free energies of these heteroaromatics are highly correlated to their gas phase interaction energies with benzene: compounds showing a high interaction energy also have a high solvation free energy value. Therefore, replacing a compound with one having a higher gas phase interaction energy might not result in the expected improvement in affinity. The desolvation costs counteract the higher stacking interactions, hence weakening or even inverting the expected gain in binding free energy.

Molecular Dynamics Gives New Insights into the Glucose Tolerance and Inhibition Mechanisms on β-Glucosidases

β-Glucosidases are enzymes with high importance for many industrial processes, catalyzing the last and limiting step of the conversion of lignocellulosic material into fermentable sugars for biofuel production. However, β-glucosidases are inhibited by high concentrations of the product (glucose), which limits the biofuel production on an industrial scale. For this reason, the structural mechanisms of tolerance to product inhibition have been the target of several studies. In this study, we performed in silico experiments, such as molecular dynamics (MD) simulations, free energy landscape (FEL) estimate, Poisson-Boltzmann surface area (PBSA), and grid inhomogeneous solvation theory (GIST) seeking a better understanding of the glucose tolerance and inhibition mechanisms of a representative GH1 β-glucosidase and a GH3 one. Our results suggest that the hydrophobic residues Y180, W350, and F349, as well the polar one D238 act in a mechanism for glucose releasing, herein called "slingshot mechanism", dependent also on an allosteric channel (AC). In addition, water activity modulation and the protein loop motions suggest that GH1 β-Glucosidases present an active site more adapted to glucose withdrawal than GH3, in consonance with the GH1s lower product inhibition. The results presented here provide directions on the understanding of the molecular mechanisms governing inhibition and tolerance to the product in β-glucosidases and can be useful for the rational design of optimized enzymes for industrial interests.

Topological Water Network Analysis Around Amino Acids

Water molecules play a key role in protein stability, folding, function and ligand binding. Protein hydration has been studied using free energy perturbation algorithms. However, the study of protein hydration without free energy calculation is also an active field of research. Accordingly, topological water network (TWN) analysis has been carried out instead of free energy calculation in the present work to investigate hydration of proteins. Water networks around 20 amino acids in the aqueous solution were explored through molecular dynamics (MD) simulations. These simulation results were compared with experimental observations. Water molecules from the protein data bank structures showed TWN patterns similar to MD simulations. This work revealed that TWNs are effected by the surrounding environment. TWNs could provide valuable clues about the environment around amino acid residues in the proteins. The findings from this study could be exploited for TWN-based drug discovery and development.

A 100-Year Review: Progress on the chemistry of milk and its components

Understanding the chemistry of milk and its components is critical to the production of consistent, high-quality dairy products as well as the development of new dairy ingredients. Over the past 100 yr we have gone from believing that milk has only 3 protein fractions to identifying all the major and minor types of milk proteins as well as discovering that they have genetic variants. The structure and physical properties of most of the milk proteins have been extensively studied. The structure of the casein micelle has been the subject of many studies, and the initial views on submicelles have given way to the current model of the micelle as being assembled as a result of the concerted action of several types of interactions (including hydrophobic and the formation of calcium phosphate nanoclusters). The benefits of this improved knowledge of the type and nature of casein interactions include better control of the cheesemaking process, more functional milk powders, development of new products such as cream liqueurs, and expanded food applications. Increasing knowledge of proteins and minerals was paralleled by developments in the analysis of milk fat and its synthesis together with greater knowledge of its packaging in the milk fat globule membrane. Advances in analytical techniques have been essential to the isolation and characterization of milk components. Milk testing has progressed from gross compositional analyses of the fat and total solids content to the rapid analysis of milk for a wide range of components for various purposes, such as diagnostic issues related to animal health. Up to the 1950s, research on dairy chemistry was mostly focused on topics such as protein fractionation, heat stability, acid-base buffering, freezing point, and the nature of the calcium phosphate present in milk. Between the 1950s and 1970s, there was a major focus on identifying all the main protein types, their sequences, variants, association behavior, and other physical properties. During the 1970s and 1980s, one of the major emphases in dairy research was on protein functionality and fractionation processes. The negative cloud over dairy fat has lifted recently due to multiple reviews and meta-analyses showing no association with chronic issues such as cardiovascular disease, but changing consumer misconceptions will take time. More recently, there has been a great deal of interest in the biological and nutritional components in milk and how these materials were uniquely designed by the cow to achieve this type of purpose.

Structural Insights into σ₁ Receptor Interactions with Opioid Ligands by Molecular Dynamics Simulations

Despite considerable advances over the past years in understanding the mechanisms of action and the role of the σ₁ receptor, several questions regarding this receptor remain unanswered. This receptor has been identified as a useful target for the treatment of a diverse range of diseases, from various central nervous system disorders to cancer. The recently solved issue of the crystal structure of the σ₁ receptor has made elucidating the structure-activity relationship feasible. The interaction of seven representative opioid ligands with the crystal structure of the σ₁ receptor (PDB ID: 5HK1) was simulated for the first time using molecular dynamics (MD). Analysis of the MD trajectories has provided the receptor-ligand interaction fingerprints, combining information on the crucial receptor residues and frequency of the residue-ligand contacts. The contact frequencies and the contact maps suggest that for all studied ligands, the hydrophilic (hydrogen bonding) interactions with Glu172 are an important factor for the ligands' affinities toward the σ₁ receptor. However, the hydrophobic interactions with Tyr120, Val162, Leu105, and Ile124 also significantly contribute to the ligand-receptor interplay and, in particular, differentiate the action of the agonistic morphine from the antagonistic haloperidol.

Balance between hydration enthalpy and entropy is important for ice binding surfaces in Antifreeze Proteins

Antifreeze Proteins (AFPs) inhibit the growth of an ice crystal by binding to it. The detailed binding mechanism is, however, still not fully understood. We investigated three AFPs using Molecular Dynamics simulations in combination with Grid Inhomogeneous Solvation Theory, exploring their hydration thermodynamics. The observed enthalpic and entropic differences between the ice-binding sites and the inactive surface reveal key properties essential for proteins in order to bind ice: While entropic contributions are similar for all sites, the enthalpic gain for all ice-binding sites is lower than for the rest of the protein surface. In contrast to most of the recently published studies, our analyses show that enthalpic interactions are as important as an ice-like pre-ordering. Based on these observations, we propose a new, thermodynamically more refined mechanism of the ice recognition process showing that the appropriate balance between entropy and enthalpy facilitates ice-binding of proteins. Especially, high enthalpic interactions between the protein surface and water can hinder the ice-binding activity.

Mixtures of two self- and mutually-associating liquids: Phase behavior, second virial coefficients, and entropy-enthalpy compensation in the free energy of mixing

The theoretical description of the phase behavior of polymers dissolved in binary mixtures of water and other miscible solvents is greatly complicated by the self- and mutual-association of the solvent molecules. As a first step in treating these complex and widely encountered solutions, we have developed an extension of Flory-Huggins theory to describe mixtures of two self- and mutually-associating fluids comprised of small molecules. Analytic expressions are derived here for basic thermodynamic properties of these fluid mixtures, including the spinodal phase boundaries, the second osmotic virial coefficients, and the enthalpy and entropy of mixing these associating solvents. Mixtures of this kind are found to exhibit characteristic closed loop phase boundaries and entropy-enthalpy compensation for the free energy of mixing in the low temperature regime where the liquid components are miscible. As discussed by Widom et al. [Phys. Chem. Chem. Phys. 5, 3085 (2003)], these basic miscibility trends, quite distinct from those observed in non-associating solvents, are defining phenomenological characteristics of the "hydrophobic effect." We find that our theory of mixtures of associating fluids captures at least some of the thermodynamic features of real aqueous mixtures.