Alamethicin adsorption to a planar lipid bilayer.

The effect of alamethicin and its derivatives on the voltage-dependent capacitance of phosphatidylethanolamine (squalane) membranes was measured using two different methods: lock-in detection and voltage pulse. Alamethicin and its derivatives modulate the voltage-dependent capacitance at voltages lower than the voltage at which alamethicin-induced conductance is detected. The magnitude and sign of this alamethicin-induced capacitance change depends on the aqueous alamethicin concentration and the kind of alamethicin used. Our experimental data can be interpreted as a potential-dependent pseudocapacitance associated with adsorbed alamethicin. Pseudocapacitance is expressed as a function of alamethicin charge, its concentration in the bathing solution and the applied electric field. The theory describes the dependence of the capacitance on applied voltage and alamethicin concentration. When alamethicin is neutral the theory predicts no change of the voltage-dependent capacitance with either sign of applied voltage. Experimental data are consistent with the model in which alamethicin molecules interact with each other while being adsorbed to the membrane surface. The energy of this interaction depends on the alamethicin concentration.     

Multiple calcium binding sites make calmodulin multifunctional

Protein-protein or protein-ion interactions with multisite proteins are essential to the regulation of intracellular and extracellular events. There is, however, limited understanding of how ligand-multisite protein interactions selectively regulate the activities of multiple protein targets. In this paper, we focus on the important calcium (Ca(2+)) binding protein calmodulin (CaM), which has four Ca(2+) ion binding sites and regulates the activity of over 30 other proteins. Recent progress in structural studies has led to significant improvements in the understanding of Ca(2+)-CaM-dependent regulation mechanisms. However, no quantitative model is currently available that can fully explain how the structural diversity of protein interaction surfaces leads to selective activation of protein targets. In this paper, we analyze the multisite protein-ligand binding mechanism using mathematical modelling and experimental data for Ca(2+)-CaM-dependent protein targets. Our study suggests a potential mechanism for selective and differential activation of Ca(2+)-CaM targets by the same CaM molecules, which are involved in a variety of intracellular functions. The close agreement between model predictions and experimental dose-response curves for CaM targets available in the literature suggests that such activation is due to the selective activity of CaM conformations in complexes with variable numbers of Ca(2+) ions. Although the paper focuses on the Ca(2+)-CaM pair as a particularly data rich example, the proposed model predictions are quite general and can easily be extended to other multisite proteins. The results of the study may therefore be proposed as a general explanation for multifunctional target regulation by multisite proteins.     

How Hofmeister ion interactions affect protein stability.

Model compound studies in the literature show how Hofmeister ion interactions affect protein stability. Although model compound results are typically obtained as salting-out constants, they can be used to find out how the interactions affect protein stability. The null point in the Hofmeister series, which divides protein denaturants from stabilizers, arises from opposite interactions with different classes of groups: Hofmeister ions salt out nonpolar groups and salt in the peptide group. Theories of how Hofmeister ion interactions work need to begin by explaining the mechanisms of these two classes of interactions. Salting-out nonpolar groups has been explained by the cavity model, but its use is controversial. When applied to model compound data, the cavity model 1) uses surface tension increments to predict the observed values of the salting-out constants, within a factor of 3, and 2) predicts that the salting-out constant should increase with the number of carbon atoms in the aliphatic side chain of an amino acid, as observed. The mechanism of interaction between Hofmeister ions and the peptide group is not well understood, and it is controversial whether this interaction is ion-specific, or whether it is nonspecific and the apparent specificity resides in interactions with nearby nonpolar groups. A nonspecific salting-in interaction is known to occur between simple ions and dipolar molecules; it depends on ionic strength, not on position in the Hofmeister series. A theory by Kirkwood predicts the strength of this interaction and indicates that it depends on the first power of the ionic strength. Ions interact with proteins in various ways besides the Hofmeister ion interactions discussed here, especially by charge interactions. Much of what is known about these interactions comes from studies by Serge Timasheff and his co-workers. A general model, suitable for analyzing diverse ion-protein interactions, is provided by the two-domain model of Record and co-workers.     

Protein interaction networks in medicine and disease

The physical interaction of proteins is subject to intense investigation that has revealed that proteins are assembled into large densely connected networks. In this review, we will examine how signaling pathways can be combined to form higher order protein interaction networks. By using network graph theory, these interaction networks can be further analyzed for global organization, which has revealed unique aspects of the relationships between protein networks and complex biological phenotypes. Moreover, several studies have shown that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer progression. These relationships suggest a novel paradigm for treatment of complex multigenic disease where the protein interaction network is the target of therapy more so than individual molecules within the network.     

The importance of electrostatic potential in the interaction of sweet proteins with the sweet taste receptor

In addition to many small molecular mass sweeteners there are in nature a few sweet proteins. The molecular volume of sweet proteins is so different from that of common sweeteners that it was difficult to understand how molecules as large as proteins can activate a receptor designed to host small molecules. We have recently shown that sweet proteins can activate the sweet receptor by a mechanism of interaction, called 'wedge model", in which proteins fit a large cavity of the receptor with wedge-shaped surfaces of their structures. In order to substantiate this model we have designed, expressed and characterized seven mutants of MNEI, a single chain monellin. Three uncharged residues of the interaction surface, Met42, Tyr63 and Tyr65, were changed either into acidic or basic residues whereas Asp68, a key acidic residue, was changed into a basic one. As a general trend, we observe that an increase of the negative charge is much more detrimental for sweetness than an increase of positive charge. In addition we show that by a careful choice of a residue at the center of the interface between MNEI and receptor, it is possible even to increase the sweetness of MNEI. These results are fully consistent with the wedge model.     

Biothermodynamic analysis of BSA adsorption to alum gel using isothermal titration calorimetry

In this study, we used ITC (isothermal titration calorimetry) to quantitatively investigate the impacts of temperature and protein concentration on adsorption behavior on a solid surface, using BSA (bovine serum albumin) as a model protein, and alum (aluminum hydroxide) gel as an adsorbent. The zeta potential measurement for alum gel (0.25 mV at pH 9.3) revealed that its surface charge was not strong enough for electrostatic interaction. ITC analysis showed that the BSA-alum gel interaction was entropy-driven, suggesting that during adsorption, water molecules were expelled from the hydration layers of the alum gel and BSA. Therefore, the major mechanism for the BSA-alum gel interaction was hydrophobic interaction rather than electrostatic interaction. This biothermodynamic approach can be helpful not only to identify interaction mechanisms, but also to explore the optimum conditions for protein-adsorbent interactions.     

Abnormal SDS-PAGE migration of cytosolic proteins can identify domains and mechanisms that control surfactant binding

The amino acid substitution or post-translational modification of a cytosolic protein can cause unpredictable changes to its electrophoretic mobility during SDS-PAGE. This type of "gel shifting" has perplexed biochemists and biologists for decades. We identify a mechanism for "gel shifting" that predominates among a set of ALS (amyotrophic lateral sclerosis) mutant hSOD1 (superoxide dismutase) proteins, post-translationally modified hSOD1 proteins, and homologous SOD1 proteins from different organisms. By first comparing how 39 amino acid substitutions throughout hSOD1 affected SDS-PAGE migration, we found that substitutions that caused gel shifting occurred within a single polyacidic domain (residues ~80-101), and were nonisoelectric. Substitutions that decreased the net negative charge of domain 80-101 increased migration; only one substitution increased net negative charge and slowed migration. Capillary electrophoresis, circular dichroism, and size exclusion chromatography demonstrated that amino acid substitutions increase migration during SDS-PAGE by promoting the binding of three to four additional SDS molecules, without significantly altering the secondary structure or Stokes radius of hSOD1-SDS complexes. The high negative charge of domain 80-101 is required for SOD1 gel shifting: neutralizing the polyacidic domain (via chimeric mouse-human SOD1 fusion proteins) inhibited amino acid substitutions from causing gel shifting. These results demonstrate that the pattern of gel shifting for mutant cytosolic proteins can be used to: (i) identify domains in the primary structure that control interactions between denatured cytosolic proteins and SDS and (ii) identify a predominant chemical mechanism for the interaction (e.g., hydrophobic vs. electrostatic).     

Calculation of the total electrostatic energy of a macromolecular system: solvation energies, binding energies, and conformational analysis

In this report we describe an accurate numerical method for calculating the total electrostatic energy of molecules of arbitrary shape and charge distribution, accounting for both Coulombic and solvent polarization terms. In addition to the solvation energies of individual molecules, the method can be used to calculate the electrostatic energy associated with conformational changes in proteins as well as changes in solvation energy that accompany the binding of charged substrates. The validity of the method is examined by calculating the hydration energies of acetate, methyl ammonium, ammonium, and methanol. The method is then used to study the relationship between the depth of a charge within a protein and its interaction with the solvent. Calculations of the relative electrostatic energies of crystal and misfolded conformations of Themiste dyscritum hemerythrin and the VL domain of an antibody are also presented. The results indicate that electrostatic charge-solvent interactions strongly favor the crystal structures. More generally, it is found that charge-solvent interactions, which are frequently neglected in protein structure analysis, can make large contributions to the total energy of a macromolecular system.     

Dimerisation-dependent GTPase reaction of MnmE: how potassium acts as GTPase-activating element

MnmE, a Guanine nucleotide-binding protein conserved between bacteria and man, is involved in the modification of tRNAs. Here we provide biochemical and X-ray structural evidence for a new GTP-hydrolysis mechanism, where the G-domains of MnmE dimerise in a potassium-dependent manner and induce GTP hydrolysis. The structure in the presence of GDP-AlFx and potassium shows how juxtaposition of the subunits induces a conformational change around the nucleotide which reorients the catalytic machinery. A critical glutamate is positioned such as to stabilise or activate the attacking water. Potassium provides a positive charge into the catalytic site in a position analogous to the arginine finger in the Ras-RasGAP system. Mutational studies show that potassium-dependent dimerisation and GTP hydrolysis can be uncoupled and that interaction between the G-domains is a prerequisite for subsequent phosphoryl transfer. We propose a model for the juxtaposition of G-domains in the full-length protein and how it induces conformational changes in the putative tRNA-modification centre.     

Evolutionary dynamics in structured populations

Evolutionary dynamics shape the living world around us. At the centre of every evolutionary process is a population of reproducing individuals. The structure of that population affects evolutionary dynamics. The individuals can be molecules, cells, viruses, multicellular organisms or humans. Whenever the fitness of individuals depends on the relative abundance of phenotypes in the population, we are in the realm of evolutionary game theory. Evolutionary game theory is a general approach that can describe the competition of species in an ecosystem, the interaction between hosts and parasites, between viruses and cells, and also the spread of ideas and behaviours in the human population. In this perspective, we review the recent advances in evolutionary game dynamics with a particular emphasis on stochastic approaches in finite sized and structured populations. We give simple, fundamental laws that determine how natural selection chooses between competing strategies. We study the well-mixed population, evolutionary graph theory, games in phenotype space and evolutionary set theory. We apply these results to the evolution of cooperation. The mechanism that leads to the evolution of cooperation in these settings could be called ‘spatial selection’: cooperators prevail against defectors by clustering in physical or other spaces.     

Quantitative determination of size and shape of surface-bound DNA using an acoustic wave sensor

DNA bending plays a significant role in many biological processes, such as gene regulation, DNA replication, and chromosomal packing. Understanding how such processes take place and how they can, in turn, be regulated by artificial agents for individual oriented therapies is of importance to both biology and medicine. In this work, we describe the application of an acoustic wave device for characterizing the conformation of DNA molecules tethered to the device surface via a biotin-neutravidin interaction. The acoustic energy dissipation per unit mass observed upon DNA binding is directly related to DNA intrinsic viscosity, providing quantitative information on the size and shape of the tethered molecules. The validity of the above approach was verified by showing that the predesigned geometries of model double-stranded and triple-helix DNA molecules could be quantitatively distinguished: the resolution of the acoustic measurements is sufficient to allow discrimination between same size DNA carrying a bent at different positions along the chain. Furthermore, the significance of this analysis to the study of biologically relevant systems is shown during the evaluation of DNA conformational change upon protein (histone) binding.     

Constitutive and agonist-dependent homo-oligomerization of the thyrotropin-releasing hormone receptor. Detection in living cells using bioluminescence resonance energy transfer

The ability of G-protein-coupled receptors (GPCRs) to interact to form new functional structures, either forming oligomers with themselves or forming associations with other intracellular proteins, has important implications for the regulation of cellular events; however, little is known about how this occurs. Here, we have employed a newly emerging technology, bioluminescence resonance energy transfer (BRET), used to study protein-protein interactions in living cells, to demonstrate that the thyrotropin-releasing hormone receptor (TRHR) forms constitutive homo-oligomers. This formation of TRHR homo-oligomers in the absence of ligand was shown by demonstration of an energy transfer between TRHR molecules fused to either donor, Renilla luciferase (Rluc) or acceptor, enhanced yellow fluorescent protein (EYFP) molecules. This interaction was shown to be specific, since energy transfer was not detected between co-expressed tagged TRHRs and either complementary tagged gonadotropin-releasing hormone (GnRH) or beta(2)-adrenergic receptors. Furthermore, generation of a BRET signal between the TRHRs could only be inhibited by co-expression of the wild-type TRHR and not by other GPCRs. Agonist stimulation led to a time- and dose-dependent increase in the amount of energy transfer. Inhibition of receptor internalization by co-expression of dynamin mutant K44A did not affect the interaction between TRHRs, suggesting that clustering of receptors within clathrin-coated pits is not sufficient for energy transfer to occur. BRET also provided evidence for the agonist-induced oligomerization of another GPCR, the GnRH receptor (GnRHR), and the presence of an agonist-induced interaction of the adaptor protein, beta-arrestin, with TRHR and the absence of an interaction of beta-arrestin with GnRHR. This study supports the usefulness of BRET as a powerful tool for studying GPCR aggregations and receptor/protein interactions in general and presents evidence that the functioning unit of TRHRs exists as homomeric complexes.     

Prediction of regulation relationship between protein interactions in signaling networks

The discovery of regulation relationship of protein interactions is crucial for the mechanism research in signaling network. Bioinformatics methods can be used to accelerate the discovery of regulation relationship between protein interactions, to distinguish the activation relations from inhibition relations. In this paper, we describe a novel method to predict the regulation relations of protein interactions in the signaling network. We detected 4,417 domain pairs that were significantly enriched in the activation or inhibition dataset. Three machine learning methods, logistic regression, support vector machines(SVMs), and naïve bayes, were explored in the classifier models. The prediction power of three different models was evaluated by 5-fold cross-validation and the independent test dataset. The area under the receiver operating characteristic curve for logistic regression, SVM, and naïve bayes models was 0.946, 0.905 and 0.809, respectively. Finally, the logistic regression classifier was applied to the human proteome-wide interaction dataset, and 2,591 interactions were predicted with their regulation relations, with 2,048 in activation and 543 in inhibition. This model based on domains can be used to identify the regulation relations between protein interactions and furthermore reconstruct signaling pathways.     

Specific interactions in proteins due to proton fluctuations

A theory of site–site interaction due to proton/charge fluctuations in protein molecules has been developed. It is shown that, with the proper geometric configuration of identical ionizable groups on matching sites, a specific attraction may be established. This attractive force has a bell-shaped pH dependence and is maximal close to the pK of the groups involved. Various types of protein interactions are examined in the light of this theory.