Equilibrium self-assembly of colloids with distinct interaction sites: Thermodynamics, percolation, and cluster distribution functions

We calculate the equilibrium thermodynamic properties, percolation threshold, and cluster distribution functions for a model of associating colloids, which consists of hard spherical particles having on their surfaces three short-ranged attractive sites (sticky spots) of two different types, A and B. The thermodynamic properties are calculated using Wertheim's perturbation theory of associating fluids. This also allows us to find the onset of self-assembly, which can be quantified by the maxima of the specific heat at constant volume. The percolation threshold is derived, under the no-loop assumption, for the correlated bond model: In all cases it is two percolated phases that become identical at a critical point, when one exists. Finally, the cluster size distributions are calculated by mapping the model onto an effective model, characterized by a-state-dependent-functionality (f) over bar and unique bonding probability (p) over bar. The mapping is based on the asymptotic limit of the cluster distributions functions of the generic model and the effective parameters are defined through the requirement that the equilibrium cluster distributions of the true and effective models have the same number-averaged and weight-averaged sizes at all densities and temperatures. We also study the model numerically in the case where BB interactions are missing. In this limit, AB bonds either provide branching between A-chains (Y-junctions) if epsilon(AB)/epsilon(AA) is small, or drive the formation of a hyperbranched polymer if epsilon(AB)/epsilon(AA) is large. We find that the theoretical predictions describe quite accurately the numerical data, especially in the region where Y-junctions are present. There is fairly good agreement between theoretical and numerical results both for the thermodynamic (number of bonds and phase coexistence) and the connectivity properties of the model (cluster size distributions and percolation locus).

Percolation of colloids with distinct interaction sites

We generalize the Flory-Stockmayer theory of percolation to a model of associating (patchy) colloids, which consists of hard spherical particles, having on their surfaces f short-ranged-attractive sites of m different types. These sites can form bonds between particles and thus promote self-assembly. It is shown that the percolation threshold is given in terms of the eigenvalues of a m x m matrix, which describes the recursive relations for the number of bonded particles on the ith level of a cluster with no loops; percolation occurs when the largest of these eigenvalues equals unity. Expressions for the probability that a particle is not bonded to the giant cluster, for the average cluster size and the average size of a cluster to which a randomly chosen particle belongs, are also derived. Explicit results for these quantities are computed for the case f = 3 and m = 2. We show how these structural properties are related to the thermodynamics of the associating system by regarding bond formation as a (equilibrium) chemical reaction. This solution of the percolation problem, combined with Wertheim's thermodynamic first-order perturbation theory, allows the investigation of the interplay between phase behavior and cluster formation for general models of patchy colloids.

Structural and functional interaction sites between Na,K-ATPase and FXYD proteins.

Several members of the FXYD protein family are tissue-specific regulators of Na,K-ATPase that produce distinct effects on its apparent K(+) and Na(+) affinity. Little is known about the interaction sites between the Na,K-ATPase alpha subunit and FXYD proteins that mediate the efficient association and/or the functional effects of FXYD proteins. In this study, we have analyzed the role of the transmembrane segment TM9 of the Na,K-ATPase alpha subunit in the structural and functional interaction with FXYD2, FXYD4, and FXYD7. Mutational analysis combined with expression in Xenopus oocytes reveals that Phe(956), Glu(960), Leu(964), and Phe(967) in TM9 of the Na,K-ATPase alpha subunit represent one face interacting with the three FXYD proteins. Leu(964) and Phe(967) contribute to the efficient association of FXYD proteins with the Na,K-ATPase alpha subunit, whereas Phe(956) and Glu(960) are essential for the transmission of the functional effect of FXYD proteins on the apparent K(+) affinity of Na,K-ATPase. The relative contribution of Phe(956) and Glu(960) to the K(+) effect differs for different FXYD proteins, probably reflecting the intrinsic differences of FXYD proteins on the apparent K(+) affinity of Na,K-ATPase. In contrast to the effect on the apparent K(+) affinity, Phe(956) and Glu(960) are not involved in the effect of FXYD2 and FXYD4 on the apparent Na(+) affinity of Na,K-ATPase. The mutational analysis is in good agreement with a docking model of the Na,K-ATPase/FXYD7 complex, which also predicts the importance of Phe(956), Glu(960), Leu(964), and Phe(967) in subunit interaction. In conclusion, by using mutational analysis and modeling, we show that TM9 of the Na,K-ATPase alpha subunit exposes one face of the helix that interacts with FXYD proteins and contributes to the stable interaction with FXYD proteins, as well as mediating the effect of FXYD proteins on the apparent K(+) affinity of Na,K-ATPase.

Identification of continuous interaction sites in PLA(2)-based protein complexes by peptide arrays

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Evidence for two nonidentical drug-interaction sites in the human P-glycoprotein

Human P-glycoprotein (Pgp) confers multidrug resistance to cancer cells by ATP-dependent extrusion of a great many structurally dissimilar hydrophobic compounds. The manner in which Pgp recognizes these different substrates is unknown. The protein shows internal homology between its N- and C-terminal halves, each comprised of six putative transmembrane helices and a consensus ATP binding/utilization site. Photoactive derivatives of certain Pgp substrates specifically label two regions, one on each half of the protein. In this study, using [125I]iodoarylazidoprazosin ([125I]IAAP), a photoactive analog of prazosin, we have demonstrated the presence of two nonidentical drug-interaction sites within Pgp. Taking advantage of a highly susceptible trypsin cleavage site in the linker region of Pgp, we characterized the [125I]IAAP binding to the N- and C-terminal halves. cis(Z)-Flupentixol, a modulator of Pgp function, preferentially increased the affinity of [125I]IAAP for the C-terminal half of the protein (C-site) by reducing the Kd from 20 to 6 nM without changing the labeling or affinity (Kd = 42–46 nM) of the N-terminal half (N-site). Also, the concentration of vinblastine (Pgp substrate) and cyclosporin A (Pgp modulator) required for 50% inhibition of [125I]IAAP binding to the C-site was increased 5- to 6-fold by cis(Z)-flupentixol without any effect on the N-site. In addition, [125I]IAAP binding to the N-site was less susceptible than to C-site to inhibition by vanadate which blocks ATP hydrolysis and drug transport. These data demonstrate the presence of at least two nonidentical substrate interaction sites in Pgp.

Mapping interaction sites within the N-terminus of the calcitonin gene-related peptide receptor; the role of residues 23-60 of the calcitonin receptor-like receptor

The calcitonin receptor-like receptor (CLR) acts as a receptor for the calcitonin gene-related peptide (CGRP) but in order to recognize CGRP, it must form a complex with an accessory protein, receptor activity modifying protein 1 (RAMP1). Identifying the protein/protein and protein/ligand interfaces in this unusual complex would aid drug design. The role of the extreme N-terminus of CLR (Glu23-Ala60) was examined by an alanine scan and the results were interpreted with the help of a molecular model. The potency of CGRP at stimulating cAMP production was reduced at Leu41Ala, Gln45Ala, Cys48Ala and Tyr49Ala; furthermore, CGRP-induced receptor internalization at all of these receptors was also impaired. Ile32Ala, Gly35Ala and Thr37Ala all increased CGRP potency. CGRP specific binding was abolished at Leu41Ala, Ala44Leu, Cys48Ala and Tyr49Ala. There was significant impairment of cell surface expression of Gln45Ala, Cys48Ala and Tyr49Ala. Cys48 takes part in a highly conserved disulfide bond and is probably needed for correct folding of CLR. The model suggests that Gln45 and Tyr49 mediate their effects by interacting with RAMP1 whereas Leu41 and Ala44 are likely to be involved in binding CGRP. Ile32, Gly35 and Thr37 form a separate cluster of residues which modulate CGRP binding. The results from this study may be applicable to other family B GPCRs which can associate with RAMPs.

The use of confocal laser scanning microscopy to analyze the process of parasitic protozoon-host cell interaction

In this communication we review the results obtained with the confocal laser scanning microscope to characterize the interaction of epimastigote and trypomastigote forms of Trypanosoma cruzi and tachyzoites of Toxoplasma gondii with host cells. Early events of the interaction process were studied by the simultaneous localization of sites of protein phosphorylation, revealed by immunocytochemistry, and sites of actin assembly, revealed by the use of labeled phaloidin. The results obtained show that proteins localized in the interaction sites are phosphorylated. The process of formation of the parasitophorous vacuole was monitored by labeling the host cell surface with fluorescent probes for lipids (PKH26), proteins (DTAF) and sialic acid (FITC-thiosemicarbazide) before interaction with the parasites. Evidence was obtained indicating transfer of components of the host cell surface to the parasite surface in the beginning of the interaction process. We also analyzed the distribution of cytoskeletal structures (microtubules and microfilaments visualized with specific antibodies), mitochondria (visualized with rhodamine 123), the Golgi complex (visualized with C6-NBD-ceramide) and the endoplasmic reticulum (visualized with anti-reticulin antibodies and DIOC6) during the evolution of intracellular parasitism. The results obtained show that some, but not all, structures change their position during evolution of the intracellular parasitism.

Structural and functional evidence for membrane docking and disruption sites on phospholipase A2-like proteins revealed by complexation with the inhibitor suramin

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multiplex selection technique (MuST): an approach to clone transcription factor binding sites.

We have used a multiplex selection approach to construct a library of DNA-protein interaction sites recognized by many of the DNA-binding proteins present in a cell type. An estimated minimum of two-thirds of the binding sites present in a library prepared from activated Jurkat T cells represent authentic transcription factor binding sites. We used the library for isolation of "optimal" binding site probes that facilitated cloning of a factor and to identify binding activities induced within 2 hr of activation of Jurkat cells. Since a large fraction of the oligonucleotides obtained appear to represent "optimal" binding sites for sequence-specific DNA-binding proteins, it is feasible to construct a catalog of consensus binding sites for DNA-binding proteins in a given cell type. Qualitative and quantitative comparisons of the catalogs of binding site sequences from various cell types could provide valuable insights into the process of differentiation acting at the level of transcriptional control.

A THEORETICAL STUDY OF INTERACTION OF NANOPARTICLES WITH BIOMOLECULE

Many types of materials at nanoscale are currently being used in everyday life. The production and use of such products based on engineered nanomaterials have raised concerns of the possible risks and hazards associated with these nanomaterials. In order to evaluate and gain a better understanding of their effects on living organisms, we have performed first-principles quantum mechanical calculations and molecular dynamics simulations. Specifically, we will investigate the interaction of nanomaterials including semiconducting quantum dots and metallic nanoparticles with various biological molecules, such as dopamine, DNA nucleobases and lipid membranes. Firstly, interactions of semiconducting CdSe/CdS quantum dots (QDs) with the dopamine and the DNA nucleobase molecules are investigated using similar quantum mechanical approach to the one used for the metallic nanoparticles. A variety of interaction sites are explored. Our results show that small-sized Cd4Se4 and Cd4S4 QDs interact strongly with the DNA nucleobase if a DNA nucleobase has the amide or hydroxyl chemical group. These results indicate that these QDs are suitable for detecting subcellular structures, as also reported by experiments. The next two chapters describe a preparation required for the simulation of nanoparticles interacting with membranes leading to accurate structure models for the membranes. We develop a method for the molecular crystalline structure prediction of 1,2-Dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC), 1,2-Dimyristoyl-sn-glycero-3-phosphorylethanolamine (DMPE) and cyclic di-amino acid peptide using first-principles methods. Since an accurate determination of the structure of an organic crystal is usually an extremely difficult task due to availability of the large number of its conformers, we propose a new computational scheme by applying knowledge of symmetry, structural chemistry and chemical bonding to reduce the sampling size of the conformation space. The interaction of metal nanoparticles with cell membranes is finally carried out by molecular dynamics simulations, and the results are reported in the last chapter. A new force field is developed which accurately describes the interaction forces between the clusters representing small-sized metal nanoparticles and the lipid bilayer molecules. The permeation of nanoparticles into the cell membrane is analyzed together with the RMSD values of the membrane modeled by a lipid bilayer. The simulation results suggest that the AgNPs could cause the same amount of deformation as the AuNPs for the dysfunction of the membrane.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Force-induced globule-coil transition in laminin binding protein and its role for viral-cell membrane fusion.

The specific interactions of the pairs laminin binding protein (LBP)-purified tick-borne encephalitis viral surface protein E and certain recombinant fragments of this protein, as well as West Nile viral surface protein E and certain recombinant fragments of that protein, are studied by combined methods of single-molecule dynamic force spectroscopy (SMDFS), enzyme immunoassay and optical surface waves-based biosensor measurements. The experiments were performed at neutral pH (7.4) and acid pH (5.3) conditions. The data obtained confirm the role of LBP as a cell receptor for two typical viral species of the Flavivirus genus. A comparison of these data with similar data obtained for another cell receptor of this family, namely human αVβ3 integrin, reveals that both these receptors are very important. Studying the specific interaction between the cell receptors in question and specially prepared monoclonal antibodies against them, we could show that both interaction sites involved in the process of virus-cell interaction remain intact at pH 5.3. At the same time, for these acid conditions characteristic for an endosome during flavivirus-cell membrane fusion, SMDFS data reveal the existence of a force-induced (effective already for forces as small as 30-70 pN) sharp globule-coil transition for LBP and LBP-fragments of protein E complexes. We argue that this conformational transformation, being an analog of abrupt first-order phase transition and having similarity with the famous Rayleigh hydrodynamic instability, might be indispensable for the flavivirus-cell membrane fusion process. Copyright © 2014 John Wiley & Sons, Ltd.

Stoichiometry of Heteromeric BAFF and APRIL Cytokines Dictates Their Receptor Binding and Signaling Properties.

The closely related TNF family ligands B cell activation factor (BAFF) and a proliferation-inducing ligand (APRIL) serve in the generation and maintenance of mature B-lymphocytes. Both BAFF and APRIL assemble as homotrimers that bind and activate several receptors that they partially share. However, heteromers of BAFF and APRIL that occur in patients with autoimmune diseases are incompletely characterized. The N and C termini of adjacent BAFF or APRIL monomers are spatially close and can be linked to create single-chain homo- or hetero-ligands of defined stoichiometry. Similar to APRIL, heteromers consisting of one BAFF and two APRILs (BAA) bind to the receptors B cell maturation antigen (BCMA), transmembrane activator and CAML interactor (TACI) but not to the BAFF receptor (BAFFR). Heteromers consisting of one APRIL and two BAFF (ABB) bind to TACI and BCMA and weakly to BAFFR in accordance with the analysis of the receptor interaction sites in the crystallographic structure of ABB. Receptor binding correlated with activity in reporter cell line assays specific for BAFFR, TACI, or BCMA. Single-chain BAFF (BBB) and to a lesser extent single-chain ABB, but not APRIL or single-chain BAA, rescued BAFFR-dependent B cell maturation in BAFF-deficient mice. In conclusion, BAFF-APRIL heteromers of different stoichiometries have distinct receptor-binding properties and activities. Based on the observation that heteromers are less active than BAFF, we speculate that their physiological role might be to down-regulate BAFF activity.

Molecular dynamics simulation of the spherical electrical double layer of a soft nanoparticle. Effect of the surface and counterion valence

Molecular dynamics simulations were performed to study the ion and water distribution around a spherical charged nanoparticle. A soft nanoparticle model was designed using a set of hydrophobic interaction sites distributed in six concentric spherical layers. In order to simulate the effect of charged functionalyzed groups on the nanoparticle surface, a set of charged sites were distributed in the outer layer. Four charged nanoparticle models, from a surface charge value of −0.035 Cm−2 to − 0.28 Cm−2, were studied in NaCl and CaCl2 salt solutions at 1 M and 0.1 M concentrations to evaluate the effect of the surface charge, counterion valence, and concentration of added salt. We obtain that Na + and Ca2 + ions enter inside the soft nanoparticle. Monovalent ions are more accumulated inside the nanoparticle surface, whereas divalent ions are more accumulated just in the plane of the nanoparticle surface sites. The increasing of the the salt concentration has little effect on the internalization of counterions, but significantly reduces the number of water molecules that enter inside the nanoparticle. The manner of distributing the surface charge in the nanoparticle (uniformly over all surface sites or discretely over a limited set of randomly selected sites) considerably affects the distribution of counterions in the proximities of the nanoparticle surface.

O ESTADO DA ARTE DA LIGAÇÃO DE HIDROGÊNIO

Along the historical background of science, the hydrogen bond became widely known as the universal interaction, thus playing a key role in many molecular processes. Through the available theoretical approaches, many of these processes can be unveiled on the basis of the molecular parameters of the subject intermolecular system, such as the variation of bond length and mainly the frequency shift observed in the proton donor. Supported by the natural bond analysis (NBO) with the quantification of the hybridization contributions, the structural deformations and vibrational effects cited above are also attributed to the outcome of the intermolecular interaction strength, which consequently can be estimated by means of the quantum theory of atoms in molecules (QTAIM) as well as evaluated by the symmetry-adapted perturbation theory (SAPT). Moreover, to identify the preferential interaction sites for proton donors and acceptors, the molecular electrostatic potential (MEP) is useful in this regard.