Analysis of thermodynamic non-ideality in terms of protein solvation

The effects of thermodynamic non-ideality on the forms of sedimentation equilibrium distributions for several isoelectric proteins have been analysed on the statistical-mechanical basis of excluded volume to obtain an estimate of the extent of protein solvation. Values of the effective solvation. parameter delta are reported for ellipsoidal as well as spherical models of the proteins, taken to be rigid, impenetrable macromolecular structures. The dependence of the effective solvated radius upon protein molecular mass exhibits reasonable agreement with the relationship calculated for a model in which the unsolvated protein molecule is surrounded by a 0.52-nm solvation shell. Although the observation that this shell thickness corresponds to a double layer of water molecules may be of questionable relevance to mechanistic interpretation of protein hydration, it augurs well for the assignment of magnitudes to the second virial coefficients of putative complexes in the quantitative characterization of protein-protein interactions under conditions where effects of thermodynamic non-ideality cannot justifiably be neglected. (C) 2001 Elsevier Science B.V. All rights reserved.

Studies of solute self-association by sedimentation equilibrium: allowance for effects of thermodynamic non-ideality beyond the consequences of nearest-neighbor interactions

A sedimentation equilibrium study of a-chymotrypsin self-association in acetate-chloride buffer, pH 4.1 I 0.05, has been used to illustrate determination of a dimerization constant under conditions where thermodynamic non-ideality is manifested beyond the consequences of nearest-neighbor interactions. Because the expressions for the experimentally determinable interaction parameters comprise a mixture of equilibrium constant and excluded volume terms, the assignment of reasonable magnitudes to the relevant virial coefficients describing non-associative cluster formation is essential for the evaluation of a reliable estimate of the dimerization constant. Determination of these excluded volume parameters by numerical integration over the potential-of-mean-force is shown to be preferable to their calculation by approximate analytical solutions of the integral for this relatively small enzyme monomer with high net charge (+ 10) under conditions of low ionic strength (0.05 M). (C) 2001 Elsevier Science B.V. All rights reserved.

Solution Structures of the cis- and trans-Pro30 Isomers of a Novel 38-Residue Toxin from the Venom of Hadronyche Infensa sp. that Contains a Cystine-Knot Motif within Its Four Disulfide Bonds

The primary sequence and three-dimensional structure of a novel peptide toxin isolated from the Australian funnel-web spider Hadronyche infensa sp. is reported. ACTX-HI:OB4219 contains 38 amino acids, including eight-cysteine residues that form four disulfide bonds. The connectivities of these disulfide bonds were previously unknown but have been unambiguously determined in this study. Three of these disulfide bonds are arranged in an inhibitor cystine-knot (ICK) motif, which is observed in a range of other disulfide-rich peptide toxins. The motif incorporates an embedded ring in the structure formed by two of the disulfides and their connecting backbone segments penetrated by a third disulfide bond. Using NMR spectroscopy, we determined that despite the isolation of a single native homologous product by RP-HPLC, ACTX-HI:OB4219 possesses two equally populated conformers in solution. These two conformers were determined to arise from cis/trans isomerization of the bond preceding Pro30. Full assignment of the NMR spectra for both conformers allowed for the calculation of their structures, revealing, the presence of a triple-stranded antiparallel sheet consistent with the inhibitor cystine-knot (ICK) motif.

NMR analysis of covalent intermediates in thiamin diphosphate enzymes

Enzymic catalysis proceeds via intermediates formed in the course of substrate conversion. Here, we directly detect key intermediates in thiamin diphosphate (ThDP)-dependent enzymes during catalysis using H-1 NMR spectroscopy. The quantitative analysis of the relative intermediate concentrations allows the determination of the microscopic rate constants of individual catalytic steps. As demonstrated for pyruvate decarboxylase (PDC), this method, in combination with site-directed mutagenesis, enables the assignment of individual side chains to single steps in catalysis. In PDC, two independent proton relay systems and the stereochemical control of the enzymic environment account for proficient catalysis proceeding via intermediates at carbon 2 of the enzyme-bound cofactor. The application of this method to other ThDP-dependent enzymes provides insight into their specific chemical pathways.

Thermodynamic pathway for the formation of SnSe and SnSe2 polycrystalline thin films by selenization of metal precursors

In this work, tin selenide thin films (SnSex) were grown on soda lime glass substrates by selenization of dc magnetron sputtered Sn metallic precursors. Selenization was performed at maximum temperatures in the range 300 °C to 570 °C. The thickness and the composition of the films were analysed using step profilometry and energy dispersive spectroscopy, respectively. The films were structurally and optically investigated by X-ray diffraction, Raman spectroscopy and optical transmittance and reflectance measurements. X-Ray diffraction patterns suggest that for temperatures between 300 °C and 470 °C, the films are composed of the hexagonal-SnSe2 phase. By increasing the temperature, the films selenized at maximum temperatures of 530 °C and 570 °C show orthorhombic-SnSe as the dominant phase with a preferential crystal orientation along the (400) crystallographic plane. Raman scattering analysis allowed the assignment of peaks at 119 cm−1 and 185 cm−1 to the hexagonal-SnSe2 phase and those at 108 cm−1, 130 cm−1 and 150 cm−1 to the orthorhombic-SnSe phase. All samples presented traces of condensed amorphous Se with a characteristic Raman peak located at 255 cm−1. From optical measurements, the estimated band gap energies for hexagonal-SnSe2 were close to 0.9 eV and 1.7 eV for indirect forbidden and direct transitions, respectively. The samples with the dominant orthorhombic-SnSe phase presented estimated band gap energies of 0.95 eV and 1.15 eV for indirect allowed and direct allowed transitions, respectively.

A study of ternary Cu2SnS3 and Cu3SnS4 thin films prepared by sulfurizing stacked metal precursors

Thin films of Cu2SnS3 and Cu3SnS4 were grown by sulfurization of dc magnetron sputtered Sn–Cu metallic precursors in a S2 atmosphere. Different maximum sulfurization temperatures were tested which allowed the study of the Cu2SnS3 phase changes. For a temperature of 350 ◦C the films were composed of tetragonal (I -42m) Cu2SnS3. The films sulfurized at a maximum temperature of 400 ◦C presented a cubic (F-43m) Cu2SnS3 phase. On increasing the temperature up to 520 ◦C, the Sn content of the layer decreased and orthorhombic (Pmn21) Cu3SnS4 was formed. The phase identification and structural analysis were performed using x-ray diffraction (XRD) and electron backscattered diffraction (EBSD) analysis. Raman scattering analysis was also performed and a comparison with XRD and EBSD data allowed the assignment of peaks at 336 and 351 cm−1 for tetragonal Cu2SnS3, 303 and 355 cm−1 for cubic Cu2SnS3, and 318, 348 and 295 cm−1 for the Cu3SnS4 phase. Compositional analysis was done using energy dispersive spectroscopy and induced coupled plasma analysis. Scanning electron microscopy was used to study the morphology of the layers. Transmittance and reflectance measurements permitted the estimation of absorbance and band gap. These ternary compounds present a high absorbance value close to 104 cm−1. The estimated band gap energy was 1.35 eV for tetragonal (I -42m) Cu2SnS3, 0.96 eV for cubic (F-43m) Cu2SnS3 and 1.60 eV for orthorhombic (Pmn21) Cu3SnS4. A hot point probe was used for the determination of semiconductor conductivity type. The results show that all the samples are p-type semiconductors. A four-point probe was used to obtain the resistivity of these samples. The resistivities for tetragonal Cu2SnS3, cubic Cu2SnS3 and orthorhombic (Pmn21) Cu3SnS4 are 4.59 × 10−2 cm, 1.26 × 10−2 cm, 7.40 × 10−4 cm, respectively.

The isolation and characterization of cytochrome c nitrite reductase subunits (NrfA and NrfH) from Desulfovibrio desulfuricans ATCC 27774

Eur. J. Biochem. 270, 3904–3915 (2003)

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.

Task partitioning and priority assignment for distributed hard real-time systems

In this paper, we propose the Distributed using Optimal Priority Assignment (DOPA) heuristic that finds a feasible partitioning and priority assignment for distributed applications based on the linear transactional model. DOPA partitions the tasks and messages in the distributed system, and makes use of the Optimal Priority Assignment (OPA) algorithm known as Audsley’s algorithm, to find the priorities for that partition. The experimental results show how the use of the OPA algorithm increases in average the number of schedulable tasks and messages in a distributed system when compared to the use of Deadline Monotonic (DM) usually favoured in other works. Afterwards, we extend these results to the assignment of Parallel/Distributed applications and present a second heuristic named Parallel-DOPA (P-DOPA). In that case, we show how the partitioning process can be simplified by using the Distributed Stretch Transformation (DST), a parallel transaction transformation algorithm introduced in [1].

Desulfovibrio gigas ferredoxin II: redox structural modulation of the [3Fe–4S] cluster

J Biol Inorg Chem (2006) 11: 307–315 DOI 10.1007/s00775-005-0077-2

The isolation and characterization of cytochrome c nitrite reductase subunits (NrfA and NrfH) from Desulfovibrio desulfuricans ATCC 27774

Eur. J. Biochem. 270, 3904–3915 (2003) doi:10.1046/j.1432-1033.2003.03772.x

Characterization of novel heme-containing sensor proteins from Geobacter sulfurreducens

The focus of this Thesis was the study of the sensor domains of two heme-containing methyl-accepting chemotaxis proteins (MCP) from Geobacter sulfurreducens: GSU0582 and GSU0935. These domains contain one c-type heme, form swapped dimers with a PAS-like fold and are the first examples of a new class of heme sensors. NMR spectroscopy was used to assign the heme and polypeptide signals in both sensors, as a first step to probe conformational changes in the vicinity of the hemes. However, the presence of two conformations in solution impaired the confident assignment of the polypeptide signals. To understand how conformational changes and swapped dimerization mechanism can effectively modulate the function of the two sensor domains and their signal transduction process, the sensor domains folding and stability were studied by circular dichroism and UV-visible spectroscopy. The results showed differences in the thermodynamic stability of the sensors, with GSU0582 displaying higher structural stability. These studies also demonstrated that the heme moiety undergoes conformational changes matching those occurring at the global protein structure and that the content of intrinsically disordered segments within these proteins (25% for GSU0935; 13% for GSU0582) correlates with the stability differences observed. The thermodynamic and kinetic properties of the sensor domains were determined at different pH and ionic strength by visible spectroscopy and stopped-flow techniques. Despite the remarkably similar spectroscopic and structural features of the two sensor domains, the results showed that their properties are quite distinct. Sensor domain GSU0935 displayed more negative reduction potentials and smaller reduction rate constants, which were more affected by pH and ionic strength. The available structures were used to rationalize these differences. Overall, the results described in this Thesis indicate that the two G. sulfurreducens MCP sensor domains are designed to function in different working potential ranges, allowing this bacterium to trigger an adequate cellular response in distinct anoxic subsurface environments.

Characterization of Endotrypanum Parasites Using Specific Monoclonal Antibodies

A large number of Endotrypanum stocks (representing an heterogeneous population of strains) have been screened against a panel of monoclonal antibodies (MAbs) derived for selected species of Endotrypanum or Leishmania, to see whether this approach could be used to group/differentiate further among these parasites. Using different immunological assay systems, MAbs considered specific for the genus Endotrypanum (E-24, CXXX-3G5-F12) or strain M6159 of E. schaudinni (E-2, CXIV-3C7-F5) reacted variably according to the test used but in the ELISA or immunofluorescence assay both reacted with all the strains tested. Analyses using these MAbs showed antigenic diversity occurring among the Endotrypanum strains, but no qualitative or quantitative reactivity pattern could be consistently related to parasite origin (i.e., host species involved) or geographic area of isolation. Western blot analyses of the parasites showed that these MAbs recognized multiple components. Differences existed either in the epitope density or molecular forms associated with the antigenic determinants and therefore allowed the assignment of the strains to specific antigenic groups. Using immunofluorescence or ELISA assay, clone E-24 produced reaction with L. equatorensis (which is a parasite of sloth and rodent), but not with other trypanosomatids examined. Interestingly, the latter parasite and the Endotrypanum strains cross-reacted with a number of MAbs that were produced against members of the L. major-L. tropica complex

Genetic epidemiology of fecal egg excretion during Schistosoma mansoni infection in an endemic area in Minas Gerais, Brazil

There is considerable variation in the level of fecal egg excretion during Schistosoma mansoni infections. Within a single endemic area, the distribution of egg counts is typically overdispersed, with the majority of eggs excreted coming from a minority of residents. The purpose of this study was to quantify the influence of genetic factors on patterns of fecal egg excretion in a rural study sample in Brazil. Individual fecal egg excretions, expressed in eggs per gram of feces, were determined by the Kato-Katz method on stool samples collected on three different days. Detailed genealogic information was gathered at the time of sampling, which allowed assignment of 461 individuals to 14 pedigrees containing between 3 and 422 individuals. Using a maximum likelihood variance decomposition approach, we performed quantitative genetic analyses to determine if genetic factors could partially account for the observed pattern of fecal egg excretion. The quantitative genetic analysis indicated that between 21-37% of the variation in S. mansoni egg counts was attributable to additive genetic factors and that shared environment, as assessed by common household, accounted for a further 12-21% of the observed variation. A maximum likelihood heritability (h²) estimate of 0.44 ± 0.14 (mean ± SE) was found for the 9,604 second- and higher-degree pairwise relationships in the study sample, which is consistent with the upper limit (37%) of the genetic factor determined in the variance decomposition analysis. These analyses point to the significant influence of additive host genes on the pattern of S. mansoni fecal egg excretion in this endemic area.

Cytotaxonomy of Simulium cauchense Floch & Abonnenc and Simulium quadrifidum Lutz (Diptera: Simuliidae) in Brazilian Amazonia

Simulium cauchense Floch & Abonnenc and Simulium quadrifidum Lutz are widely distributed in the Amazon region and are morphologically similar at the larval and pupal stages. Chromosomally, these species are readily distinguished by the position of the nucleolar organizer, which is in the short arm of chromosome I in S. cauchense and in the long arm of chromosomes III in S. quadrifidum. They also differ by three fixed inversions. Sex chromosomes are undifferentiated in both species. Chromosomal resolution of the two species allowed us to evaluate four structural features previously used as diagnostic aids at the larval stage. Characters that distinguish larvae of the two species are the number of branches and branching patterns of the dorsal abdominal setae and the dark band on each primary fan. Branching patterns of the gill histoblasts were often diagnostic, with S. quadrifidum exhibiting more proximal branching and S. cauchense more distal branching. Sites where both species occurred sometimes had larvae with one petiole branching proximally and the other distally; in these cases examination of the chromosomes permitted assignment of the specimen to species. Pigmentation patterns of larvae, on the other hand, are highly variable. Color typically is sex linked in both species.