Solution structure of methionine-oxidized amyloid beta-peptide (1-40). Does oxidation affect conformational switching?

The solution structure of A beta(1-40)Met(O), the methionine-oxidized form of amyloid beta-peptide A beta(1-40), has been investigated by CD and NMR spectroscopy. Oxidation of Met35 may have implications in the aetiology of Alzheimer's disease. Circular dichroism experiments showed that whereas A beta(1-40) and A beta(1-40)Met(O) both adopt essentially random coil structures in water (pH 4) at micromolar concentrations, the former aggregates within several days while the latter is stable for at least 7 days under these conditions. This remarkable difference led us to determine the solution structure of A beta(1-40)Met(O) using H-1 NMR spectroscopy. In a water-SDS micelle medium needed to solubilize both peptides at the millimolar concentrations required to measure NMR spectra, chemical shift and NOE data for A beta(1-40)Met(O) strongly suggest the presence of a helical region between residues 16 and 24. This is supported by slow H-D exchange of amide protons in this region and by structure calculations using simulated annealing with the program XPLOR. The remainder of the structure is relatively disordered. Our previously reported NMR data for A beta(1-40) in the same solvent shows that helices are present over residues 15-24 (helix 1) and 28-36 (helix 2), Oxidation of Met35 thus causes a local and selective disruption of helix 2. In addition to this helix-coil rearrangement in aqueous micelles, the CD data show that oxidation inhibits a coil-to-beta-sheet transition in water. These significant structural rearrangements in the C-terminal region of A beta may be important clues to the chemistry and biology of A beta(1-40) and A beta(1-42).

NMR studies of the low-density lipoprotein receptor-binding peptide of apolipoprotein E bound to dodecylphosphocholine micelles

Circular dichroism and NMR spectroscopy have been used to determine the structure of the low-density lipoprotein (LDL) receptor-binding peptide, comprising residues 130-152, of the human apolipoprotein E. This peptide has little persistent three-dimensional structure in solution, but when bound to micelles of dodecylphosphocholine (DPC) it adopts a predominantly alpha-helical structure. The three-dimensional structure of the DPC-bound peptide has been determined by using H-1-NMR spectroscopy: the structure derived from NOE-based distance constraints and restrained molecular dynamics is largely helical. The derived phi and psi angle order parameters show that the helical structure is well defined but with some flexibility that causes the structures not to be superimposable over the full peptide length. Deuterium exchange experiments suggest that many peptide amide groups are readily accessible to the solvent, but those associated with hydrophobic residues exchange more slowly, and this helix is thus likely to be positioned on the surface of the DPC micelles. In this conformation the peptide has one hydrophobic face and two that are rich in basic amino acid side chains. The solvent-exposed face of the peptide contains residues previously shown to be involved in binding to the LDL receptor.

Identification of initiation sites for T4 lysozyme folding using CD and NMR spectroscopy of peptide fragments

Using CD and 2D H-1 NMR spectroscopy, we have identified potential initiation sites for the folding of T4 lysozyme by examining the conformational preferences of peptide fragments corresponding to regions of secondary structure. CD spectropolarimetry showed most peptides were unstructured in water, but adopted partial helical conformations in TFE and SDS solution. This was also consistent with the H-1 NMR data which showed that the peptides were predominantly disordered in water, although in some cases, nascent or small populations of partially folded conformations could be detected. NOE patterns, coupling constants, and deviations from random coil Her chemical shift values complemented the CD data and confirmed that many of the peptides were helical in TFE and SDS micelles. In particular, the peptide corresponding to helix E in the native enzyme formed a well-defined helix in both TFE and SDS, indicating that helix E potentially forms an initiation site for T4 lysozyme folding. The data for the other peptides indicated that helices D, F, G, and H are dependent on tertiary interactions for their folding and/or stability. Overall, the results from this study, and those of our earlier studies, are in agreement with modeling and IID-deuterium exchange experiments, and support an hierarchical model of folding for T4 lysozyme.

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.

Inherently chiral calix[4]arenes with planar chirality: two new entries to the family

The synthesis of two new inherently chiral calix[4]arenes (ICCs, 1 and 2), endowed with electron-rich concave surfaces, has been achieved through the desymmetrization of a lower rim distal-bridged oxacyclophane (OCP) macrocycle. The new highly emissive ICCs were resolved by chiral HPLC, and the enantiomeric nature of the isolated antipodes proved by electronic circular dichroism (CD). Using time-dependent density functional calculations of CD spectra, their absolute configurations were established. NMR studies with (S)-Pirkle's alcohol unequivocally showed that the host-guest interactions occur in the chiral pocket comprehending the calix-OCP exo cavities and the carbazole moieties.

Identification of Ligands for the Tau Exon 10 Splicing Regulatory Element RNA Using Dynamic Combinatorial Chemistry

We describe the use of dynamic combinatorial chemistry (DCC) to identify ligands for the stem-loop structure located at the exon 10-5'-intron junction of Tau pre-mRNA, which is involved in the onset of several tauopathies including frontotemporal dementia with Parkinsonism linked to chromosome 17 (FTDP-17). A series of ligands that combine the small aminoglycoside neamine and heteroaromatic moieties (azaquinolone and two acridines) have been identified by using DCC. These compounds effectively bind the stem-loop RNA target (the concentration required for 50% RNA response (EC(50)): 2-58 μM), as determined by fluorescence titration experiments. Importantly, most of them are able to stabilize both the wild-type and the +3 and +14 mutated sequences associated with the development of FTDP-17 without producing a significant change in the overall structure of the RNA (as analyzed by circular dichroism (CD) spectroscopy), which is a key factor for recognition by the splicing regulatory machinery. A good correlation has been found between the affinity of the ligands for the target and their ability to stabilize the RNA secondary structure.

Polychlorinated trityl radicals for dynamic nuclear polarization: the role of chlorine nuclei

Polychlorinated trityl radicals bearing carboxylate substituents are water soluble persistent radicals that can be used for dynamic nuclear polarization. In contrast to other trityl radicals, the polarization mechanism differs from the classical solid effect. DFT calculations performed to rationalize this behaviour support the hypothesis that polarization is transferred from the unpaired electron to chlorine nuclei and from these to carbon by spin diffusion. The marked differences observed between neutral and anionic forms of the radical will be discussed.

Exploring the effect of aminoglycoside guanidinylation on ligands for Tau exon 10 splicing regulatory element RNA

We describe the effect of guanidinylation of the aminoglycoside moiety on acridine-neamine-containing ligands for the stem-loop structure located at the exon 10-5′-intron junction of Tau pre-mRNA, an important regulatory element of tau gene alternative splicing. On the basis of dynamic combinatorial chemistry experiments, ligands that combine guanidinoneamine and two different acridines were synthesized and their RNA-binding properties were compared with those of their amino precursors. Fluorescence titration experiments and UV-monitored melting curves revealed that guanidinylation has a positive effect both on the binding affinity and specificity of the ligands for the stemloop RNA, as well as on the stabilization of all RNA sequences evaluated, particularly some mutated sequences associated with the development of FTDP-17 tauopathy. However, this correlation between binding affinity and stabilization due to guanidinylation was only found in ligands containing a longer spacer between the acridine and guanidinoneamine moieties, since a shorter spacer produced the opposite effect (e.g. lower binding affinity and lower stabilization). Furthermore, spectroscopic studies suggest that ligand binding does not significantly change the overall RNA structure upon binding (circular dichroism) and that the acridine moiety might intercalate near the bulged region of the stem->loop structure (UV-Vis and NMR spectroscopy).

Self-condensation of n-(N-propyl)butanimine: NMR and mass spectral analyses and investigation by theoretical calculation

The stability of N-propylbutanimine (1) was investigated under different experimental conditions. The acid-catalyzed self-condensation that produced the E-enimine (4) and Z-inimine (5) was studied by experimental analyses and theoretical calculations. Since the calculations for the energy of 5 indicated that it had a lower energy than 4, yet 4 was the principal product, the self-condensation of 1 must be kinetically controlled.

Evaluation of group electronegativities and hardness (softness) of group 14 elements and containing functional groups through density functional theory and correlation with NMR spectra data

Quantum Chemical calculations for group 14 elements of Periodic Table (C, Si, Ge, Sn, Pb) and their functional groups have been carried out using Density Functional Theory (DFT) based reactivity descriptors such as group electronegativities, hardness and softness. DFT calculations were performed for a large series of tetracoordinated Sn compounds of the CH3SnRR'X type, where X is a halogen and R and R' are alkyl, halogenated alkyl, alkoxy, or alkyl thio groups. The results were interpreted in terms of calculated electronegativity and hardness of the SnRR'X groups, applying a methodology previously developed by Geerlings and coworkers (J. Phys. Chem. 1993, 97, 1826). These calculations allowed to see the regularities concerning the influence of the nature of organic groups RR' and inorganic group X on electronegativities and hardness of the SnRR'X groups; in this case, it was found a very good correlation between the electronegativity of the fragment and experimental 119Sn chemical shifts, a property that sensitively reflects the change in the valence electronic structure of molecules. This work was complemented with the study of some compounds of the EX and ER types, where E= C, Si, Ge, Sn and R= CH3, H, which was performed to study the influence that the central atom has on the electronegativity and hardness of molecules, or whether these properties are mainly affected for the type of ligand bound to the central atom. All these calculations were performed using the B3PW91 functional together with the 6-311++G** basis set level for H, C, Si, Ge, F, Cl and Br atoms and the 3-21G for Sn and I atoms.

Influence of the solvent on the self-assembly of a modified amyloid beta peptide fragment. II. NMR and computer simulation investigation

The conformation of a model peptide AAKLVFF based on a fragment of the amyloid beta peptide A beta 16-20, KLVFF, is investigated in methanol and water via solution NMR experiments and Molecular dynamics computer simulations. In previous work, we have shown that AAKLVFF forms peptide nanotubes in methanol and twisted fibrils in water. Chemical shift measurements were used to investigate the solubility of the peptide as a function of concentration in methanol and water. This enabled the determination of critical aggregation concentrations, The Solubility was lower in water. In dilute solution, diffusion coefficients revealed the presence of intermediate aggregates in concentrated solution, coexisting with NMR-silent larger aggregates, presumed to be beta-sheets. In water, diffusion coefficients did not change appreciably with concentration, indicating the presence mainly of monomers, coexisting with larger aggregates in more concentrated solution. Concentration-dependent chemical shift measurements indicated a folded conformation for the monomers/intermediate aggregates in dilute methanol, with unfolding at higher concentration. In water, an antiparallel arrangement of strands was indicated by certain ROESY peak correlations. The temperature-dependent solubility of AAKLVFF in methanol was well described by a van't Hoff analysis, providing a solubilization enthalpy and entropy. This pointed to the importance of solvophobic interactions in the self-assembly process. Molecular dynamics Simulations constrained by NOE values from NMR suggested disordered reverse turn structures for the monomer, with an antiparallel twisted conformation for dimers. To model the beta-sheet structures formed at higher concentration, possible model arrangements of strands into beta-sheets with parallel and antiparallel configurations and different stacking sequences were used as the basis for MD simulations; two particular arrangements of antiparallel beta-sheets were found to be stable, one being linear and twisted and the other twisted in two directions. These structures Were used to simulate Circular dichroism spectra. The roles of aromatic stacking interactions and charge transfer effects were also examined. Simulated spectra were found to be similar to those observed experimentally.(in water or methanol) which show a maximum at 215 or 218 nm due to pi-pi* interactions, when allowance is made for a 15-18 nm red-shift that may be due to light scattering effects.

Oxindole-Schiff base copper(II) complexes interactions with human serum albumin: Spectroscopic, oxidative damage, and computational studies

CD and EPR were used to characterize interactions of oxindole-Schiff base copper(II) complexes with human serum albumin (HSA). These imine ligands form very stable complexes with copper, and can efficiently compete for this metal ion towards the specific N-terminal binding site of the protein, consisting of the amino acid sequence Asp-Ala-His. Relative stability constants for the corresponding complexes were estimated from CD data, using the protein as competitive ligand, with values of log K(CuL) in the range 15.7-18.1, very close to that of [Cu(HSA)] itself, with log K(CuHSA) 16.2. Some of the complexes are also able to interfere in the a-helix structure of the protein, while others seem not to affect it. EPR spectra corroborate those results, indicating at least two different metal species in solution, depending on the imine ligand. Oxidative damage to the protein after incubation with these copper(II) complexes, particularly in the presence of hydrogen peroxide, was monitored by carbonyl groups formation, and was observed to be more severe when conformational features of the protein were modified. Complementary EPR spin-trapping data indicated significant formation of hydroxyl and carbon centered radicals, consistent with an oxidative mechanism. Theoretical calculations at density functional theory (DFT) level were employed to evaluate Cu(II)-L binding energies, L -> Cu(II) donation, and Cu(II) -> L back-donation, by considering the Schiff bases and the N-terminal site of HSA as ligands. These results complement previous studies on cytotoxicity, nuclease and pro-apoptotic properties of this kind of copper(II) complexes, providing additional information about their possibilities of transport and disposition in blood plasma. (C) 2009 Elsevier Inc. All rights reserved.

VCD to determine absolute configuration of natural product molecules: secolignans from Peperomia blanda

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

Silver(I) complexes with symmetrical Schiff bases: Synthesis, structural characterization, DFT studies and antimycobacterial assays

Synthesis, structural and spectroscopic characterizations, molecular modeling and antimycobacterial assays of new silver(I) complexes with two Schiff bases - MBDA and MBDB - are reported. The complexes [Ag(MBDA) 2]NO3, or AgMBDA, and [Ag(MBDB)NO3] or AgMBDB, were obtained by the reaction of the respective ligands with silver(I) nitrate in methanol. The Schiff bases were previously obtained by mixing ethylenediamine or 1,3-diaminopropane with p-anisaldehyde. The characterizations of the complexes were based on elemental (C, H and N) and thermal (TG-DTA) analyses and 13C and 1H NMR and FT-IR spectroscopic measurements, as well as X-ray structure determination for AgMBDA. Spectroscopic data predicted by DFT calculations are in agreement with the experimental data for the AgMBDA complex. The AgMBDA complex has a monomeric structure with a molar proportion 1:2 Ag/ligand, while AgMBDB presents a 1:1 proportion. The complexes AgMBDA and AgMBDB showed to be more effective against Mycobacterium tuberculosis than antibacterial agent silver sulfadiazine - SSD. © 2013 Elsevier Ltd. All rights reserved.

Biotransformação e sequestro de micromoléculas de Aristolochia giberti por Battus polydamas

Pós-graduação em Química - IQ