Kinetic and equilibrium studies on the polyazamacrocycle neotetren: metal-complex formation and DNA interaction

The macrocyclic polyamine 2,5,8,11,14-pentaaza[15]-[15](2,9)[1,10]phenanthrolinophane (neotetren) is studied in its ability to coordinate Cu(ii) even at very low pH values and to interact, as a metal complex, with DNA. The kinetics and equilibria for 1 : 1 and 2 : 1 metal-ligand complexes formation are studied by the stopped-flow method and UV spectrophotometry. Differently protonated complexes are formed, with rate constants much lower than that of water exchange at copper(II) and other Cu(II)/amine systems, this behaviour being ascribed to ring effects and intra-molecular hydrogen bonds. Concerning the DNA/copper(II)-neotetren complexes interaction, analysis of data suggests an intercalative mode of binding. The kinetic results for both DNA/CuL and DNA/Cu(2)L systems agree with the sequence D + S <-->D,S <-->DS where the metal complexes (D) react with the DNA sites (S) leading to fast formation of an externally bound form (D,S) which is converted into an intercalated complex (DS). A very slow process is also detected and ascribed to a conformational change in the polynucleotide secondary structure where the metal centre plays a crucial role. Chromatographic experiments demonstrate that both the investigated Cu(II)/L complexes are able to cleave DNA, but only in the presence of hydrogen peroxide.     

Predicting physical-chemical properties of compounds from molecular structures by recursive neural networks

In this paper, we report on the potential of a recently developed neural network for structures applied to the prediction of physical chemical properties of compounds. The proposed recursive neural network (RecNN) model is able to directly take as input a structured representation of the molecule and to model a direct and adaptive relationship between the molecular structure and target property. Therefore, it combines in a learning system the flexibility and general advantages of a neural network model with the representational power of a structured domain. As a result, a completely new approach to quantitative structure-activity relationship/quantitative structure-property relationship (QSPR/QSAR) analysis is obtained. An original representation of the molecular structures has been developed accounting for both the occurrence of specific atoms/groups and the topological relationships among them. Gibbs free energy of solvation in water, Delta(solv)G degrees , has been chosen as a benchmark for the model. The different approaches proposed in the literature for the prediction of this property have been reconsidered from a general perspective. The advantages of RecNN as a suitable tool for the automatization of fundamental parts of the QSPR/QSAR analysis have been highlighted. The RecNN model has been applied to the analysis of the Delta(solv)G degrees in water of 138 monofunctional acyclic organic compounds and tested on an external data set of 33 compounds. As a result of the statistical analysis, we obtained, for the predictive accuracy estimated on the test set, correlation coefficient R = 0.9985, standard deviation S = 0.68 kJ mol(-1), and mean absolute error MAE = 0.46 kJ mol(-1). The inherent ability of RecNN to abstract chemical knowledge through the adaptive learning process has been investigated by principal components analysis of the internal representations computed by the network. It has been found that the model recognizes the chemical compounds on the basis of a nontrivial combination of their chemical structure and target property.     

Isoperimetric inequalities for an ergodic stochastic control problem

In this paper we deal with blow-up solutions to an elliptic equation with a nonlinear gradient term. The problem under consideration can be seen as the ergodic limit of a stochastic control problem with state constraints. It is well known that it has a solution only when a parameter which appears in the equation assumes a particular value known as ergodic constant. For such a constant many properties similar to those of an eigenvalue hold true. We show that a Faber–Krahn inequality can be stated for the ergodic constant and that for the corresponding solution a comparison result in terms of the solution to a symmetrized problem can be proved.     

Unprecedented Diastereoselective Arylogous Michael Addition of Unactivated Phthalides

The first highly enantioselective arylogous Michael reaction (AMR) of 3-unsubstituted phthalides has been described. This phase-transfer methodology, which uses catalytic amounts of KOH/18-crown-6 catalyst in mesitylene in the presence of N,O-bis(trimethylsilyl)acetamide (BSA), gives access to a broad range of 3-monosubstituted phthalides with high levels of syn diastereoselectivity and good yields, starting from 3-unsubstituted derivatives and diverse α,β-unsaturated carbonyl compounds. The reaction also applies to unactivated 3-alkyl phthalides to afford 3,3-dialkyl derivatives. A plausible mechanism has been suggested. DFT analysis of possible transition states gives a rationale of the high syn diastereoselectivity observed and its correlation with the solvent's dielectric constant.     

Structural studies on Ba(II) adducts of the cytosine nucleobase and its derivative 1-Methylcytosine*

Abstract

The use of the cytosine nucleobase or its 1-Methylcytosine derivative as ligands toward barium(II) cations led to the formation of three compounds, {[Ba(1-Mecyt)(H₂O)X₂]}_n [X=Cl (1), Br (2)], and {[Ba(cyt)₂(H₂O)(ClO₄)₂]}_n (3). Depending on the ligand and the counterion employed, 1–3 exhibit different architectures, which serve as a playground to study how the methyl substitution, together with the nature of the counterion are both significant in the self-assembling process of such species. The effect of the nature and size of the alkaline-earth metal ion on the final structural motif is also evident when comparing these structures with parent complexes of the Ca(II) ion.     

Kinetic investigation of porphyrin interaction with chiral templates reveals unexpected features of the induction and self-propagation mechanism of chiral memory

Kinetics of the porphyrin aggregation leading to a chiral memory system shows a remarkable "catalytic" effect of the noncovalent templates explaining their self-replication ability.     

Industrial Applications of Gold Catalysis

Gold catalysis has recently found its first large‐scale applications in the chemical industry. This Minireview provides a critical analysis of the success factors and of the main obstacles that had to be overcome on the long way from the discovery to the commercialization of gold catalysts. The insights should be useful to researchers in both academia and industry working on the development of tomorrow's gold catalysts to tackle significant environmental and economic issues.     

From glycerol to value-added products

Today, industrial plants that produce glycerol are closing down and others are opening that use glycerol as a raw material, owing to the large surplus of glycerol formed as a by-product during the production of biodiesel. Research efforts to find new applications of glycerol as a low-cost feedstock for functional derivatives have led to the introduction of a number of selective processes for converting glycerol into commercially valued products. This Minireview describes a selection of such achievements and shows how glycerol will be a central raw material in future chemical industries.