Catalysis Within the Self-Assembled Resorcin[4]arene Hexamer

Supramolecular catalysis is now enriched by a new principal actor: the resorcin[ 4]arene hexamer as an example of a very large, substrate-selective nanohost able to greatly stabilize reactions involving electron-poor and cationic intermediates. This simple and pseudospherical aggregate that spontaneously forms in organic solvents from a vase-shape molecule obtained in a single synthetic step, has been exploited as a well-defined nanoreactor for a wide range of chemical transformations. All the features observed are consequences of the encapsulation of the substrates or of specific cationic catalysts. These species experience unique solvation effects imparted by the electron-rich aromatic surfaces of the assembly. Thanks to its very large cavity, this assembly has attracted the interest of several research groups looking to use it as a simple but efficient example of artificial nanoenzyme

Gangs, displaced, and group-based aggression

Many urban areas experienced an alarming growth of gang activity and violence during the end of the 20th and the beginning of the 21st centuries. Gang members, motivated by various factors, commit a variety of different types of violent acts towards rivals and other targets. Our focus involves instances of displaced aggression, which generally refers to situations in which aggression is targeted towards individuals who have either not themselves committed an offense against the aggressor (s), or who provide an offense that is too mild to justify the aggression levels that are expressed towards them. We discuss how social–psychological mechanisms and models of two types of displaced aggression might help explain some aspects of the retaliatory behavior that is expressed by members of street gangs. We also propose general techniques that have the potential to reduce such aggressive behavior

A resorcin[4]arene hexameric capsule as a supramolecular catalyst in elimination and isomerization reactions

The hexameric resorcin[4]arene capsule as a self-assembled organocatalyst promotes a series of reactions like the carbonyl–ene cyclization of (S)-citronellal preferentially to isopulegol, the water elimination from 1,1-diphenylethanol, the isomerization of α-pinene and β-pinene preferentially to limonene and minor amounts of camphene. The role of the supramolecular catalyst consists in promoting the protonation of the substrates leading to the formation of cationic intermediates that are stabilized within the cavity with consequent peculiar features in terms of acceleration and product selectivity. In all cases the catalytic activity displayed by the hexameric capsule is remarkable if compared to many other strong Brønsted or Lewis acid

Nanoreattori Supramolecolari in Catalisi Omogenea

Semplici sistemi auto-assemblanti, quali i tensioattivi in acqua e capsule esameriche di resorcinarene in solventi organici, permettono di ottenere efficaci sistemi nanometrici impiegabili come nanoreattori in grado di ospitare sistemi catalitici omogenei con positive ripercussioni sulle relative reazioni catalitiche. L’effetto di solvatazione offerto da queste nanostrutture nei confronti di catalizzatori omogenei consente di migliorare notevolmente la resa delle reazioni, la selettività di prodotto e di substrato e la riciclabilità dei sistemi catalitici, oltre a rappresentare semplici ma efficaci sistemi mimetici degli enzim

β-Cyclodextrin Supramolecular Recognition of bis-Cationic Dithienylethenes

The supramolecular interactions in water between b-cyclodextrin and the open and closed photochromic forms of two bis-cationic dithienylethenes, characterized by different electronic properties, were investigated aiming at underlying the key aspects of the recognition process. The dithienylethene equipped with the cyclopentenyl unit showed a difference in binding free energies to the b-cyclodextrin between the open and closed photochromic forms of about 1 kJ/mol. Conversely, the dithienylethene equipped with the perfluorinated cyclopentenyl unit not only was a better guest but showed a three times higher difference in the binding of free energies between the open and closed isomers

Functional bisphosphonate synthesis for the development of new anti-resorption bone drug candidates

Herein we present the synthesis of b-mono and b-bis-substituted vinylidenebisphosphonate esters bearing a carboxylic ester moiety to be used as building blocks for further functionalizations. Reactions of these new bisphosphonate scaffolds through hydrogenation of the unsaturated CQC bond and through metal mediated addition of aryl boronic acids and indoles provide a wide range of new bisphosphonate products as potential leads to contrast osteoporosis

Organocatalytic Enantioselective Epoxidation of Some Aryl-Substituted Vinylidenebisphosphonate Esters: On the Way to Chiral Anti-Osteoporosis Drugs

The synthesis of a new class of epoxide derivatives from prochiral vinylidene bisphosphonate (VBP) precursors is reported using hydrogen peroxide as the terminal oxidant. The reaction is carried out using a series of possible organic catalysts having a basic character, the best results being observed using quinine and sparteine. These catalysts not only provide from good to excellent epoxide yields with a large variety of VBPs but also interesting enantioselectivities in the 67-96% ee range at least in the case of the Ph and m-MeO-Ph VBP derivatives opening the way to a number of chiral anti-osteoporosis potentially active pharmaceutical ingredient

Automatic classification of signal regions in 1H Nuclear Magnetic Resonance spectra

The identification and characterization of signal regions in Nuclear Magnetic Resonance (NMR) spectra is a challenging but crucial phase in the analysis and determination of complex chemical compounds. Here, we present a novel supervised deep learning approach to perform automatic detection and classification of multiplets in 1H NMR spectra. Our deep neural network was trained on a large number of synthetic spectra, with complete control over the features represented in the samples. We show that our model can detect signal regions effectively and minimize classification errors between different types of resonance patterns. We demonstrate that the network generalizes remarkably well on real experimental 1H NMR spectra