1,038 research outputs found
DNA/RNA G-Quadruplexes and SARS-CoV-2: An Innovative Target for Metal Complexes with Salphen Ligands
No full textL'attenzione rivolta a malattie prive di target molecolari noti e l'interesse crescente verso bersagli terapeutici non convenzionali, come le strutture secondarie del DNA alternative alla nota doppia elica destrorsa (B-DNA), sono diventati temi di grande rilievo tra la comunità scientifica. In questo contesto, le strutture G-quadruplex (G4) del DNA/RNA hanno attirato l'interesse per la loro presenza in sequenze regolatorie dei genomi umani e virali, rendendoli target promettenti per lo sviluppo di nuovi farmaci. La stabilizzazione dei G4 potrebbe modulare l'espressione genica e interrompere processi patologici nel genoma umano o nella replicazione di organismi patogeni, aprendo nuove prospettive per il trattamento di malattie attualmente prive di terapie molecolari efficaci. Tuttavia, lo sviluppo clinico e preclinico di terapie mirate ai G4 è ancora limitato dalla difficoltà di identificare molecole in grado di riconoscere selettivamente questo tipo di strutture secondarie. Molti composti noti per interagire con questo target mostrano affinità anche per il DNA a doppia elica, un aspetto che ne limita la specificità. Una molecola dovrebbe idealmente essere in grado di colpire selettivamente specifiche strutture G4 implicate nella progressione della malattia, modulando unicamente i processi biologici in cui tali strutture sono coinvolte. Per affrontare queste sfide, è essenziale comprendere a fondo le relazioni strutturali tra i G4 e i potenziali candidati molecolari.Questo progetto di dottorato rappresenta un approccio innovativo e multidisciplinare per lo sviluppo di nuovi complessi metallici con leganti di basi di Schiff, capaci di stabilizzare selettivamente le strutture G4 umane e virali. L'originalità del progetto risiede nell'integrazione di metodologie distinte ma complementari, che includono chimica sintetica, tecniche spettroscopiche, computazionali e algoritmi avanzati di machine learning.Nella fase sperimentale, condotta presso l'Università di Palermo, l'esplorazione della chimica di coordinazione è stata centrale per la sintesi di nuovi complessi di Ni(II), Pd(II), Zn(II) e Cu(II) con leganti di tipo “Salfen”, noti per la loro forte affinità verso le strutture G4. Tali composti sono stati caratterizzati attraverso Risonanza Magnetica Nucleare (NMR), spettrometria di massa, analisi elementare CHN e cristallografia a raggi X. Successivamente, tecniche biofisiche, come la spettroscopia UV-Vis, il dicroismo circolare (CD), saggi di fluorescenza e di trasferimento di energia per risonanza di Förster (FRET), sono state utilizzate per studiare l'affinità e le interazioni tra questi complessi e i bersagli G4 umani e virali.La fase computazionale, condotta principalmente durante un soggiorno di sei mesi a Parigi presso l'Université Paris Cité, ha coinvolto l’applicazione di homology modeling, mirata in particolare alla predizione delle strutture tridimensionali di sequenze virali di G4 attualmente non caratterizzate sperimentalmente e disponibili quindi nel database Protein Data Bank (PDB). Questo lavoro ha permesso uno studio dettagliato delle sequenze selezionate, attraverso simulazioni di dinamica molecolare (MD) e tecniche ibride di meccanica quantistica/meccanica molecolare (QM/MM). I metodi computazionali utilizzati hanno consentito la determinazione teorica degli spettri di dicroismo circolare dei G4, fornendo una base per confronti diretti con gli spettri CD ottenuti sperimentalmente e, di conseguenza, per la caratterizzazione delle sequenze investigate. L’approccio usato rafforza l'indagine correlando le previsioni teoriche con i dati empirici, migliorando così la comprensione delle strutture G4 e delle loro interazioni con i composti metallici.Infine, in collaborazione con la Fondazione Ri.Med, sono stati implementati approcci avanzati di machine learning per prevedere l'attività di molecole di sintesi verso strutture di tipo G4. Nello specifico, è stato sviluppato un modello di machine learning basato su descrittori molecolari chimici classici e quantistici. L’utilizzo dell'intelligenza artificiale ha lo scopo di fornire un metodo innovativo per esplorare la relazione struttura-attività nella scoperta di potenziali farmaci, con un focus particolare sull'affinità e la selettività di legame con i G4. I risultatati ottenuti, non solo aprono nuove strade per lo sviluppo di terapie mirate basate sul “G-quadruplex targeting”, ma evidenzia anche il ruolo sempre più centrale di tecniche basate sull’intelligenza artificiale nella scienza molecolare.La tesi presentata è organizzata in tre sezioni: I) Introduzione, II) Risultati e III) Conclusioni. Ogni sezione è divisa in capitoli. In particolare, nella sezione “Risultati”, i tre capitoli si allineano con le tre fasi descritte sopra. Il primo capitolo tratta principalmente la sintesi di nuovi complessi metallici con leganti di tipo Salfen e la loro interazione con G4 umani. Il secondo capitolo, invece, si concentra sui G4 virali, utilizzando una combinazione di tecniche sperimentali e teoriche per esplorarne la struttura e le modalità di interazione con i complessi sintetizzati. Infine, il terzo capitolo consolida tutte le informazioni raccolte nelle fasi precedenti, sia dal punto di vista progettuale che temporale, convergendo nel primo modello di machine learning “open source" per predire l’attività di composti organici e inorganici verso strutture G4.The focus on diseases lacking known molecular targets and the growing interest in unconventional therapeutic targets, such as non-canonical DNA/RNA secondary structures, have become increasingly significant within the scientific community. DNA/RNA G-quadruplexes (G4s) have recently garnered attention due to their presence in regulatory sequences within human and viral genomes, making them appealing targets for potential new drugs. Stabilizing G4s could induce the modulation of gene expression and block pathological processes in the human genome or the replication of pathogenic organisms, thereby opening new avenues for treating diseases that currently lack effective molecular therapies. However, the clinical and even preclinical development of G4-targeting therapies remains constrained by the challenge of identifying molecules that can selectively recognize G4 structures. Many known G4 binders also show affinity for double-helical DNA and lack of specificity for G4 sequences. An ideal binding molecule should be able to selectively target specific G4 structures implicated in disease progression, thereby modulating only the biological processes or signaling pathways in which these structures are involved. To address these challenges, a deeper understanding of the intricate structural relationships between G4 structures and potential small-molecule drug candidates is essential. Today, there is a fundamental need for research dedicated to the collection and codification of critical information required for designing biologically active and highly selective molecules.This PhD project aims at proposing an innovative and multifaceted approach to the development of new Schiff base transition metal complexes capable of selectively stabilizing human and viral G4 structures. The project’s originality lies in the integration of distinct yet complementary methodologies, encompassing synthetic chemistry, spectroscopic and biophysical techniques, computational modeling, and cutting-edge machine learning algorithms.In the experimental phase, conducted at the University of Palermo, the exploration of coordination chemistry was central to the synthesis of novel Ni(II), Pd(II), Zn(II), and Cu(II) complexes with Salphen ligands, renowned for their strong affinity toward G4 structures. These compounds have been characterized through nuclear magnetic resonance (NMR), mass spectrometry, CHN elemental analysis, and X-ray crystallography, providing detailed insight into their composition and structure. Subsequently, optical spectroscopic techniques, such as UV-Vis absorption, circular dichroism (CD), fluorescence, and Förster Resonance Energy Transfer (FRET), were employed to elucidate the affinity and the interactions between these complexes and both human and viral DNA and RNA G4 targets.The computational phase, predominantly carried out during a six-month stay in Paris at Université Paris Cité, involved computational modeling, specifically aimed at predicting the three-dimensional structures at atomic resolution of viral G4 sequences that are currently non present in the “Protein Data Bank” (PDB) database. This work enabled a detailed study of the motifs through classic and hybrid quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations. These computational methods allowed for the theoretical determination of CD spectra of G4s in solution, providing a basis for direct comparison with experimentally obtained CD spectra and, consequently, the characterization of the investigated sequences. This approach strengthens the investigation by correlating theoretical predictions with empirical data, thus enhancing the understanding of G4 structures and their interactions with metal- based compounds.Finally, in collaboration with Fondazione Ri.Med, advanced machine learning (ML) approaches were implemented to predict binding activity toward G4 structures. A machine learning model was developed, leveraging classical and quantum chemical (QC) molecular descriptors, to predict the affinity of G4 binders and their stabilization capacity. This integration with artificial intelligence (AI) provides a novel method for exploring structure-function relationships in drug discovery, particularly focusing on G4-binding affinity and selectivity. This breakthrough not only opens new pathways for targeted therapeutic development but also highlights the increasingly pivotal role of AI in molecular science.This thesis is organized into three sections: I) Introduction, II) Results, and III) Conclusions. Every section is divided in chapters. In particular, in the “Results” section, the three chapters align with the three phases described above. The first chapter primarily focuses on the synthesis of novel Salphen complexes and their interaction with human G4s, aiming to elucidate their structural, chemical, and electronic properties. The second chapter shifts the focus to viral G4s, employing a combination of experimental and theoretical techniques to investigate their structure and interaction modes with thesynthesized complexes. Finally, the third chapter consolidates all the information gathered in the previous phases, both in terms of design and timeline, culminating in the development of the first open-source machine learning model capable of predicting the activity of organic and inorganic compounds toward G4 structures
Coloring effects of synthetic inorganic cobalt pigments in fast-fired porcelainized tiles
No full textThis paper reports a laboratory and industrial study on the rationalization of using synthetic cobalt oxide, aluminate, and silicate pigments (0.5-4.0 wt%) for coloring porcelainized stoneware tiles. Adding about 1-2 wt% of pigments to the base body does not appreciably modify the microstructure, nature, and amount of phases of the fired tiles, while higher amounts, by promoting liquid phase formation, favor the sintering and can cause swelling of compact samples
Acute siliconomas of the face triggered by skin rejuvenation mesotherapy with low weight hyaluronic acid: surgical treatment and pathogenetic hypothesis
No full text“Hängendes Tuch” eine neue Modifikation zur Stabilisierung des klassischen mehrzeitigen retroaurikulären Lappens
No full textSynthesis and characterization of trigonal-bipyramidal platinum(II) olefin complexes with chalcogenide ligands in axial positions. X-ray molecular structures of [Pt(SMe)(2)(dmphen)(diphenyl fumarate)], its cationic dipositive derivative [Pt(SMe2)(2)(dmphen)(diphenyl fumarate)][BF4](2), and free diphenyl fumarate
No full textThe oxidative addition of RE-ER molecules (E = O, R = H, C(O)Ph, C(O)Me; E = S, Se, Te, R = Me, Ph) to Pt(0) precursors [Pt(N,N-chelate)(olefin)] (1: N,N-chelate = e.g. 2,9-dimethyl-1,10-phenanthroline; olefin = maleic or fumaric ester) has been studied. Symmetrical cleavage of the E-E bonds affords unprecedented trigonal-bipyramidal Pt(II) complexes of the formula [Pt(ER)2(N,N-chelate)(olefin)] (2). Products of type 2, which have been characterized through H-1 and C-13 NMR spectroscopy, contain chalcogenide ligands in the axial positions. The reactivity of the new compounds has also been investigated. Thus, Pt-OH fragments generated by the addition of H2O2 are acetylated by acetic anhydride. Furthermore, S, Se, and Te coordinated to Pt are readily methylated by trimethyloxonium tetrafluoroborate, affording the first examples of dipositive coordinatively saturated platinum(11) cations (3). The structures of the related neutral [Pt(SMe)(2)(2,9-dimethyl-1,10-phenanthroline)(diphenyl fumarate)] and cationic [Pt( Me2)(2)(2,9-dimethyl-1,10-phenanthroline)(diphenyl fumarate)] [BF4](2) compounds have been determined by X-ray diffraction together with that of the free diphenyl fumarate ligand. RI Monari, Magda/B-2648-200
Targeting G-quadruplexes with organic dyes: Chelerythrine–DNA binding elucidated by combining molecular modeling and optical spectroscopy
No full textThe DNA-binding of the natural benzophenanthridine alkaloid chelerythrine (CHE) has been assessed by combining molecular modeling and optical absorption spectroscopy. Specifically, both double-helical (B-DNA) and G-quadruplex sequences—representative of different topologies and possessing biological relevance, such as telomeric or regulatory sequences—have been considered. An original multiscale protocol, making use of molecular dynamics (MD) simulations and quantum mechanics/molecular mechanics (QM/MM) calculations, allowed us to compare the theoretical and experimental circular dichroism spectra of the different DNA topologies, readily providing atomic-level details of the CHE–DNA binding modes. The binding selectivity towards G-quadruplexes is confirmed by both experimental and theoretical determination of the binding free energies. Overall, our mixed computational and experimental approach is able to shed light on the interaction of small molecules with different DNA conformations. In particular, CHE may be seen as the building block of promising drug candidates specifically targeting G-quadruplexes for both antitumoral and antiviral purposes
Multiple eruptive clear cell acanthoma
No full textBackground: Clear cell acanthoma is a rare solitary benign epidermal tumor of unknown etiology. The disease arises in the middle-age, with no sex predominance. It appears as a single reddish papule or papule-nodule and a peripheral scaling collarette is characteristic. Although solitary lesions are the rule, less than 30 cases of multiple Clear cell acanthoma have been described in the literature to date. Main observations: We report an unusual case of a healthy 74-year-old male with multiple clear cell acanthoma on the lower extremities treated successfully with cryotherapy. Conclusion: Despite significant progress in treatment of clear cell acanthoma, cryotherapy, based on liquid nitrogen, remains an important alternative in treating multiple clear cell acanthomas
Hierarchical Bayesian models for the estimation of correlated multiple effects in multilevel data: a simulation study to assess model performance
No full textIn this paper, we aim at assessing hierarchical Bayesian modeling for the analysis of multiple exposures and highly correlated effects in a multilevel setting. We exploit an artificial data set to apply our method and show the gains in the final estimates of the crucial parameters. As a motivating example to simulate data, we consider a real prospective cohort study designed to investigate the association of dietary exposures with the occurrence of colon-rectum cancer in a multilevel framework, where, e.g., individuals have been enrolled from different countries or cities. We rely on the presence of some additional information suitable to mediate the final effects of the exposures and to be arranged in a level-2 regression to model similarities among the parameters of interest (e.g., data on the nutrient compositions for each dietary item)
Successful treatment of systemic cold contact urticaria with etanercept in a patient with psoriasis
No full textStudio sulle trasformazioni chimico-fisiche indotte da piccole aggiunte di particolari componenti negli smalti
No full textL'articolo riporta risultati di una ricerca eseguita al fine di verificare l'effetto sulle caratteristiche e sulle trasformazioni chimico-fisiche indotte da piccole aggiunte di particolari componenti negli smalt
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