Chemoinformatics approaches for new drugs discovery

Chemoinformatics uses computational methods and technologies to solve chemical problems. It works on molecular structures, their representations, properties and related data. The first and most important phase in this field is the translation of interconnected atomic systems into in-silico models, ensuring complete and correct chemical information transfer. In the last 20 years the chemical databases evolved from the state of molecular repositories to research tools for new drugs identification, while the modern high-throughput technologies allow for continuous chemical libraries size increase as highlighted by publicly available repository like PubChem [http://pubchem.ncbi.nlm.nih.gov/], ZINC [http://zinc.docking.org/], ChemSpider[http://www.chemspider. com/]. Chemical libraries fundamental requirements are molecular uniqueness, absence of ambiguity, chemical correctness (related to atoms, bonds, chemical orthography), standardized storage and registration formats. The aim of this work is the development of chemoinformatics tools and data for drug discovery process. The first part of the research project was focused on accessible commercial chemical space analysis; looking for molecular redundancy and in-silico models correctness in order to identify a unique and univocal molecular descriptor for chemical libraries indexing. This allows for the 0%-redundancy achievement on a 42 millions compounds library. The protocol was implemented as MMsDusty, a web based tool for molecular databases cleaning. The major protocol developed is MMsINC, a chemoinformatics platform based on a starting number of 4 millions non-redundant high-quality annotated and biomedically relevant chemical structures; the library is now being expanded up to 460 millions compounds. MMsINC is able to perform various types of queries, like substructure or similarity search and descriptors filtering. MMsINC is interfaced with PDB(Protein Data Bank)[http://www.rcsb.org/pdb/home/home.do] and related to approved drugs. The second developed protocol is called pepMMsMIMIC, a peptidomimetic screening tool based on multiconformational chemical libraries; the screening process uses pharmacophoric fingerprints similarity to identify small molecules able to geometrically and chemically mimic endogenous peptides or proteins. The last part of this project lead to the implementation of an optimized and exhaustive conformational space analysis protocol for small molecules libraries; this is crucial for high quality 3D molecular models prediction as requested in chemoinformatics applications. The torsional exploration was optimized in the range of most frequent dihedral angles seen in X-ray solved small molecules structures of CSD(Cambridge Structural Database); by appling this on a 89 millions structures library was generated a library of 2.6 x 10 exp 7 high quality conformers. Tools, protocols and platforms developed in this work allow for chemoinformatics analysis and screening on large size chemical libraries achieving high quality, correct and unique chemical data and in-silico model

Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study

In this work, we present an extensive study on the use of pre-trained language models for the task of automatic Counter Narrative (CN) generation to fight online hate speech in English. We first present a comparative study to determine whether there is a particular Language Model (or class of LMs) and a particular decoding mechanism that are the most appropriate to generate CNs. Findings show that autoregressive models combined with stochastic decodings are the most promising. We then investigate how an LM performs in generating a CN with regard to an unseen target of hate. We find out that a key element for successful `out of target' experiments is not an overall similarity with the training data but the presence of a specific subset of training data, i.e. a target that shares some commonalities with the test target that can be defined a-priori. We finally introduce the idea of a pipeline based on the addition of an automatic post-editing step to refine generated CNs.Comment: To appear in "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL): Findings

MMsINC: a large-scale chemoinformatics database

MMsINC (http://mms.dsfarm.unipd.it/MMsINC/search) is a database of non-redundant, richly annotated and biomedically relevant chemical structures. A primary goal of MMsINC is to guarantee the highest quality and the uniqueness of each entry. MMsINC then adds value to these entries by including the analysis of crucial chemical properties, such as ionization and tautomerization processes, and the in silico prediction of 24 important molecular properties in the biochemical profile of each structure. MMsINC is consequently a natural input for different chemoinformatics and virtual screening applications. In addition, MMsINC supports various types of queries, including substructure queries and the novel ‘molecular scissoring’ query. MMsINC is interfaced with other primary data collectors, such as PubChem, Protein Data Bank (PDB), the Food and Drug Administration database of approved drugs and ZINC

Attività di testing rapido HIV al Pride di Torino per determinare politiche strategiche e organizzative tra gli MSM

L’offerta del test HIV presso un evento sociale frequentato prevalentemente da giovani uomini che fanno sesso con uomini (MSM) fornisce una possibilità unica di intervenire nel processo di diagnosi precoce dell’HIV. Il progetto Torino Fast Track City permette di osservare elementi organizzativi utili per l’organizzazione dei test rapidi sul territorio, al tempo stesso l’adesione a COBATEST Network fornisce la possibilità di osservare un campione determinando le variabili utili per la costruzione di strategie di intervento e campagne di prevenzione. La somministrazione dei test rapidi HIV da parte delle associazioni è uno strumento chiave per incrementare il numero di soggetti che si sottopongono al test, accedono alle cure precocemente e vengono informati sulle terapie e sui possibili comportamenti a rischio

Black hole spin: theory and observation

In the standard paradigm, astrophysical black holes can be described solely by their mass and angular momentum - commonly referred to as `spin' - resulting from the process of their birth and subsequent growth via accretion. Whilst the mass has a standard Newtonian interpretation, the spin does not, with the effect of non-zero spin leaving an indelible imprint on the space-time closest to the black hole. As a consequence of relativistic frame-dragging, particle orbits are affected both in terms of stability and precession, which impacts on the emission characteristics of accreting black holes both stellar mass in black hole binaries (BHBs) and supermassive in active galactic nuclei (AGN). Over the last 30 years, techniques have been developed that take into account these changes to estimate the spin which can then be used to understand the birth and growth of black holes and potentially the powering of powerful jets. In this chapter we provide a broad overview of both the theoretical effects of spin, the means by which it can be estimated and the results of ongoing campaigns.Comment: 55 pages, 5 figures. Published in: "Astrophysics of Black Holes - From fundamental aspects to latest developments", Ed. Cosimo Bambi, Springer: Astrophysics and Space Science Library. Additional corrections mad

Chemoinformatics approaches for new drugs discovery

Chemoinformatics uses computational methods and technologies to solve chemical problems. It works on molecular structures, their representations, properties and related data. The first and most important phase in this field is the translation of interconnected atomic systems into in-silico models, ensuring complete and correct chemical information transfer. In the last 20 years the chemical databases evolved from the state of molecular repositories to research tools for new drugs identification, while the modern high-throughput technologies allow for continuous chemical libraries size increase as highlighted by publicly available repository like PubChem [http://pubchem.ncbi.nlm.nih.gov/], ZINC [http://zinc.docking.org/], ChemSpider[http://www.chemspider. com/]. Chemical libraries fundamental requirements are molecular uniqueness, absence of ambiguity, chemical correctness (related to atoms, bonds, chemical orthography), standardized storage and registration formats. The aim of this work is the development of chemoinformatics tools and data for drug discovery process. The first part of the research project was focused on accessible commercial chemical space analysis; looking for molecular redundancy and in-silico models correctness in order to identify a unique and univocal molecular descriptor for chemical libraries indexing. This allows for the 0%-redundancy achievement on a 42 millions compounds library. The protocol was implemented as MMsDusty, a web based tool for molecular databases cleaning. The major protocol developed is MMsINC, a chemoinformatics platform based on a starting number of 4 millions non-redundant high-quality annotated and biomedically relevant chemical structures; the library is now being expanded up to 460 millions compounds. MMsINC is able to perform various types of queries, like substructure or similarity search and descriptors filtering. MMsINC is interfaced with PDB(Protein Data Bank)[http://www.rcsb.org/pdb/home/home.do] and related to approved drugs. The second developed protocol is called pepMMsMIMIC, a peptidomimetic screening tool based on multiconformational chemical libraries; the screening process uses pharmacophoric fingerprints similarity to identify small molecules able to geometrically and chemically mimic endogenous peptides or proteins. The last part of this project lead to the implementation of an optimized and exhaustive conformational space analysis protocol for small molecules libraries; this is crucial for high quality 3D molecular models prediction as requested in chemoinformatics applications. The torsional exploration was optimized in the range of most frequent dihedral angles seen in X-ray solved small molecules structures of CSD(Cambridge Structural Database); by appling this on a 89 millions structures library was generated a library of 2.6 x 10 exp 7 high quality conformers. Tools, protocols and platforms developed in this work allow for chemoinformatics analysis and screening on large size chemical libraries achieving high quality, correct and unique chemical data and in-silico modelsIl termine chemoinformatica si riferisce all’uso di metodi informatici per risolvere problemi chimici ed ha come oggetto strutture molecolari e loro rappresentazioni, proprietà e dati collegati; passaggio cruciale è la traduzione di sistemi atomici interconnessi in rappresentazioni e modelli in silico, garantendo il completo e corretto trasferimento dell’ informazione chimica. Negli ultimi 20 anni i database chimici sono evoluti da semplici archivi molecolari a strumenti di ricerca per l’ identificazione di nuovi candidati farmaci, grazie allo sviluppo di tecnologie di high-throughput che permettono una continua e costante espansione delle librerie chimiche come testimoniato da database pubblici quali PubChem[http://pubchem.ncbi.nlm.nih.gov/], ZINC[http://zinc.docking.org/], ChemSpider[http://www.chemspider.com/]. Requisiti fondamentali per qualsiasi libreria chimica sono l’ unicità e disambiguità molecolare, la correttezza chimica (relativa ad atomi, legami, ortografia chimica), la standardizzazione dei formati di archiviazione e registrazione molecolare. Lo scopo di questo lavoro è lo sviluppo di strumenti e masse dati chemoinformatici applicabili al processo di identificazione di nuovi farmaci. La prima fase del progetto si è focalizzata sull’ analisi dello spazio chimico commerciale in termini di ridondanza molecolare e correttezza dei modelli in-silico, allo scopo di identificare un descrittore molecolare univoco e non ambiguo utilizzabile nella indicizzazione di librerie molecolari; questo ha permesso di unicare una libreria di 42 milioni di composti commercialmente disponibili e di implementare MMsDusty, un’ applicativo web per l’ unicazione di librerie chemoinformatiche. Uno dei prodotti principali del progetto è MMsINC, una piattaforma chemoinformatica basata su una libreria iniziale di 4 milioni di modelli molecolari di elevata qualità e priva di ridondanza, espansa poi a circa 460 milioni di strutture. La piattaforma permette di effettuare analisi chemoinformatiche tramite funzioni appositamente sviluppate (ricerca per similarità, sottostruttura, descrittori molecolari) oltre ad essere interfacciata col PDB(Protein Data Bank)[http://www.rcsb.org/pdb/home/home.do] e correlata ai farmaci attualmente in commercio. La seconda piattaforma sviluppata è pepMMsMIMIC, un protocollo di analisi ed identificazione di peptidomimetici basato su screening di librerie chimiche multiconformero tramite FP(fingerprints) farmacoforici, allo scopo di identificare piccole molecole organiche in grado di mimare geometricamente e chimicamente peptidi o proteine endogeni. Infine è stato sviluppato un protocollo di analisi conformazionale esaustiva di librerie chimiche, fondamentale per la predizione di modelli molecolari tridimensionali di alta qualità, richiesti nelle applicazioni chemoinformatiche; ottimizzando l’ esplorazione torsionale all’ interno degli intervalli degli angoli diedri più frequenti rilevati nelle strutture organiche risolte ai raggi X del CSD (Cambridge Structural Database) su 89 milioni di grafi molecolari, sono stati generati 2.6 x 10 exp 7 conformeri di alta qualità. Nel complesso la piattaforma ed i protocolli sviluppati permettono di effettuare analisi chemoinformatiche su librerie molecolari di grosse dimensioni, garantendo elevata qualità, correttezza ed unicità del dato chimico e della sua rappresentazione in silico tramite modelli tridimensional

MACHINE LEARNING METHODS FOR PREDICTION OF ULTRA HIGH-FREQUENCY FINANCIAL DATA

Applicazione metodi di machine learning per prevedere la dinamica del prezzo intra-giornaliera in un mercato finanziario strutturato come una doppia asta continua (limit order book). Analisi empirica di dati del mercato americano Nasdaq

L’approccio endoscopico alla calcolosi della via biliare: acquisizione e sviluppo dell’esperienza in una Unità Operativa di Chirurgia Generale. Due periodi a confronto

Lo sviluppo della chirurgia laparoscopica ha fatto sorgere la necessità, presso molti Centri, di controllare e trattare endoscopica - mente l’eventuale litiasi della via biliare associata alla calcolosi della colecisti. La diffusione di tale metodica è sempre stata ostacolata da una sua discreta complessità organizzativa e tecnica e soprattutto dal rischio di complicanze; per tali motivi la tendenza (confortata da autorevoli pareri) è sempre stata quella di concentrare l’esecuzione di ERCP in Centri che ne praticassero molte e con grande frequenza. I risultati di questo studio, con il confronto tra il primo e l’ulti - mo anno completo di attività, indicano che si può acquisire la capa - cità necessaria a soddisfare le esigenze dell’Unità Operativa Chirurgica partendo dal volume di attività offerto dalla propria casi - stica attendendosi buoni risultati con bassa incidenza di complicanze