Machine learning applications to essential oils and natural extracts

Machine Learning (ML) is a branch of Artificial Intelligence (AI) that allow computers to learn without being explicitly programmed. Various are the applications of ML in pharmaceutical sciences, especially for the prediction of chemical bioactivity and physical properties, becoming an integral component of the drug discovery process. ML is characterized by three learning paradigms that differ in the type of task or problem that an algorithm is intended to solve: supervised, unsupervised, and reinforcement learning. In chapter 2, supervised learning methods were applied to extracts of Lycium barbarum L. fruits for the development of a QSPR model to predict zeaxanthin and carotenoids content based on routinely colorimetric analyses performed on homogenized samples, developing a useful tool that could be used in the food industry. In chapters 3 and 4, ML was applied to the chemical composition of essential oils and correlated to the experimentally determined associated biofilm modulation influence that was either positive or negative. In these two studies, it was demonstrated that biofilm growth is influenced by the presence of essential oils extracted from different plants harvested in different seasons. ML classification techniques were used to develop a Quantitative Activity-Composition Relationship (QCAR) to discover the chemical components mainly responsible for the anti-biofilm activity. The derived models demonstrated that machine learning is a valuable tool to investigate complex chemical mixtures, enabling scientists to understand each component's contribution to the activity. Therefore, these classification models can describe and predict the activity of chemical mixtures and guide the composition of artificial essential oils with desired biological activity. In chapter 5, unsupervised learning models were developed and applied to clinical strains of bacteria that cause cystic fibrosis. The most severe infections reoccurring in cystic fibrosis are due to S. aureus and P. aeruginosa. Intensive use of antimicrobial drugs to fight lung infections leads to the development of antibiotic-resistant bacterial strains. New antimicrobial compounds should be identified to overcome antibiotic resistance in patients. Sixty-one essential oils were studied against a panel of 40 clinical strains of S. aureus and P. aeruginosa isolated from cystic fibrosis patients, and unsupervised machine learning algorithms were applied to pick-up a small number of representative strains (clusters of strains) among the panel of 40. Thus, rapidly identifying three essential oils that strongly inhibit antibiotic-resistant bacterial growth

Antimicrobial and antibiofilm activity and machine learning classification analysis of essential oils from different mediterranean plants against pseudomonas aeruginosa

Pseudomonas aeruginosa is a ubiquitous organism and opportunistic pathogen that can cause persistent infections due to its peculiar antibiotic resistance mechanisms and to its ability to adhere and form biofilm. The interest in the development of new approaches for the prevention and treatment of biofilm formation has recently increased. The aim of this study was to seek new non-biocidal agents able to inhibit biofilm formation, in order to counteract virulence rather than bacterial growth and avoid the selection of escape mutants. Herein, different essential oils extracted from Mediterranean plants were analyzed for their activity againstP. aeruginosa. Results show that they were able to destabilize biofilm at very low concentration without impairing bacterial viability. Since the action is not related to a bacteriostatic/bactericidal activity onP. aeruginosa, the biofilm change of growth in presence of the essential oils was possibly due to a modulation of the phenotype. To this aim, application of machine learning algorithms led to the development of quantitative activity-composition relationships classification models that allowed to direct point out those essential oil chemical components more involved in the inhibition of biofilm production. The action of selected essential oils on sessile phenotype make them particularly interesting for possible applications such as prevention of bacterial contamination in the community and in healthcare environments in order to prevent human infections. We assayed 89 samples of different essential oils asP. aeruginosaanti-biofilm. Many samples inhibitedP. aeruginosabiofilm at concentrations as low as 48.8 µg/mL. Classification of the models was developed through machine learning algorithms

Essential oils against bacterial isolates from cystic fibrosis patients by means of antimicrobial and unsupervised machine learning approaches

Recurrent and chronic respiratory tract infections in cystic fibrosis (CF) patients result in progressive lung damage and represent the primary cause of morbidity and mortality. Staphylococcus aureus (S. aureus) is one of the earliest bacteria in CF infants and children. Starting from early adolescence, patients become chronically infected with Gram-negative non-fermenting bacteria, and Pseudomonas aeruginosa (P. aeruginosa) is the most relevant and recurring. Intensive use of antimicrobial drugs to fight lung infections inevitably leads to the onset of antibiotic resistant bacterial strains. New antimicrobial compounds should be identified to overcome antibiotic resistance in these patients. Recently interesting data were reported in literature on the use of natural derived compounds that inhibited in vitro S. aureus and P. aeruginosa bacterial growth. Essential oils, among these, seemed to be the most promising. In this work is reported an extensive study on 61 essential oils (EOs) against a panel of 40 clinical strains isolated from CF patients. To reduce the in vitro procedure and render the investigation as convergent as possible, machine learning clusterization algorithms were firstly applied to pick-up a fewer number of representative strains among the panel of 40. This approach allowed us to easily identify three EOs able to strongly inhibit bacterial growth of all bacterial strains. Interestingly, the EOs antibacterial activity is completely unrelated to the antibiotic resistance profile of each strain. Taking into account the results obtained, a clinical use of EOs could be suggested

Shmt2: a stat3 signaling new player in prostate cancer energy metabolism

Prostate cancer (PCa) is a multifactorial disease characterized by the aberrant activity of different regulatory pathways. STAT3 protein mediates some of these pathways and its activation is implicated in the modulation of several metabolic enzymes. A bioinformatic analysis indicated a STAT3 binding site in the upstream region of SHMT2 gene. We demonstrated that in LNCaP, PCa cells' SHMT2 expression is upregulated by the JAK2/STAT3 canonical pathway upon IL-6 stimulation. Activation of SHTM2 leads to a decrease in serine levels, pushing PKM2 towards the nuclear compartment where it can activate STAT3 in a non-canonical fashion that in turn promotes a transient shift toward anaerobic metabolism. These results were also confirmed on FFPE prostate tissue sections at different Gleason scores. STAT3/SHMT2/PKM2 loop in LNCaP cells can modulate a metabolic shift in response to inflammation at early stages of cancer progression, whereas a non-canonical STAT3 activation involving the STAT3/HIF-1α/PKM2 loop is responsible for the maintenance of Warburg effect distinctive of more aggressive PCa cells. Chronic inflammation might thus prime the transition of PCa cells towards more advanced stages, and SHMT2 could represent a missing factor to further understand the molecular mechanisms responsible for the transition of prostate cancer towards a more aggressive phenotyp

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1. PRODUZIONE E COMMERCIALIZZAZIONE DI: QUADERNI ELETTRONICI PER LABORATORI SCIENTIFICI CON CAPACITA' DI ELABORAZIONI DEDICATE E TAILORING ALGORITHMS CON OPPORTUNE INTERFACCE CON UN MAIN FRAME DEDICATO ALL'ANALISI CHEMIOMETRICA E BIOINFORMATICA; PIATTAFORME DEDICATE AL SETTORE CHIMICA-FARMACEUTICO E AGRI-FOOD (INTEGRATORI ALIMENTARI, NUTRACEUTICA, COSMECEUTICA, ECC.); SOFTWARE PER CHIMICA FARMACEUTICA PER DRUG DESIGN (PROGETTAZIONE FARMACI E COMPOSTI BIOATTIVI) E PROCESSI DI SINTESI DI MOLECOLE ORGANICHE; L'OTTIMIZZAZIONE DEI PARAMETRI DI PROCESSO PER L'ESTRAZIONE DI PRINCIPI ATTIVI DA MATERIALE DI ORIGINE NATURALE; PREVISIONE DI MANOVRE CORRETTIVE PER LA STABILIZZAZIONE ORGANOLETTICA DEI PRODOTTI AGRO-ALIMENTARI E LO STUDIO FINALIZZATO ALLA VERIFICA DI STABILITA' DI PRODOTTI CHIMICI INCLUSI IN PREPARAZIONI FARMACEUTICHE E SIMILARI. 2. SVILUPPO, PRODUZIONE, PROGETTAZIONE, GESTIONE E COMMERCIALIZZAZIONE DI PRODOTTI E/O SERVIZI INNOVATIVI AD ALTO VALORE TECNOLOGICO NEL SETTORE INFORMATICO (SOFTWARE ED HARDWARE DI OGNI GENERE INCLUSE RETI CABLATE E WIRELESS) E TELEMATICO, INCLUSO WEB ED APP PER DISPOSITIVI MOBILI. 3. CONTROLLO, SPERIMENTAZIONE, PROVA, MISURA E MONITORAGGIO NEI SETTORI PRODUTTIVI DI INTERESSE (FARMACEUTICO, NUTRACEUTICO, AGROALIMENTAREE SCIENTIFICO IN GENERE) SIA SUL CAMPO CHE IN LABORATORIO; NONCHE' CERTIFICAZIONE PER MATERIALI E PRODOTTI, ATTREZZATURE E MACCHINARI SU AUTORIZZAZIONE MINISTERIALE. 4. ELABORAZIONE ED ATTUAZIONE DI RICERCA E SPERIMENTAZIONE CON SVILUPPO DI MATERIALI AVANZATI E/O DISPOSITIVI INNOVATIVI E DIVULGAZIONE DEI RISULTATI NEI SETTORI PRODUTTIVI INTERESSATI ANCHE MEDIANTE ATTIVITA' DI FORMAZIONE. 5. ATTIVITA' DI RICERCA, STUDIO, CALCOLI, CONSULENZE, PROJECT MANAGEMENT, PROJECT FINANCING, STUDI DI FATTIBILITA' TECNICA ED ECONOMICO-FINANZIARIA, CONSULENZA STRATEGICA, BREVETTI E PROPRIETA' INDUSTRIALE ED ASSISTENZE TECNICHE PER OPERE, IMPIANTI ED INSEDIAMENTI CIVILI ED INDUSTRIALI NEI SETTORI PRODUTTIVI INTERESSATI (FARMACEUTICO, NUTRACEUTICO, AGROALIMENTARE E SCIENTIFICO IN GENERE), ANCHE IN MATERIA DI QUALITA' AZIENDALE E DI SICUREZZA ED IGIENE SUL LAVORO E NEGLI AMBIENTI DI LAVORO. 6. ASSISTENZA E SUPPORTO ALLA PROGETTAZIONE DI SISTEMI INFORMATICI A SERVIZIO E SUPPORTO DI ATTIVITA' TECNICHE E GESTIONALI NEI SETTORI PRODUTTIVI INTERESSATI (FARMACEUTICO, NUTRACEUTICO, AGROALIMENTARE E SCIENTIFICO IN GENERE), ANCHE CON SVILUPPO DI SOFTWARE APPLICATIVO. 7. ASSISTENZA TECNICA RELATIVAMENTE A STUDI DI FATTIBILITA' E CONGRUITA', VALUTAZIONE DELL'IMPATTO AMBIENTALE NELLE DISCIPLINE DEL SETTORE CHIMICO E CHIMICO-FARMACEUTICO E AFFINI (NUTRACEUTICO, AGROALIMENTARE E SCIENTIFICO IN GENERE). 8. ASSISTENZA TECNICA CONNESSA AI PRODOTTI INFORMATICI INNOVATIVI AD ALTO VALORE TECNOLOGICO. 9. SVILUPPO ATTIVITA' SEO, POSIZIONAMENTO E SVILUPPO SITI WEB E PROFESSIONALI, PUBBLICITA' E PROMOZIONE DI ATTIVITA' COMMERCIALI SUL WEB CON METODOLOGIE INNOVATIVE. 10. QUALSIASI ATTIVITA' NELL'AMBITO DELLA ICT NEI SETTORI PRODUTTIVI INTERESSATI (FARMACEUTICO, NUTRACEUTICO, AGROALIMENTARE E SCIENTIFICO IN GENERE) AD ALTO CONTENUTO TECNOLOGICO ED INNOVATIVO. 11. GRAFICA WEB ED EDITORIALE, CAMPAGNE DI MARKETING INNOVATIVE, IDEAZIONE E REGISTRAZIONE LOGHI, MARCHI E BREVETTI, STAMPA TIPOLITOGRAFICA E SU QUALSIASI MATERIALE, GADGET, BROCHURE, PRESENTAZIONI ON LINE E PRODUZIONI SU ALTRI SUPPORTI. 12. CREAZIONE, SVILUPPO, GESTIONE, CONSULENZA PER LA SPECIFICA ATTIVITA' DEL SOCIAL MEDIA MARKETING E TUTTE LE ATTIVITA' DI MARKETING INNOVATIVE E CHE FANNO USO DI STRUMENTI AD ALTO VALORE TECNOLOGICO. 13. ELABORAZIONE BUSINESS PLAN E PIANI DI IMPRESA PER PROGETTI DI FINANZIAMENTO PUBBLICO E PRIVATO E CONTROLLO DI GESTIONE, CON PARTICOLARE RIFERIMENTO AI PROGETTI INNOVATIVI E AD ALTO VALORE TECNOLOGICO. 14. CORSI DI FORMAZIONE LIBERI ED AUTORIZZATI DA ENTI PUBBLICI CON L'AUSILIO DI STRUMENTI TECNOLOGICAMENTE EVOLUTI ED INNOVATIVI. 15. ORGANIZZAZIONE E GESTIONE CONVEGNI, WORKSHOP MEETING, CONGRESSI, FIERE E CONTESTI NEL QUALE SVILUPPARE L'INFORMAZIONE, CONOSCENZA E SOCIALIZZAZIONE PREVALENTEMENTE SULLA RETE E SULLE TEMATICHE DELL'INNOVATIVITA'' E DELLE IDEE DI IMPRESA AD ALTO CONTENUTO TECNOLOGICO. 16. EESECUZIONE, ANCHE IN COLLABORAZIONE ED IN COOPERAZIONE CON ALTRI SOGGETTI, PUBBLICI E PRIVATI, STUDI, RICERCHE, ATTIVITA' DI INNOVAZIONE TECNOLOGICA, E ALTRI PROGRAMMI E INTERVENTI VARI, ASSUMENDONE ANCHE LA RELATIVA GESTIONE, VOLTI A FAR CONOSCERE, VALORIZZARE E CORRETTAMENTE UTILIZZARE LE TECNICHE E TECNOLOGIE NEI SETTORI PRODUTTIVI INTERESSATI (FARMACEUTICO, NUTRACEUTICO, AGROALIMENTARE E SCIENTIFICO IN GENERE). 17. ASSUNZIONE DI RAPPRESENTANZE COMMERCIALI DA PRODUTTORI NAZIONALI O INTERNAZIONALI OPERANTI NEL SETTORE DEI SENSORI E ATTREZZATURE DI MISURA E DI PROVA, MACCHINARI DI PROVA, SISTEMI DI MONITORAGGIO, LABORATORI MOBILI, MACCHINE, SOFTWARE E 18. PRODUZIONE DI COMPOSTI BIOLOGICAMENTE ATTIVI SIA DI ORIGINE SINTETICA SIA DI ORIGINE NATURALE E 19. REDIGERE, STAMPARE E COMMERCIALIZZARE TESTI, MANUALI O ALTRI SUPPORTI DIDATTICI ANCHE MEDIANTE STRUMENTI INFORMATICI E TECNOLOGICI IN GENERE

Carotenoid content of Goji berries: CIELAB, HPLC-DAD analyses and quantitative correlation

Fruits of Lycium barbarum L., have been used in Chinese traditional medicine for centuries. In the last decade, there has been much interest in the potential health benefits of many biologically constituents of these fruits. The high level of carotenoids offers protection against development of cardiovascular diseases, diabetes and related comorbidities. In the present work two different selections of Lycium barbarum L., cultivated in Italy and coming from three discrete harvest stages, were subjected to two different grinding procedure and to a simplified extraction method of carotenoid component. CIELAB colorimetric analysis of the freshly prepared purees and HPLC-DAD analysis of carotenoid extracts were performed and compared. Different harvesting dates and grinding procedures deeply influence the carotenoids content and statistical analysis showed high correlation between carotenoid content and colorimetric data. The final model provides a reliable tool to directly assess carotenoid content by performing cheap and routinely colorimetric analyses for food industry

Understanding the molecular determinant of reversible human monoamine oxidase B inhibitors containing 2H-chromen-2-one core: structure-based and ligand-based derived three-dimensional quantitative structure-activity relationships predictive models

Monoamine oxidase B (MAO B) catalyzes the oxidative deamination of aryalkylamines neurotransmitters with concomitant reduction of oxygen to hydrogen peroxide. Consequently, the enzyme’s malfunction can induce oxidative damage to mitochondrial DNA and mediates development of Parkinson’s disease. Thus, MAO B emerges as a promising target for developing pharmaceuticals potentially useful to treat this vicious neuro-degenerative condition. Aiming to contribute to the development of drugs with the reversible mechanism of MAO B inhibition only, herein, an extended in silico−in vitro procedure for the selection of novel MAO B inhibitors is demonstrated, including the following: (1) definition of optimized and validated structure-based three-dimensional (3-D) quantitative structure−activity relationships (QSAR) models derived from available cocrystallized inhibitor−MAO B complexes; (2) elaboration of SAR features for either irreversible or reversible MAO B inhibitors to characterize and improve coumarin-based inhibitor activity (Protein Data Bank ID: 2V61) as the most potent reversible lead compound; (3) definition of structure-based (SB) and ligand-based (LB) alignment rule assessments by which virtually any untested potential MAO B inhibitor might be evaluated; (4) predictive ability validation of the best 3-D QSAR model through SB/LB modeling of four coumarin-based external test sets (267 compounds); (5) design and SB/LB alignment of novel coumarin-based scaffolds experimentally validated through synthesis and biological evaluation in vitro. Due to the wide range of molecular diversity within the 3-D QSAR training set and derived features, the selected N probe-derived 3-D QSAR model proves to be a valuable tool for virtual screening (VS) of novel MAO B inhibitors and a platform for design, synthesis and evaluation of novel active structures. Accordingly, six highly active and selective MAO B inhibitors (picomolar to low nanomolar range of activity) were disclosed as a result of rational SB/LB 3D QSAR design; therefore, D123 (IC 50 = 0.83 nM, K i = 0.25 nM) and D124 (IC 50 = 0.97 nM, K i = 0.29 nM) are potential lead candidates as anti-Parkinson’s drugs

Novel Pyrimidine Derivatives as Antioxidant and Anticancer Agents: Design, Synthesis and Molecular Modeling Studies

The heterocyclic ring system of pyrido [2,3-d]pyrimidines is a privileged scaffold in medicinal chemistry, possessing several biological activities. The synthesis of the pyrimidine derivatives was performed via the condensation of a suitable α,β-unsaturated ketone with 4-amino-6-hydroxy-2-mercaptopyrimidine monohydrate in glacial acetic acid. Chalcones were synthesized, as starting materials, via the Claisen–Schmidt condensation of an appropriately substituted ketone and an appropriately substituted aldehyde in the presence of aqueous KOH 40% w/v in ethanol. All the synthesized compounds were characterized using IR, 1H-NMR, 13C-NMR, LC-MS and elemental analysis. The synthesized compounds were evaluated for their antioxidant (DPPH assay), anti-lipid peroxidation (AAPH), anti-LOX activities and ability to interact with glutathione. The compounds do not interact significantly with DPPH but strongly inhibit lipid peroxidation. Pyrimidine derivatives 2a (IC50 = 42 μΜ), 2f (IC50 = 47.5 μΜ) and chalcone 1g (IC50 = 17 μM) were the most potent lipoxygenase inhibitors. All the tested compounds were found to interact with glutathione, apart from 1h. Cell viability and cytotoxicity assays were performed with the HaCaT and A549 cell lines, respectively. In the MTT assay towards the HaCaT cell line, none of the compounds presented viability at 100 μM. On the contrary, in the MTT assay towards the A549 cell line, the tested compounds showed strong cytotoxicity at 100 μM, with derivative 2d presenting the strongest cytotoxic effects at the concentration of 50 μΜ