Efficient siRNA-peptide conjugation for specific targeted delivery into tumor cells

Despite the broad applicability of the Huisgen cycloaddition reaction, the click functionalization of RNAs with peptides remains still a challenge. Here we describe a straightforward method for the click functionalization of siRNAs with peptides of different size and complexity. Among them, a promising peptide carrier for the selective siRNA delivery into HER2+ breast cancer cell lines

Conjugation of a Ru(II) Arene Complex to Neomycin or to Guanidinoneomycin Leads to Compounds with Differential Cytotoxicities and Accumulation between Cancer and Normal Cells

A straightforward methodology for the synthesis of conjugates between a cytotoxic organometallic ruthenium(II) complex and amino- and guanidinoglycosides, as potential RNA-targeted anticancer compounds, is described. Under microwave irradiation, the imidazole ligand incorporated on the aminoglycoside moiety (neamine or neomycin) was found to replace one triphenylphosphine ligand from the ruthenium precursor [(η6-p-cym)RuCl(PPh3)2]+, allowing the assembly of the target conjugates. The guanidinylated analogue was easily prepared from the neomycin-ruthenium conjugate by reaction with N,N′-di-Boc-N″-triflylguanidine, a powerful guanidinylating reagent that was compatible with the integrity of the metal complex. All conjugates were purified by semipreparative high-performance liquid chromatography (HPLC) and characterized by electrospray ionization (ESI) and matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) and NMR spectroscopy. The cytotoxicity of the compounds was tested in MCF-7 (breast) and DU-145 (prostate) human cancer cells, as well as in the normal HEK293 (Human Embryonic Kidney) cell line, revealing a dependence on the nature of the glycoside moiety and the type of cell (cancer or healthy). Indeed, the neomycin-ruthenium conjugate (2) displayed moderate antiproliferative activity in both cancer cell lines (IC50 ≈ 80 μM), whereas the neamine conjugate (4) was inactive (IC50 ≈ 200 μM). However, the guanidinylated analogue of the neomycin-ruthenium conjugate (3) required much lower concentrations than the parent conjugate for equal effect (IC50 = 7.17 μM in DU-145 and IC50 = 11.33 μM in MCF-7). Although the same ranking in antiproliferative activity was found in the nontumorigenic cell line (3 2 > 4), IC50 values indicate that aminoglycoside-containing conjugates are about 2-fold more cytotoxic in normal cells (e.g., IC50 = 49.4 μM for 2) than in cancer cells, whereas an opposite tendency was found with the guanidinylated conjugate, since its cytotoxicity in the normal cell line (IC50 = 12.75 μM for 3) was similar or even lower than that found in MCF-7 and DU-145 cancer cell lines, respectively. Cell uptake studies performed by ICP-MS with conjugates 2 and 3 revealed that guanidinylation of the neomycin moiety had a positive effect on accumulation (about 3-fold higher in DU-145 and 4-fold higher in HEK293), which correlates well with the higher antiproliferative activity of 3. Interestingly, despite the slightly higher accumulation in the normal cell than in the cancer cell line (about 1.4-fold), guanidinoneomycin-ruthenium conjugate (3) was more cytotoxic to cancer cells (about 1.8-fold), whereas the opposite tendency applied for neomycin-ruthenium conjugate (2). Such differences in cytotoxic activity and cellular accumulation between cancer and normal cells open the way to the creation of more selective, less toxic anticancer metallodrugs by conjugating cytotoxic metal-based complexes such as ruthenium(II) arene derivatives to guanidinoglycosides

Virtualizing university teaching through Open Educational Resources by means of ArcGIS Online (REARGOL)

La pandemia provocada por el virus SARS-CoV-2 (COVID19) ha demostrado la necesidad de acelerar la digitalización de la docencia universitaria. Las herramientas digitales para la transferencia ciencia-educación, que ya eran esenciales para asegurar la calidad de la docencia presencial, se han transformado en imprescindibles cuando las circunstancias han impuesto la docencia virtual. El proyecto REARGOL ha desarrollado y ensayado en ArcGIS online instrumentos para la virtualización de contenidos en asignaturas de grado y máster, sobre geomorfología, gestión de desastres, patrimonio natural y patrimonio cultural. Ha sido un ensayo piloto, replicable en todas las titulaciones y temáticas susceptibles de generar información geoespacial (prácticamente todos los títulos y áreas de conocimiento). El único límite es la imaginación. El proyecto ha priorizado la participación de estudiantes de grado, máster y doctorado, que han desarrollado 4 tipos de aplicaciones: Mapas Web y Web AppBuilder (visores cartográficos interactivos), encuestas Survey 123 (formularios recogida de datos), Cuadros de Mandos (plataformas online que permiten combinar varias aplicaciones) y Story Maps (presentaciones para mostrar conjuntamente información y aplicaciones ArcGIS online). Las aplicaciones que se ensayaron con éxito durante el curso 2020-2021, en asignaturas de grado y máster, así como en TFMs y TFGs, continúan utilizándose en el curso 2021-2022.The SARS-CoV-2 (COVID19) pandemic has shown the urgent need to improve university teaching. Digital resources for Science-Education transfer, which already were crucial for ensuring the quality of face-to-face teaching, turned to be indispensable when the health crisis forced virtual teaching. The REARGOL project has developed and tested ArcGIS Online tools for the virtualization of Bachelor’s and Master’s courses focused on geomorphology, natural disaster management, and natural and cultural heritage. This has been a preliminary test that could be applied to all undergraduate and postgraduate degrees, that can produce geospatial information in all knowledge areas. Imagination is the only constraint. The project has prioritized the participation of undergraduate and postgraduate students (Master and PhD). The project has priorized the participation of undergraduate and postgraduate (Master’s and PhD) students. They have developed four types of applications: Web Maps and Web AppBuilder (interactive cartographical viewers), Survey 123 (data collection forms), Dashboards (online platforms allowing to combine several applications) and Story Maps (presentations for displaying information and ArcGIS online applications). The tools successfully tested during the 2020-2021 academic year are still being used in the current one, in Bachelor’s and Master’s degrees, as well as in Bachelor’s and Master’s final dissertations.Depto. de GeografíaFac. de Geografía e HistoriaFALSEsubmitte

Computational Approaches for Drug-Induced Liver Injury (DILI) Prediction: State of the Art and Challenges

Drug-induced liver injury (DILI) is one of the prevailing causes of fulminant hepatic failure. It is estimated that three idiosyncratic drug reactions out of four result in liver transplantation or death. Additionally, DILI is the most common reason for withdrawal of an approved drug from the market. Therefore, the development of methods for the early identification of hepatotoxic drug candidates is of crucial importance. This review focuses on the current state of cheminformatics strategies being applied for the early in silico prediction of DILI. Herein, we discuss key issues associated with DILI modelling in terms of the data size, imbalance and quality, complexity of mechanisms, and the different levels of hepatotoxicity to model going from general hepatotoxicity to the molecular initiating events of DILI

Development of informatic tools for extracting biomedical data from open and propietary data sources with predictive purposes

Hem desenvolupat noves eines de software per tal d’obtenir informació de fonts publiques i privades per tal de desenvolupar models de toxicitat in silico. La primera eina es Collector, una aplicació de programari lliure que genera series de compostos preparats per fer modelat QSAR anotats amb bioactivitats extretes de la plataforma Open PHACTS usant tecnologies de la web semàntica. Collector ha estat utilitzada dins el projecte eTOX per desenvolupar models predictius sobre endpoints de toxicitat. Addicionalment hem concebut, desenvolupat i implementat un mètode per derivar scorings de toxicitat apropiats per modelatge predictiu que utilitza les dades obtingudes de informes d’estudis amb dosis repetides in vivo de la industria farmacèutica. El nostre mètode ha estat testejant aplicant-lo al modelat de hepatotoxicitat obtenint les dades corresponents per 3 endpoints: ‘degenerative lesions’, ‘inflammatory liver changes’ and ‘non-neoplasic proliferative lesions’. S’ha validat la idoneïtat d’aquestes dades obtingudes comparant-les amb els valors de point of departure obtinguts experimentalment i també desenvolupant models QSAR de prova obtenint resultats acceptables. El nostre mètode es basa en la inferència basada en ontologies per extreure informació de la nostra base de dades on tenim dades anotades basades en ontologies. El nostre mètode també es pot aplicar a altres bases de dades amb informació preclínica per generar scorings de toxicitat. Addicionalment el nostre mètode d’inferència basat en ontologies es pot aplicar a d’altre bases de dades relacionals anotades amb ontologies.We developed new software tools to obtain information from public and private data sources to develop in silico toxicity models. The first of these tools is Collector, an Open Source application that generates “QSAR-ready” series of compounds annotated with bioactivities, extracting the data from the Open PHACTS platform using semantic web technologies. Collector was applied in the framework of the eTOX project to develop predictive models for toxicity endpoints. Additionally, we conceived, designed, implemented and tested a method to derive toxicity scorings suitable for predictive modelling starting from in vivo preclinical repeated-dose studies generated by the pharmaceutical industry. This approach was tested by generating scorings for three hepatotoxicity endpoints: ‘degenerative lesions’, ‘inflammatory liver changes’ and ‘non-neoplasic proliferative lesions’. The suitability of these scores was tested by comparing them with experimentally obtained point of departure doses as well as by developing tentative QSAR models, obtaining acceptable results. Our method relies on ontology-based inference to extract information from our ontology annotated data stored in a relational database. Our method, as a whole, can be applied to other preclinical toxicity databases to generate toxicity scorings. Moreover, the ontology-based inference method on its own is applicable to any relational databases annotated with ontologies

An automated tool for obtaining QSAR-ready series of compounds using semantic web technologies

SUMMARY: We describe an application (Collector) for obtaining series of compounds annotated with bioactivity data, ready to be used for the development of quantitative structure-activity relationships (QSAR) models. The tool extracts data from the 'Open Pharmacological Space' (OPS) developed by the Open PHACTS project, using as input a valid name of the biological target. Collector uses the OPS ontologies for expanding the query using all known target synonyms and extracts compounds with bioactivity data against the target from multiple sources. The extracted data can be filtered to retain only drug-like compounds and the bioactivities can be automatically summarised to assign a single value per compound, yielding data ready to be used for QSAR modeling. The data obtained is locally stored facilitating the traceability and auditability of the process. Collector was used successfully for the development of models for toxicity endpoints within the eTOX project. AVAILABILITY AND IMPLEMENTATION: The software is available at http://phi.upf.edu/collector. The source code is located at https://github.com/phi-grib/Collector and is free for use under the GPL3 license. The web version is hosted at http://collector.upf.edu/. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.This project was developed under the Innovative Medicines Initiative Joint Undertaking Open PHACTS Project, grant agreement number 115191 and eTOX project, grant agreement n° 115002, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013) and EFPIA companies’ in kind contribution

PharmaTrek: a semantic web explorer for open innovation in multitarget drug discovery

This project was developed under the Innovative Medicines Initiative Joint Undertaking Open PHACTS Project, Grant Agreement Number 115191, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and members of the European Federation of Pharmaceutical Industries and Associations (EFPIA

PharmaTrek: a semantic web explorer for open innovation in multitarget drug discovery

This project was developed under the Innovative Medicines Initiative Joint Undertaking Open PHACTS Project, Grant Agreement Number 115191, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and members of the European Federation of Pharmaceutical Industries and Associations (EFPIA

Planta de producción ácido glioxílico

El objetivo principal del presente proyecto es el estudio y la viabilidad de la construcción de una planta de fabricación de ácido glioxílico a partir de anhídrido maleico (C2H2(CO)2O) y ozono (O3) ubicada en el término municipal de Tarragona. Para el diseño de la planta se ha tenido en cuenta la normativa y la legislación vigente tanto a nivel urbanístico como sectorial, con especial atención a las áreas de seguridad y medio ambiente