Development of In Vitro Corneal Models: Opportunity for Pharmacological Testing

The human eye is a specialized organ with a complex anatomy and physiology, because it is characterized by different cell types with specific physiological functions. Given the complexity of the eye, ocular tissues are finely organized and orchestrated. In the last few years, many in vitro models have been developed in order to meet the 3Rs principle (Replacement, Reduction and Refinement) for eye toxicity testing. This procedure is highly necessary to ensure that the risks associated with ophthalmic products meet appropriate safety criteria. In vitro preclinical testing is now a well-established practice of significant importance for evaluating the efficacy and safety of cosmetic, pharmaceutical, and nutraceutical products. Along with in vitro testing, also computational procedures, herein described, for evaluating the pharmacological profile of potential ocular drug candidates including their toxicity, are in rapid expansion. In this review, the ocular cell types and functionality are described, providing an overview about the scientific challenge for the development of three-dimensional (3D) in vitro models

Computer-driven development of an in silico tool for finding selective histone deacetylase 1 inhibitors

Histone deacetylases (HDACs) are a class of epigenetic modulators overexpressed in numerous types of cancers. Consequently, HDAC inhibitors (HDACIs) have emerged as promising antineoplastic agents. Unfortunately, the most developed HDACIs suffer from poor selectivity towards a specific isoform, limiting their clinical applicability. Among the isoforms, HDAC1 represents a crucial target for designing selective HDACIs, being aberrantly expressed in several malignancies. Accordingly, the development of a predictive in silico tool employing a large set of HDACIs (aminophenylbenzamide derivatives) is herein presented for the first time. Software Phase was used to derive a 3D-QSAR model, employing as alignment rule a common-features pharmacophore built on 20 highly active/selective HDAC1 inhibitors. The 3D-QSAR model was generated using 370 benzamide-based HDACIs, which yielded an excellent correlation coefficient value (R2 = 0.958) and a satisfactory predictive power (Q2 = 0.822; Q2F3 = 0.894). The model was validated (r2ext_ts = 0.794) using an external test set (113 compounds not used for generating the model), and by employing a decoys set and the receiver-operating characteristic (ROC) curve analysis, evaluating the Güner-Henry score (GH) and the enrichment factor (EF). The results confirmed a satisfactory predictive power of the 3D-QSAR model. This latter represents a useful filtering tool for screening large chemical databases, finding novel derivatives with improved HDAC1 inhibitory activity

Role of hydrogen sulfide in endothelial dysfunction: Pathophysiology and therapeutic approaches

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IN SILICO METHODS FOR DRUG DESIGN AND DISCOVERY

Computer-aided drug design (CADD) methodologies are playing an ever-increasing role in drug discovery that are critical in the cost-effective identification of promising drug candidates. These computational methods are relevant in limiting the use of animal models in pharmacological research, for aiding the rational design of novel and safe drug candidates, and for repositioning marketed drugs, supporting medicinal chemists and pharmacologists during the drug discovery trajectory.Within this field of research, we launched a Research Topic in Frontiers in Chemistry in March 2019 entitled “In silico Methods for Drug Design and Discovery,” which involved two sections of the journal: Medicinal and Pharmaceutical Chemistry and Theoretical and Computational Chemistry. For the reasons mentioned, this Research Topic attracted the attention of scientists and received a large number of submitted manuscripts. Among them 27 Original Research articles, five Review articles, and two Perspective articles have been published within the Research Topic. The Original Research articles cover most of the topics in CADD, reporting advanced in silico methods in drug discovery, while the Review articles offer a point of view of some computer-driven techniques applied to drug research. Finally, the Perspective articles provide a vision of specific computational approaches with an outlook in the modern era of CADD

CALET on the International Space Station: new direct measurements of cosmic-ray iron and nickel

The Calorimetric Electron Telescope (CALET), in operation on the International Space Station since 2015, collected a large sample of cosmic-ray over a wide energy interval. Approximately 20 million triggered events per month are recorded with energies > 10 GeV. The instrument identifies the charge of individual elements up to nickel and beyond and, thanks to a homogeneous lead-tungstate calorimeter, it measures the energy of cosmic-ray nuclei providing a direct measurement of their spectra. Iron and nickel spectra are a low background measurement with negligible contamination from spallation of higher mass elements. Iron and nickel nuclei play a key role in understanding the acceleration and propagation mechanisms of charged particles in our Galaxy. In this contribution a direct measurement of iron and nickel spectra, based on more than five years of data, are presented in the energy range from 10 GeV/n to 2 TeV/n and from 8.8 GeV/n to 240 GeV/n, respectively. The spectra are compatible within the errors with a single power law in the energy region from 50 GeV/n to 2 TeV/n and from 20 GeV/n to 240 GeV/n, respectively. Systematic uncertainties are detailed and the nickel to iron flux ratio is presented. This unprecedented measurement confirms that both elements have very similar fluxes in shape and energy dependence, suggesting that their origin, acceleration, and propagation might be explained invoking an identical mechanism in the energy range explored so far

CALET on the International Space Station: a precise measurement of the iron spectrum

The Calorimetric Electron Telescope (CALET) was launched on the International Space Station in 2015 and since then has collected a large sample of cosmic-ray charged particles over a wide energy. Thanks to a couple of layers of segmented plastic scintillators placed on top of the detector, the instrument is able to identify the charge of individual elements from proton to iron (and above). The imaging tungsten scintillating fiber calorimeter provides accurate particle tracking and the lead tungstate homogeneous calorimeter can measured the energy with a wide dynamic range. One of the CALET scientific objectives is to measure the energy spectra of cosmic rays to shed light on their acceleration and propagation in the Galaxy. By the observation in first five years, a precise measurement of the iron spectrum is now available in the range of kinetic energy per nucleon from 10 GeV/n to 2 TeV/n. The CALET’s result with a description of the analysis and details on systematic uncertainties will be illustrated. Also, a comparison with previous experiments’ results is given

The green chemistry of chalcones: Valuable sources of privileged core structures for drug discovery

The sustainable use of resources is essential in all production areas, including pharmaceuticals. However, the aspect of sustainability needs to be taken into consideration not only in the production phase, but during the whole medicinal chemistry drug discovery trajectory. The continuous progress in the fields of green chemistry and the use of artificial intelligence are contributing to the speed and effectiveness of a more sustainable drug discovery pipeline. In this light, here we review the most recent sustainable and green synthetic approaches used for the preparation and derivatization of chalcones, an important class of privileged structures and building blocks used for the preparation of new biologically active compounds with a broad spectrum of potential therapeutic applications. The literature here reported has been retrieved from the SciFinder database using the term "chalcone " as a keyword and filtering the results applying the concept: "green chemistry ", and from the Reaxys database using the keywords "chalcone " and "green ". For both databases the time-frame was 2017-2022. References were manually selected based on relevance

0365: Non-peptidic prokineticin receptor 1 agonist as a novel cardioprotective therapeutic

ObjectiveProkineticins are potent angiogenic peptides that bind to two G protein-coupled receptors to initiate their biological effects. We previously have shown that prokineticin receptor-1 (PKR1) signaling contributes to cardiomyocyte survival or repair in myocardial infarction. Here, we discovered the first non-peptidic PKR1 agonists and examined their effects in mice model of heart diseases.Methods and resultsHerein we identify a selective PKR1 agonist both in vitro and in vivo, utilizing GPCR structure-based virtual screening approach. High Throughput Docking was carried out by GOLD using homology model of PKR1. Asinex gold collection 3D chemical databese (250,000 compounds) was screened by the docking protocol. We provided a strategy with a high potential for in silico identifying one agonist hit. We present here IS20, the first synthetic PKR1 agonist that induces angiogenesis in the presence of PKR1 on the endothelial cells seeded on matrigel. IS20 reduced doxorubicin cytotoxicity in H9C2 cells. IS20 promotes mouse epicardial progenitor cell differentiation into endothelial cells. In vivo IS20 activates Akt in mice heart. IS20 treatment of mice after coronary ligation reduces mortality by 30%.ConclusionThis study identifies a non-peptidic PKR1 agonist as therapeutic target holding promise for treatment of heart diseases

Identification of Novel 3-Hydroxy-pyran-4-One Derivatives as Potent HIV-1 Integrase Inhibitors Using in silico Structure-Based Combinatorial Library Design Approach

We describe herein the development and experimental validation of a computational protocol for optimizing a series of 3-hydroxy-pyran-4-one derivatives as HIV integrase inhibitors (HIV INIs). Starting from a previously developed micromolar inhibitors of HIV integrase (HIV IN), we performed an in-depth investigation based on an in silico structure-based combinatorial library designing approach. This method allowed us to combine a combinatorial library design and side chain hopping with Quantum Polarized Ligand Docking (QPLD) studies and Molecular Dynamics (MD) simulation. The combinatorial library design allowed the identification of the best decorations for our promising scaffold. The resulting compounds were assessed by the mentioned QPLD methodology using a homology model of full-length binary HIV IN/DNA for retrieving the best performing compounds acting as HIV INIs. Along with the prediction of physico-chemical properties, we were able to select a limited number of drug-like compounds potentially displaying potent HIV IN inhibition. From this final set, based on the synthetic accessibility, we further shortlisted three representative compounds for the synthesis. The compounds were experimentally assessed in vitro for evaluating overall HIV-1 IN inhibition, HIV-1 IN strand transfer activity inhibition, HIV-1 activity inhibition and cellular toxicity. Gratifyingly, all of them showed relevant inhibitory activity in the in vitro tests along with no toxicity. Among them HPCAR-28 represents the most promising compound as potential anti-HIV agent, showing inhibitory activity against HIV IN in the low nanomolar range, comparable to that found for Raltegravir, and relevant potency in inhibiting HIV-1 replication and HIV-1 IN strand transfer activity. In summary, our results outline HPCAR-28 as a useful optimized hit for the potential treatment of HIV-1 infection by targeting HIV IN

SeaClouds: Agile management of complex applications across multiple heterogeneous clouds

SeaClouds is a European FP7 research project, whose goal is to develop a novel open solution to provide developers with the capabilities to design, configure, deploy, and manage complex applications across multiple heterogeneous clouds in an efficient and adaptive way