From Primary Data to Ethnopharmacological Investigations on Achillea erba-rotta subsp. moschata (Wulfen) I.Richardson as a Remedy against Gastric Ailments in Valmalenco (Italy).

(1) Background: Within the framework of the European Interreg Italy-Switzerland B-ICE & Heritage project (2018-2022), this study originated from a three-year ethnobotanical survey in Valmalenco (Sondrio, Italy). Following a preliminary work published by our group, this research further explored the folk therapeutic use of Achillea erba-rotta subsp. moschata (Wulfen) I.Richardson (Asteraceae) for dyspepsia disorders, specifically its anti-inflammatory potential at a gastrointestinal level. (2) Methods: Semi-structured interviews were performed. The bitter taste was investigated through molecular docking software (PLANTS, GOLD), while the anti-inflammatory activity of the hydroethanolic extract, infusion, and decoction was evaluated based on the release of IL-8 and IL-6 after treatment with TNFα or Helicobacter pylori. The minimum inhibitory concentration and bacterial adhesion on the gastric epithelium were evaluated. (3) Results: In total, 401 respondents were interviewed. Molecular docking highlighted di-caffeoylquinic acids as the main compounds responsible for the interaction with bitter taste receptors. The moderate inhibition of IL-6 and IL-8 release was recorded, while, in the co-culture with H. pylori, stronger anti-inflammatory potential was expressed (29-45 µg/mL). The concentration-dependent inhibition of H. pylori growth was recorded (MIC = 100 µg/mL), with a significant anti-adhesive effect. (4) Conclusions: Confirming the folk tradition, the study emphasizes the species' potentiality for dyspepsia disorders. Future studies are needed to identify the components mostly responsible for the biological effects.

MetaSpot: A General Approach for Recognizing the Reactive Atoms Undergoing Metabolic Reactions Based on the MetaQSAR Database.

The prediction of drug metabolism is attracting great interest for the possibility of discarding molecules with unfavorable ADME/Tox profile at the early stage of the drug discovery process. In this context, artificial intelligence methods can generate highly performing predictive models if they are trained by accurate metabolic data. MetaQSAR-based datasets were collected to predict the sites of metabolism for most metabolic reactions. The models were based on a set of structural, physicochemical, and stereo-electronic descriptors and were generated by the random forest algorithm. For each considered biotransformation, two types of models were developed: the first type involved all non-reactive atoms and included atom types among the descriptors, while the second type involved only non-reactive centers having the same atom type(s) of the reactive atoms. All the models of the first type revealed very high performances; the models of the second type show on average worst performances while being almost always able to recognize the reactive centers; only conjugations with glucuronic acid are unsatisfactorily predicted by the models of the second type. Feature evaluation confirms the major role of lipophilicity, self-polarizability, and H-bonding for almost all considered reactions. The obtained results emphasize the possibility of recognizing the sites of metabolism by classification models trained on MetaQSAR database. The two types of models can be synergistically combined since the first models identify which atoms can undergo a given metabolic reactions, while the second models detect the truly reactive centers. The generated models are available as scripts for the VEGA program.

The VEGA web service: multipurpose online tools for molecular modelling and docking analyses.

The paper presents the VEGA Online web service, which includes a set of freely available tools deriving from the development of the VEGA suite of programs. In detail, the paper is focused on two tools: the VEGA Web Edition (WE) and the Score tool. The former is a versatile file format converter including relevant features for 2D/3D conversion, for surface mapping and for editing/preparing input files. The Score application allows rescoring docking poses and in particular includes the MLP Interactions Scores (MLPInS) for describing hydrophobic interactions. To the best of our knowledge, this web service is the only available resource by which one can calculate both the virtual log P of a given input molecule according to the MLP approach plus the corresponding MLP surface.

Highly Potent and Selective Dopamine D4 Receptor Antagonists Potentially Useful for the Treatment of Glioblastoma.

To better understand the role of dopamine D4 receptor (D4R) in glioblastoma (GBM), in the present paper, new ligands endowed with high affinity and selectivity for D4R were discovered starting from the brain penetrant and D4R selective lead compound 1-(3-(4-phenylpiperazin-1-yl)propyl)-3,4-dihydroquinolin-2(1H)-one (6). In particular, the D4R antagonist 24, showing the highest affinity and selectivity over D2R and D3R within the series (D2/D4 = 8318, D3/D4 = 3715), and the biased ligand 29, partially activating D4R Gi-/Go-protein and blocking ß-arrestin recruitment, emerged as the most interesting compounds. These compounds, evaluated for their GBM antitumor activity, induced a decreased viability of GBM cell lines and primary GBM stem cells (GSC#83), with the maximal efficacy being reached at a concentration of 10 µM. Interestingly, the treatment with both compounds 24 and 29 induced an increased effect in reducing the cell viability with respect to temozolomide, which is the first-choice chemotherapeutic drug in GBM.

Phenolic Extracts from Extra Virgin Olive Oils Inhibit Dipeptidyl Peptidase IV Activity: In Vitro, Cellular, and In Silico Molecular Modeling Investigations.

Two extra virgin olive oil (EVOO) phenolic extracts (BUO and OMN) modulate DPP-IV activity. The in vitro DPP-IV activity assay was performed at the concentrations of 1, 10, 100, 500, and 1000 µg/mL, showing a dose-dependent inhibition by 6.8 ± 1.9, 17.4 ± 6.1, 37.9 ± 2.4, 57.8 ± 2.9, and 81 ± 1.4% for BUO and by 5.4 ± 1.7, 8.9 ± 0.4, 28.4 ± 7.2, 52 ± 1.3, and 77.5 ± 3.5% for OMN. Moreover, both BUO and OMN reduced the DPP-IV activity expressed by Caco-2 cells by 2.9 ± 0.7, 44.4 ± 0.7, 61.2 ± 1.8, and 85 ± 4.2% and by 3 ± 1.9, 35 ± 9.4, 60 ± 7.2, and 82 ± 2.8%, respectively, at the same doses. The concentration of the most abundant and representative secoiridoids within both extracts was analyzed by nuclear magnetic resonance (1H-NMR). Oleuropein, oleacein, oleocanthal, hydroxytyrosol, and tyrosol, tested alone, reduced the DPP-IV activity, with IC50 of 472.3 ± 21.7, 187 ± 11.4, 354.5 ± 12.7, 741.6 ± 35.7, and 1112 ± 55.6 µM, respectively. Finally, in silico molecular docking simulations permitted the study of the binding mode of these compounds.