Selective serotonin reuptake inhibitor (SSRI) antidepressants consumption has increased significantly worldwide leading to its environmental dissemination. Their frequent and increasing detection in different environmental matrices is thus an emerging environmental concern as these drugs are biologically active substances that, although designed to modulate human behaviour, have the ability to alter fish behaviour, physiology, and gene expression, even at low concentrations. The available studies with paroxetine are scarce and there is little information on how chronic exposure to SSRIs may influence the response to other environmental contaminants like nanoplastics (NPLs), which is an environmentally relevant condition as SSRIs do not exist alone in the environment. Accordingly, in this study, the effects of zebrafish 21 days exposure to 0, 40, and 400 µg/L of the antidepressant paroxetine (PAR) was assessed by studying fish behaviour. Moreover, this study also assessed how chronic exposure to PAR would affect the response to acute exposure to 1 and 10 µg/L of 50 nm polymethylmethacrylate NPLs (PMMA-NPLs).

Overall, chronic exposure to PAR decreased fish basal locomotor activity during both light and dark periods and interfered with stress response. When considering fish that were pre-exposed to PAR and then subjected to PMMA acute exposure, a significant interaction between PAR and PMMA-NPLs was found when considering fish swimming behaviour under light conditions. These results highlight the ability of SSRIs to modulate effects of other contaminants and the need to consider organisms’ previous contamination history.

Breast cancer is a common kind of cancer affecting women with a fatal outcome. Due to extensive treatment cycles, breast cancer resistance has now become a worldwide issue. Therefore, the only realistic treatment is the rapid development anti-breast cancer medications. To improve and propose new anti-breast cancer drugs, three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking studies on thioquinazolinone derivatives with aromatase enzyme (PDB: 3S7S) were attempted. Comparative Molecular Similarity Indices Analysis (CoMSIA) was utilized to develop the 3D-QSAR model in this study. The best CoMSIA model (with considerable values of Q², R² and R²_pred) was also utilized in an effort to get the high predictability. External validation that uses a test set has been utilized to validate the predictive ability of the fitted model. According to the findings, the Electrostatic, Hydrophobic, Hydrogen Bond Donor and Acceptor fields had a serious influence on anti-breast cancer activities. Thus, we designed a variety of novel effective aromatase inhibitors based on prior findings and predicted their inhibitory activities using the best model. Moreover, ADMET investigations were employed to analyze the pharmacokinetic properties of drug-candidates.

The World Health Organization (WHO), on March 12, 2020, declared a pandemic state of the global epidemic caused by a new coronavirus, SARS-CoV-2. Identifying the Main protease (Mpro) of SARS-CoV-2 as a drug target led to a speed-up drug design and discovery process. However, an effective algorithm is needed to indicate the activity against (Mpro) during virtual screening. In our studies, we proposed a virtual screening protocol combining molecular modeling and machine learning techniques that will allow us to discover novel inhibitors of SARS-CoV-2 Mpro. Based on results from virtual screening, potential Mpro inhibitors were selected for synthesis and further in vitro evaluation. The effectiveness of small-molecule compounds, derivatives of mono-, di- and tri-heterocyclic azole systems with various substituents of an amine, amide, or ester nature were evaluated in the test for antiviral activity. Compounds were first tested on Vero E6 cells to select non-toxic doses on SARS-CoV-2 infected cells. Next, we studied the anti-SARS-CoV-2 activity of selected compounds on infected Vero E6 cells. The most active compound showed 52.6% inhibition of SARS-CoV-2 replication at the dose of 20 µM. In summary, the application of the proposed virtual screening protocol allowed the selection of new compounds to be used as a starting point for developing SARS-Cov-2 Mpro inhibitors.

The project is co-financed by the Polish National Agency for Academic Exchange (PPN/BIT/2021/1/00056/U/00001), Italian Ministry of Foreign Affairs and International Cooperation Executive Programme of Scientific and Technological Cooperation between the Italian Republic and the Republic of Poland (PO22MO07), JUMC grants N42/DBS/000217, N42/DBS/000303.

Amidrazones are known for the broad biological activity of their derivatives (antimicrobial, anti-inflammatory, antiparasitic, antitumor and others). Searching for new drugs twelve new derivatives of N³-substituted amidrazones were obtained in the reaction with cis-1,2,3,6-tetrahydrophthalic anhydride. The structures of obtained linear compounds and 1,2,4-triazole derivatives were confirmed by ¹H NMR, ¹³C NMR and MS. Toxicity and inflammatory activity of obtained compounds (at concentrations of 10, 50 and 100 µg/mL) were studied in human peripheral blood mononuclear cells (PBMC). The influence of new derivatives on cytokine production (TNF-α, IL-6 and IL-10) was examined in PBMC cultures stimulated by LPS. Antiproliferative activity of compounds was studied in PBMC cultures stimulated by phytohaemagglutinin. Minimal inhibitory activity of compounds was studied by broth microdilution method on Gram-positive (S. aureus, M. smegmatis,) and Gram-negative (E. coli, Y. enterocolitica, K. pneumonia) bacterial and fungal C. albicans strain.

Obtained 1,2,4-triazole derivatives were no toxic to PBMC at concentration range 10-100 µg/mL. Only one 1,2,4-triazole derivative showed significant antiproliferative activity at the highest dose. Five 1,2,4-triazole derivatives showed significant, stronger than ibuprofen inhibition of pro-inflammatory TNF-α production at concentrations 10 and 50 µg/mL as well as significant elevation of levels of anti-inflammatory cytokine IL-10 at each used dose. Two linear compounds showed antibacterial activity against Gram-positive bacteria. In conclusion five obtained compounds showed a strong anti-inflammatory effect and deserves further research.

Ceftriaxone (CTX) a third-generation cephalosporin, is a broad-spectrum antibiotic that can be used by intramuscular or intravenous routes to treat various types of infection. However, CTX has poor cellular penetration and poor diffusion due to its high molecular weight and high hydrophilicity. To address these problems, we propose an innovative nanotherapy based on the encapsulation of CTX in a nanostructured lipid carrier. Usually, several attempts must be done, on a trial-and-error basis, until a formulation that guarantees high drug encapsulation and suitable physicochemical properties is found. Machine Learning (ML) has recently stirred great interest as a tool to model and predict the nanoparticles biological activity. Herein, for the first time, the use of ML for the optimization of a nanoformulation is explored. Several variables were optimized simultaneously, namely the amount of solid lipid, the percentage of liquid lipid, the surfactant solution, the water volume, the sonication amplitude, and the sonication time. To define the best nanoformulation, three different outcomes were considered: encapsulation efficiency of CTX, size of the nanoparticles and their zeta potential. Our ML approach was able to find, with a low number of experiments, the conditions that provided formulations with the highest encapsulation efficiency of CTX and nanoparticles with suitable size and adequate zeta potential. Besides the impressive acceleration of the optimization process that was achieved, the optimization guided by our ML model also provided insights over the optimization of other nanoformulations.