No abstract

No abstract

No abstract

This study aimed at evidencing contaminant inputs from a rapidly growing population and the accompanying anthropogenic activities to river sediments. The Fez metropolitan area and its impacts on the Sebou's sediments (the main Moroccan river) were chosen as a case study. The Fez agglomeration is surrounded by the river Fez, receiving the wastewaters of this developing city and then flowing into the Sebou. The sediment cores from the Fez and Sebou Rivers were extracted and analysed for major elements, butyltins and toxic metals. Normalised enrichment factors and geoaccumulation index were calculated. Toxicity risk was assessed by two sets of sediment quality guideline (SQG) indices. A moderate level of contamination by butyltins was observed, with monobutyltin being the dominant species across all sites and depths. The lowest level of metal pollution was identified in the Sebou's sediments in upstream of Fez city, whilst the Fez' sediments were heavily polluted and exhibited bottom-up accumulation trends, which is a clear signature of recent inputs from the untreated wastewaters of Fez city. Consequently, the sediments of Fez and Sebou at the downstream of the confluence were found to be potentially toxic, according to the SQG levels. This finding is concerned with aquatic organisms, as well as to the riverside population, which is certainly exposed to these pollutants through the daily use of water. This study suggests that although Morocco has adopted environmental regulations aiming at restricting pollutant discharges into the natural ecosystems, such regulations are neither well respected by the main polluters nor efficiently enforced by the authorities.

The recent outbreak of the coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) in the last few months raised global health concern. Previous research described that remdesivir and ritonavir can be used as effective drugs against COVID-19. In this study, we applied the structure-based virtual screening (SBVS) on the high similar remdesivir- and ritonavir-approved drugs, selected from the DrugBank database as well as on a series of ritonavir derivatives, selected from the literature. The aim was to provide new potent SARS-CoV-2 main protease (Mpro) inhibitors with high stability. The analysis was performed using AutoDock VINA implicated in the PyRx 0.8 tool. Based on the ligand binding energy, 20 compounds were selected and then analyzed by AutoDock tools. Among the 20 compounds, 3 compounds were selected as high-potent anti-COVID-19.

No abstract

No abstract

Quantitative Structure Activity Relationship (QSAR) analysis techniques are tools largely utilized in many research fields, including drug discovery processes. In this work electronic descriptors are calculated with the Gaussian 03W software using the DFT method with the BecKe 3-parameters exchange functional and Lee-Yang-Parr correlation functional, with Kohn and Sham orbitals (KS) developed on a Gaussian Basis of type 6-31G (d), in combination with five Lipinski parameters that have been calculated with ChemOffice software, in order to develop a statistically verified 2D-QSAR model able to predict the biological activity of new molecules belonging to the same range of coumarins rather than chemical synthesis and biological evaluations that require more time and resources. Two QSAR models against both MCF-7 and HepG-2 cell lines are obtained using the multiple linear regression method. The predictive power of these models has been confirmed by internal and external validation. The Leverage method was used to determine the domain of applicability of the 2D-QSAR models developed. The results indicate that the best QSAR model is the one that links the 2D descriptors with the CDK inhibitory activity of the cell line (HepG-2) R 2 = 0.748, R 2 cv = 0.618, MSE = 0.03 for the learning series and R 2 = 0.73, MSE = 0.18 for the test series. This model implies that coumarin inhibitory activity is strongly related to dipole moment and the number of hydrogen bond donors. The results obtained suggest the importance of studying structure-activity relationships as a principal axis in drug design. The docking procedure using AutoDOCK Tools was also used to understand the mechanisms of molecular interactions and consequently, to develop new inhibitors.