Removal of Organic Pollutants Benzene and Phenol Using Nanofiltration: A Molecular Dynamics Study.

Population growth has resulted in an increased demand for clean water. It is known that chemical pollutants such as phenol and benzene often make water unfit for consumption, and can be responsible for the appearance of diseases such as cancer. In this sense, studies aimed at decontaminating water are still necessary. In this study, molecular dynamics simulations were performed to evaluate the abilities of activated charcoal structures to adsorb benzene and phenol; the results of which were evaluated on the basis of root mean square deviations for all systems. The data were collected from the molecular dynamics (MD) trajectories and edited with the grace plotting tool. Visual molecular dynamics software was used to visualize the MD paths, and images were created using the UCSF chimera software. The results show that activated charcoal are viable alternatives for water decontamination by nanofiltration.

Identification of Novel Protein Kinase Receptor Type 2 Inhibitors Using Pharmacophore and Structure-Based Virtual Screening.

The Protein Kinase Receptor type 2 (RIPK2) plays an important role in the pathogenesis of inflammatory diseases; it signals downstream of the NOD1 and NOD2 intracellular sensors and promotes a productive inflammatory response. However, excessive NOD2 signaling has been associated with various diseases, including sarcoidosis and inflammatory arthritis; the pharmacological inhibition of RIPK2 is an affinity strategy that demonstrates an increased expression of pro-inflammatory secretion activity. In this study, a pharmacophoric model based on the crystallographic pose of ponatinib, a potent RIPK2 inhibitor, and 30 other ones selected from the BindingDB repository database, was built. Compounds were selected based on the available ZINC compounds database and in silico predictions of their pharmacokinetic, toxicity and potential biological activity. Molecular docking was performed to identify the probable interactions of the compounds as well as their binding affinity with RIPK2. The compounds were analyzed to ponatinib and WEHI-345, which also used as a control. At least one of the compounds exhibited suitable pharmacokinetic properties, low toxicity and an interesting binding affinity and high fitness compared with the crystallographic pose of WEHI-345 in complex with RIPK2. This compound also possessed suitable synthetic accessibility, rendering it a potential and very promising RIPK2 inhibitor to be further investigated in regards to different diseases, particularly inflammatory ones.

Leishmanicidal Activity of (+)-Phyllanthidine and the Phytochemical Profile of Margaritaria nobilis (Phyllanthaceae).

The effects of the Securinega alkaloid (+)-phyllanthidine on Leishmania (L.) amazonensis and the first chemical investigation of Margaritaria nobilis L.f. (Phyllanthaceae) are described. Treating the parasites with this alkaloid caused a dose-dependent reduction in promastigote growth of 67.68% (IC50 82.37 µg/mL or 353 µM) and in amastigote growth of 83.96% (IC50 49.11 µg/mL or 210 µM), together with ultrastructural alterations in the promastigotes. No cytotoxic effect was detected in mammalian cells (CC50 1727.48 µg/mL or CC50 5268 µM). Classical chromatographic techniques and spectral methods led to the isolation and identification of betulinic acid, kaempferol, corilagin, gallic acid and its methyl ester, besides (+)-phyllanthidine from M. nobilis leaves and stems. Margaritaria nobilis is another source of the small group of Securinega alkaloids, together with other Phyllanthaceae (Euphorbiaceae s.l.) species. The low toxicity to macrophages and the effects against promastigotes and amastigotes are suggestive that (+)-phyllanthidine could be a promising antileishmanial agent for treating cutaneous leishmaniasis.

A QSAR, pharmacokinetic and toxicological study of new artemisinin compounds with anticancer activity.

The Density Functional Theory (DFT) method and the 6-31G** basis set were employed to calculate the molecular properties of artemisinin and 20 derivatives with different degrees of cytotoxicity against the human hepatocellular carcinoma HepG2 line. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were employed to select the most important descriptors related to anticancer activity. The significant molecular descriptors related to the compounds with anticancer activity were the ALOGPS_log, Mor29m, IC5 and GAP energy. The Pearson correlation between activity and most important descriptors were used for the regression partial least squares (PLS) and principal component regression (PCR) models built. The regression PLS and PCR were very close, with variation between PLS and PCR of R(2) = ± 0.0106, R(2)(ajust) = ± 0.0125, s = ± 0.0234, F(4,11) = ± 12.7802, Q(2) = ± 0.0088, SEV = ± 0.0132, PRESS = ± 0.4808 and SPRESS = ± 0.0057. These models were used to predict the anticancer activity of eight new artemisinin compounds (test set) with unknown activity, and for these new compounds were predicted pharmacokinetic properties: human intestinal absorption (HIA), cellular permeability (PCaCO2), cell permeability Maden Darby Canine Kidney (PMDCK), skin permeability (P(Skin)), plasma protein binding (PPB) and penetration of the blood-brain barrier (C(Brain/Blood)), and toxicological: mutagenicity and carcinogenicity. The test set showed for two new artemisinin compounds satisfactory results for anticancer activity and pharmacokinetic and toxicological properties. Consequently, further studies need be done to evaluate the different proposals as well as their actions, toxicity, and potential use for treatment of cancers.

A SAR and QSAR study of new artemisinin compounds with antimalarial activity.

The Hartree-Fock method and the 6-31G** basis set were employed to calculate the molecular properties of artemisinin and 20 derivatives with antimalarial activity. Maps of molecular electrostatic potential (MEPs) and molecular docking were used to investigate the interaction between ligands and the receptor (heme). Principal component analysis and hierarchical cluster analysis were employed to select the most important descriptors related to activity. The correlation between biological activity and molecular properties was obtained using the partial least squares and principal component regression methods. The regression PLS and PCR models built in this study were also used to predict the antimalarial activity of 30 new artemisinin compounds with unknown activity. The models obtained showed not only statistical significance but also predictive ability. The significant molecular descriptors related to the compounds with antimalarial activity were the hydration energy (HE), the charge on the O11 oxygen atom (QO11), the torsion angle O1-O2-Fe-N2 (D2) and the maximum rate of R/Sanderson Electronegativity (RTe+). These variables led to a physical and structural explanation of the molecular properties that should be selected for when designing new ligands to be used as antimalarial agents.

Ricinine and other constituents of Aparisthmium cordatum (Euphorbiaceae).

The chemical study of Aparisthmium cordatum (Euphorbiaceae) led to the isolation of tannins, together with the alkaloid ricinine and other common compounds. The composition of A. cordatum is similar to most of the Alchornea species, from the same subtribe, except for the occurrence of ricinine. This study rectifies the first investigations published for A. cordatum that were conducted with Croton palanostigma.

Structure modeling of a metalloendopeptidase from Corynebacterium pseudotuberculosis.

Metalloendopeptidases are zinc-dependent hydrolases enzymes with many different roles in biological systems, ranging from remodeling conjunctive tissue to removing signaling sequences from nascent proteins. Here, we describe the three-dimensional structure of the metalloendopeptidase from Corynebacterium pseudotuberculosis generated by homology modeling and molecular dynamics. Analysis of key distances shows that His-132, Asp-136, His-211, Leu-212 and one molecule of water play an important role in the protein-Zn(2+) ion interaction. The model obtained may provide structural insights into this enzyme and can be useful for the design of new caseous lymphadenitis vaccines based on genetic attenuation from key point mutation.