Melatonin modulates acute cardiac muscle damage induced by carbon tetrachloride - involvement of oxidative damage, glutathione, and arginine and nitric oxide metabolism.

The present study was designed to evaluate the cardioprotective effects of melatonin (a single dose of 50 mg·kg-1), a naturally occurring polypharmacological molecule, in Wistar rats acutely exposed to carbon tetrachloride (CCl4). This was done for the first time by tracking different biochemical parameters that reflect rat heart antioxidative and oxidative capacities, nitric oxide and arginine metabolism, and the glutathione cycle. Additionally, the extrinsic apoptosis pathway related parameters were studied. Acute exposure to CCl4 led to an increase in the studied tissue oxidant parameters (hydrogen peroxide, malondialdehyde, and carbonylated protein content), as well as the activity alteration of antioxidant (catalase, superoxide dismutase, and peroxidase) and glutathione-metabolizing (glutathione peroxidase, S-transferase, and reductase) enzymes. Furthermore, CCl4 caused a disturbance in the tissue myeloperoxidase, nitric oxide, citrulline, arginase, and inducible nitric oxide synthase content and activities and in two apoptosis-related parameters, caspase-3 and FAS ligand. Melatonin as a post-treatment prevented the changes induced by CCl4 to a differing extent, and in some cases, it was so potent that it completely abolished any tissue disturbances. This study is a promising starting point for further research directed to the development of melatonin treatment in cardiac tissue associated diseases.

Design and development of novel therapeutics for coronary heart disease treatment based on cholesteryl ester transfer protein inhibition - in silico approach.

Cholesteryl ester transfer protein (CETP) belongs to the group of enzymes which inhibition have the application in the treatment of cardiovascular diseases. This study presents QSAR modeling for a set of compounds acting as CETP inhibitors based on the Monte Carlo optimization with SMILES notation and molecular graph-based descriptors, and field-based 3D modeling. A 3D QSAR model was developed for one random split into the training and test sets, whereas conformation independent QSAR models were developed for three random splits, with the results suggesting there is an excellent correlation between them. Various statistical approaches were used to assess the statistical quality of the developed models, including robustness and predictability, and the obtained results were very good. This study used a novel statistical metric known as the index of ideality of correlation for the final assessment of the model, and the results that were obtained suggested that the model was good. Also, molecular fragments which account for the increases and/or decreases of a studied activity were defined and then used for the computer-aided design of new compounds as potential CETP inhibitors. The final assessment of the developed QSAR model and designed inhibitors was done using molecular docking, which revealed an excellent correlation with the results from QSAR modeling.Communicated by Ramaswamy H. Sarma.

Development and design of novel cardiovascular therapeutics based on Rho kinase inhibition-In silico approach.

Rho kinases, one of the best-known members of the serine/threonine (Ser/Thr) protein kinase family, can be used as target enzymes for the treatment of many diseases such as cancer or multiple sclerosis, and especially for the treatment of cardiovascular diseases. This study presents QSAR modeling for a series of 41 chemical compounds as Rho kinase inhibitors based on the Monte Carlo method. QSAR models were developed for three random splits into the training and test set. Molecular descriptors used for QSAR modeling were based on the SMILES notation and local invariants of the molecular graph. The statistical quality of the developed model, including robustness and predictability, was tested with different statistical approaches and satisfying results were obtained. The best calculated QSAR model had the following statistical parameters: r2 = 0.8825 and q2 = 0.8626 for the training set and r2 = 0.9377 and q2 = 0.9124 for the test set. Novel statistical metric entitled as the index of ideality of correlation was used for the final model assessment, and the obtained results were 0.6631 for the training and 0.9683 for the test set. Molecular fragments responsible for the increases and decreases of the studied activity were defined and they were further used for the computer-aided design of new compounds as potential Rho kinase inhibitors. The final assessment of the developed QSAR model and designed inhibitors was achieved with the application of molecular docking. An excellent correlation between the results from QSAR and molecular docking studies was obtained.