A novel phospholipase A2 (D49) from the venom of the Crotalus oreganus abyssus (North American Grand canyon rattlesnake).

Currently, Crotalus viridis was divided into two species: Crotalus viridis and Crotalus oreganus. The current classification divides "the old" Crotalus viridis into two new and independent species: Crotalus viridis (subspecies: viridis and nuntius) and Crotalus oreganus (subspecies: abyssus, lutosus, concolor, oreganus, helleri, cerberus, and caliginis). The analysis of a product from cDNA (E6d), derived from the gland of a specie Crotalus viridis viridis, was found to produce an acid phospholipase A2. In this study we isolated and characterized a PLA2 (D49) from Crotalus oreganus abyssus venom. Our studies show that the PLA2 produced from the cDNA of Crotalus viridis viridis (named E6d) is exactly the same PLA2 primary sequence of amino acids isolated from the venom of Crotalus oreganus abyssus. Thus, the PLA2 from E6d cDNA is actually the same PLA2 presented in the venom of Crotalus oreganus abyssus and does not correspond to the venom from Crotalus viridis viridis. These facts highlight the importance of performing more studies on subspecies of Crotalus oreganus and Crotalus viridis, since the old classification may have led to mixed results or mistaken data.

Medicinal electrochemistry: integration of electrochemistry, medicinal chemistry and computational chemistry.

Over the last centuries, there were many important discoveries in medicine that were crucial for gaining a better understanding of several physiological processes. Molecular modelling techniques are powerful tools that have been successfully used to analyse and interface medicinal chemistry studies with electrochemical experimental results. This special combination can help to comprehend medicinal chemistry problems, such as predicting biological activity and understanding drug action mechanisms. Electrochemistry has provided better comprehension of biological reactions and, as a result of many technological improvements, the combination of electrochemical techniques and biosensors has become an appealing choice for pharmaceutical and biomedical analyses. Therefore, this review will briefly outline the present scope and future advances related to the integration of electrochemical and medicinal chemistry approaches based on various applications from recent studies.

Molecular features related to the binding mode of PPARδ agonists from QSAR and docking analyses.

Diabetes affects approximately 4% of world's population and metabolic syndrome has been directly related to obesity. There is a class of nuclear receptors, peroxisome proliferator-activated receptors (PPARs), which controls the metabolism of carbohydrates and lipids. It has been considered an attractive target to treat diabetes and metabolic syndrome. Accordingly, the primary objective of this study was to employ molecular modelling techniques to understand the factors involved in PPARδ activation. The QSAR models obtained showed good internal and external consistency and presented good validation coefficients (QSAR: q(2) = 0.83, r(2) = 0.87; HQSAR: q(2) = 0.73, r(2) = 0.90; CoMFA: q(2) = 0.88, r(2) = 0.94). The selected properties and the contour maps described the possible interactions between the PPARδ receptor and its agonists. From these findings, it is possible to propose molecular modifications to design new compounds with improved biological properties.

Machine learning techniques and drug design.

The interest in the application of machine learning techniques (MLT) as drug design tools is growing in the last decades. The reason for this is related to the fact that the drug design is very complex and requires the use of hybrid techniques. A brief review of some MLT such as self-organizing maps, multilayer perceptron, bayesian neural networks, counter-propagation neural network and support vector machines is described in this paper. A comparison between the performance of the described methods and some classical statistical methods (such as partial least squares and multiple linear regression) shows that MLT have significant advantages. Nowadays, the number of studies in medicinal chemistry that employ these techniques has considerably increased, in particular the use of support vector machines. The state of the art and the future trends of MLT applications encompass the use of these techniques to construct more reliable QSAR models. The models obtained from MLT can be used in virtual screening studies as well as filters to develop/discovery new chemicals. An important challenge in the drug design field is the prediction of pharmacokinetic and toxicity properties, which can avoid failures in the clinical phases. Therefore, this review provides a critical point of view on the main MLT and shows their potential ability as a valuable tool in drug design.

A structure-activity relationship study of quinone compounds with trypanocidal activity.

A set of 25 quinone compounds with anti-trypanocidal activity was studied by using the density functional theory (DFT) method in order to calculate atomic and molecular properties to be correlated with the biological activity. The chemometric methods principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA), Kth nearest neighbor (KNN) and soft independent modeling of class analogy (SIMCA) were used to obtain possible relationships between the calculated descriptors and the biological activity studied and to predict the anti-trypanocidal activity of new quinone compounds from a prediction set. Four descriptors were responsible for the separation between the active and inactive compounds: T5 (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors give information on the kind of interaction that occurs between the compounds and the biological receptor. The prediction study was done with a set of three new compounds by using the PCA, HCA, SDA, KNN and SIMCA methods and two of them were predicted as active against the Trypanosoma cruzi.