Abstract: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 OPEN ACCESSMolecules 2014, 19 10671 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 S PRESS = ±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 (P CaCO2 ), cell permeability Maden Darby Canine Kidney (P MDCK ), 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.

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The peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that acts as a transcription factor, regulating glucose, lipid and inflammation signaling and it is exploited in type 2 diabetes treatment. However, the selective activation of this PPAR subtype has been linked to important adverse effects which can be mitigated through concomitant activation of PPARα and PPARδ. In this study, we proposed new PPARγ agonists using PharmaGist Server for pharmacophore prediction, the molecular docking was performed by GOLD (genetic optimization for ligand docking) v2.2, AutoDock 4.2 and AutoDock Vina 1.1 and QikProp v4.0 and Derek for absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment. One molecule showed high predicted affinity to PPARγ and favorable pharmacokinetic and toxicity properties. It was then evaluated against PPARα and PPARδ and showed greater affinity to these receptors than the controls. Therefore this molecule is a promising drug lead for the development of derivatives and for the treatment of metabolic syndrome with the benefits of a PPAR pan activation.Keywords: type 2 diabetes, PPAR pan agonist, molecular modeling, ADMET prediction IntroductionThe general cause of mortality among type 2 diabetes mellitus patients is due to dyslipidemia leading to cardiovascular complications. Currently, the drugs used to control these disorders act separately either on reducing blood glucose or lowering triglyceride levels, free fatty acid and low-density lipoprotein. However, the increasing number of cases of patients with diabetic metabolic syndrome requires the development of therapies that act simultaneously reducing glicidic and lipidic levels in a combined effort to ease cardiovascular disorders. 1 Peroxisome proliferatoractivated receptors (PPARs) are nuclear receptors that act as transcription factors, regulating glucose homeostasis, lipid metabolism and inflammation signaling, making them attractive targets for the development of new therapies for metabolic syndromes. They regulate the expression of target genes after forming a heterodimer with 9-cis-retinoic acid receptor (RXR) and bind to the peroxisome proliferators response elements (PPRE) in the regulatory region of the target gene. The increased transcriptional rates of their target genes may be increased after interaction with an agonist ligand which alters the conformation of PPAR, exposing the DNA (deoxyribonucleic acid) binding site. Three distinct receptors have already been described, PPARα, PPARδ and PPARγ. 2 Padilha et al. 1637 Vol. 27, No. 9, 2016 PPARγ plays an important role in the regulation of glucose and lipid metabolism and it is widely distributed in adipose tissue. 3,4 In adipocytes, the PPARγ activity regulates the expression of genes involved in lipid metabolism, 5-7 in addition to the control of the expression of proteins involved in the uptake of lipids by adipocytes. 8 The PPARγ activation in adipose tissue presents an indirect activity in tissues which respond to insulin. 9 This e...

The central importance of quantum chemistry is to obtain solutions of the Schrödinger equation for the accurate determination of the properties of atomic and molecular systems that occurred from the calculation of wave functions accurate for many diatomic and polyatomic molecules, using Self Consistent Field method (SCF). The application of quantum chemical methods in the study and planning of bioactive compounds has become a common practice nowadays. From the point of view of planning it is important to note, when it comes to the use of molecular modeling, a collective term that refers to methods and theoretical modeling and computational techniques to mimic the behavior of molecules, not intend to reach a bioactive molecule simply through the use of computer programs. The choice of method for energy minimization depends on factors related to the size of the molecule, parameters of availability, stored data and computational resources. Molecular models generated by the computer are the result of mathematical equations that estimate the positions and properties of the electrons and nuclei, the calculations exploit experimentally, the characteristics of a structure, providing a new perspective on the molecule. In this work we show that studies of