Aedes aegypti is the main vector of dengue fever transmission, yellow fever, Zika, and chikungunya in tropical and subtropical regions and it is considered to cause health risks to millions of people in the world. In this study, we search to obtain new molecules with insecticidal potential against Ae. aegypti via virtual screening. Pyriproxyfen was chosen as a template compound to search molecules in the database Zinc_Natural_Stock (ZNSt) with structural similarity using ROCS (rapid overlay of chemical structures) and EON (electrostatic similarity) software, and in the final search, the top 100 were selected. Subsequently, in silico pharmacokinetic and toxicological properties were determined resulting in a total of 14 molecules, and these were submitted to the PASS online server for the prediction of biological insecticide and acetylcholinesterase activities, and only two selected molecules followed for the molecular docking study to evaluate the binding free energy and interaction mode. After these procedures were performed, toxicity risk assessment such as LD50 values in mg/kg and toxicity class using the PROTOX online server, were undertaken. Molecule ZINC00001624 presented potential for inhibition for the acetylcholinesterase enzyme (insect and human) with a binding affinity value of −10.5 and −10.3 kcal/mol, respectively. The interaction with the juvenile hormone was −11.4 kcal/mol for the molecule ZINC00001021. Molecules ZINC00001021 and ZINC00001624 had excellent predictions in all the steps of the study and may be indicated as the most promising molecules resulting from the virtual screening of new insecticidal agents.

Prostate cancer is one of the leading causes of disease and death on the planet. The probable bioactive pose of 16-((diisobutylamino)methyl)-6α-hydroxyvouacapane-7β,17β-lactone (N,N-DHL), a pivot compound with prostatic anti-cancer activity, was investigated via a semi-empirical method (PM3) and refined with the base set 6-31+G(d,p) calculated in the DFT method at the B3LYP level of theory. This structure was used in ligand-based virtual screening for five commercial compound bases using the software ROCS and EON that selected 2000 per base and another that resulted in 100 per base, respectively. This set was used for pharmacokinetic and toxicological predictions. The molecular overlap index at 50 % steric/electrostatic provided 68 structures that were used for a molecular docking study. The results showed that of 238,922 structures, only eight, 7 (-10.9 kcal mol-1) as the best in the series and 1 (-8.1 kcal mol-1) as less favorable, with others in this range (±2.8 kcal mol-1) with their respective binding affinity: 8 (-8.2 kcal mol-1), 5 (-8.2 kcal mol-1), 4 (-8.3 kcal mol-1), 2 (-8.5 kcal mol-1), 3 (-8.6 kcal mol-1) and 6 (-8.8 kcal mol-1) remaining in the final selection. The predictions for 21 pharmacokinetic properties were within the recommended range, similar to 95 % of the drugs available on the market, with no toxicity warning. The structures showed similarity greater than 75 % to the pivot based on binding affinity and predictions but only the structures 6 and 7 were considered more promising for their potential anti-prostate cancer activity (PC-3).

The DFT method has become a promising alternative in the support of traditional NMR experimental techniques, comparing experimental data with theoretical data, thereby achieving accurate and satisfactory results. In the present study, the experimental data of two diterpenes were compared to the theoretical data obtained by the GIAO method, applying DFT at the B3LYP/cc-pVDZ and B3PW91/DGDZVP levels to verify the degree of correlation, significance and predictability of the models obtained with the purpose of proving which of the computational methods is the most efficient for this class of substances. The theoretical NMR values obtained at B3LYP/cc-pVDZ were the more satisfactory, showing better linear correlations, presenting greater degrees of adjustments, significance and predictability compared to the B3PW91/DGDZVP method. Thus, these values were used to define H α and H β 1, 2, 3, 6 and 7 for diterpene 1 and 1, 2, 3, 6 and 7 for diterpene 2, which was not possible using experimental data. This showed that the quantum method used could help in the structural elucidation of natural products.