Identification of Potential New Aedes aegypti Juvenile Hormone Inhibitors from N-Acyl Piperidine Derivatives: A Bioinformatics Approach.

Aedes aegypti mosquitoes transmit several human pathogens that cause millions of deaths worldwide, mainly in Latin America. The indiscriminate use of insecticides has resulted in the development of species resistance to some such compounds. Piperidine, a natural alkaloid isolated from Piper nigrum, has been used as a hit compound due to its larvicidal activity against Aedes aegypti. In the present study, piperidine derivatives were studied through in silico methods: pharmacophoric evaluation (PharmaGist), pharmacophoric virtual screening (Pharmit), ADME/Tox prediction (Preadmet/Derek 10.0®), docking calculations (AutoDock 4.2) and molecular dynamics (MD) simulation on GROMACS-5.1.4. MP-416 and MP-073 molecules exhibiting ΔG binding (MMPBSA -265.95 ± 1.32 kJ/mol and -124.412 ± 1.08 kJ/mol, respectively) and comparable to holo (ΔG binding = -216.21 ± 0.97) and pyriproxyfen (a well-known larvicidal, ΔG binding= -435.95 ± 2.06 kJ/mol). Considering future in vivo assays, we elaborated the theoretical synthetic route and made predictions of the synthetic accessibility (SA) (SwissADME), lipophilicity and water solubility (SwissADME) of the promising compounds identified in the present study. Our in silico results show that MP-416 and MP-073 molecules could be potent insecticides against the Aedes aegypti mosquitoes.

Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches.

Non-steroidal anti-inflammatory drugs are inhibitors of cyclooxygenase-2 (COX-2) that were developed in order to avoid the side effects of non-selective inhibitors of COX-1. Thus, the present study aims to identify new selective chemical entities for the COX-2 enzyme via molecular modeling approaches. The best pharmacophore model was used to identify compounds within the ZINC database. The molecular properties were determined and selected with Pearson's correlation for the construction of quantitative structure-activity relationship (QSAR) models to predict the biological activities of the compounds obtained with virtual screening. The pharmacokinetic/toxicological profiles of the compounds were determined, as well as the binding modes through molecular docking compared to commercial compounds (rofecoxib and celecoxib). The QSAR analysis showed a fit with R = 0.9617, R2 = 0.9250, standard error of estimate (SEE) = 0.2238, and F = 46.2739, with the tetra-parametric regression model. After the analysis, only three promising inhibitors were selected, Z-964, Z-627, and Z-814, with their predicted pIC50 (-log IC50) values, Z-814 = 7.9484, Z-627 = 9.3458, and Z-964 = 9.5272. All candidates inhibitors complied with Lipinski's rule of five, which predicts a good oral availability and can be used in in vitro and in vivo tests in the zebrafish model in order to confirm the obtained in silico data.

Potential inhibitors of the enzyme acetylcholinesterase and juvenile hormone with insecticidal activity: study of the binding mode via docking and molecular dynamics simulations.

Models validation in QSAR, pharmacophore, docking and others can ensure the accuracy and reliability of future predictions in design and selection of molecules with biological activity. In this study, pyriproxyfen was used as a pivot/template to search the database of the Maybridge Database for potential inhibitors of the enzymes acetylcholinesterase and juvenile hormone as well. The initial virtual screening based on the 3D shape resulted in 2000 molecules with Tanimoto index ranging from 0.58 to 0.88. A new reclassification was performed on the overlapping of positive and negative charges, which resulted in 100 molecules with Tanimoto's electrostatic score ranging from 0.627 to 0.87. Using parameters related to absorption, distribution, metabolism and excretion and the pivot molecule, the molecules selected in the previous stage were evaluated regarding these criteria, and 21 were then selected. The pharmacokinetic and toxicological properties were considered and for 12 molecules, the DEREK software not fired any alert of toxicity, which were thus considered satisfactory for prediction of biological activity using the Web server PASS. In the molecular docking with insect acetylcholinesterase, the Maybridge3_002654 molecule had binding affinity of -11.1 kcal/mol, whereas in human acetylcholinesterase, the Maybridge4_001571molecule show in silico affinity of -10.2 kcal/mol, and in the juvenile hormone, the molecule MCULE-8839595892 show in silico affinity value of -11.6 kcal/mol. Subsequent long-trajectory molecular dynamics studies indicated considerable stability of the novel molecules compared to the controls.AbbreviationsQSARquantitative structure-activity relationshipsPASSprediction of activity spectra for substancesCommunicated by Ramaswamy H. Sarma.

Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening.

Leukemias are neoplasms that affect hematopoietic cells, which are developed by genetic alterations (mutations) that lead to the loss of proliferation control mechanisms (maturation and/or cell death). The α4ß1 integrin receptor is a therapeutic target for inflammation, autoimmune diseases and lymphoid tumors. This study was carried out to search through the antagonists-based virtual screening for α4ß1 receptor. Initially, seventeen (17) structures were selected (based on the inhibitory activity values, IC50) and the structure with the best value was chosen as the pivot. The pharmacophoric pattern was determined from the online PharmaGist server and resulted in a model of score value equal to 97.940 with 15 pharmacophoric characteristics that were statistically evaluated via Pearson correlations, principal component analysis (PCA) and hierarchical clustering analysis (HCA). A refined model generated four pharmacophoric hypotheses totaling 1.478 structures set of Zinc_database. After, the pharmacokinetic, toxicological and biological activity predictions were realized comparing with pivot structure that resulted in five (ZINC72088291, ZINC68842860, ZINC14365931, ZINC09588345 and ZINC91247798) structures with optimal in silico predictions. Therefore, future studies are needed to confirm antitumor potential activity of molecules selected this work with in vitro and in vivo assays.