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 New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach.

The cyclooxygenase-2 receptor is a therapeutic target for planning potential drugs with anti-inflammatory activity. The selective cyclooxygenase-2 (COX-2) inhibitor rofecoxib was selected as a pivot molecule to perform virtual ligand-based screening from six commercial databases. We performed the search for similarly shaped Rapid Overlay of Chemical Structures (ROCS) and electrostatic (EON) compounds. After, we used pharmacokinetic and toxicological parameters to determine the best potential compounds, obtained through the softwares QikProp and Derek, respectively. Then, the compounds proceeded to the molecular anchorage study, which showed promising results of binding affinity with the hCOX-2 receptor: LMQC72 (∆G = -11.0 kcal/mol), LMQC36 (∆G = -10.6 kcal/mol), and LMQC50 (∆G = -10.2 kcal/mol). LMQC72 and LMQC36 showed higher binding affinity compared to rofecoxib (∆G = -10.4 kcal/mol). Finally, molecular dynamics (MD) simulations were used to evaluate the interaction of the compounds with the target hCOX-2 during 150 ns. In all MD simulation trajectories, the ligands remained interacting with the protein until the end of the simulation. The compounds were also complexing with hCOX-2 favorably. The compounds obtained the following affinity energy values: rofecoxib: ΔGbind = -45.31 kcal/mol; LMQC72: ΔGbind = -38.58 kcal/mol; LMQC36: ΔGbind = -36.10 kcal/mol; and LMQC50: ΔGbind = -39.40 kcal/mol. The selected LMQC72, LMQC50, and LMQC36 structures showed satisfactory pharmacokinetic results related to absorption and distribution. The toxicological predictions of these compounds did not display alerts for possible toxic groups and lower risk of cardiotoxicity compared to rofecoxib. Therefore, future in vitro and in vivo studies are needed to confirm the anti-inflammatory potential of the compounds selected here with bioinformatics approaches based on rofecoxib ligand.

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.