Novel chalcones derivatives with potential antineoplastic activity investigated by docking and molecular dynamics simulations.

Glioblastoma is an aggressive primary tumor of the central nervous system (CNS). Is the most aggressive among infiltrative gliomas arising from the CNS. This tumor has low patient survival rate and several studies aiming at developing new drugs have increased. Patients with this cancer type face significant morbidity and mortality. This study evaluated the antineoplastic activity of synthetic chalcones (3a-3f) using in vitro glioblastoma models and molecular modeling. Cytotoxicity assay showed that Astrocitoma Hospital Ofir Loyola No 1 (AHOL1) and Uppsala 87 neoplastic glioblastoma lines (U87) cellular viability were significantly reduced compared to Healthy human fibroblasts cell lines (AN27) when exposed to chalcones. Interaction with the serine amino acid was present in the most promising and the reference binder docking, suggesting its importance inhibiting cell growth. Comparative analysis between the reference ligands and the molecules showed that the amino acid LYS352 present in all fittings, suggesting that this is the main amino acid for interaction with tubulin and are consistent with those in cytotoxicity assay, suggesting antineoplastic potential in glioblastoma. Long trajectory molecular dynamics studies were also carried out in order to investigate stability and conformations amongst the chalcones bound tubulin as well, in comparison to doxorubicin (here used as control), however future studies are needed to further assess the mechanism of inhibition of chalcones used in this investigation.Communicated by Ramaswamy H. Sarma.

Revisiting the Proposition of Binding Pockets and Bioactive Poses for GSK-3ß Allosteric Modulators Addressed to Neurodegenerative Diseases.

Glycogen synthase kinase-3 beta (GSK-3ß) is an enzyme pertinently linked to neurodegenerative diseases since it is associated with the regulation of key neuropathological features in the central nervous system. Among the different kinds of inhibitors of this kinase, the allosteric ones stand out due to their selective and subtle modulation, lowering the chance of producing side effects. The mechanism of GSK-3ß allosteric modulators may be considered still vague in terms of elucidating a well-defined binding pocket and a bioactive pose for them. In this context, we propose to reinvestigate and reinforce such knowledge by the application of an extensive set of in silico methodologies, such as cavity detection, ligand 3D shape analysis and docking (with robust validation of corresponding protocols), and molecular dynamics. The results here obtained were consensually consistent in furnishing new structural data, in particular by providing a solid bioactive pose of one of the most representative GSK-3ß allosteric modulators. We further applied this to the prospect for new compounds by ligand-based virtual screening and analyzed the potential of the two obtained virtual hits by quantum chemical calculations. All potential hits achieved will be subsequently tested by in vitro assays in order to validate our approaches as well as to unveil novel chemical entities as GSK-3ß allosteric modulators.

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.

Pharmacophore and structure-based drug design, molecular dynamics and admet/tox studies to design novel potential pad4 inhibitors.

We have used docking (GLIDE), pharmacophore modeling (Discovery Studio), long trajectory molecular dynamics (Discovery Studio) and ADMET/Tox (QikProp and DEREK) to investigate PAD4 in order to determine potential novel inhibitors and hits. We have carried out virtual screening in the ZINC natural compounds database. Pharmacokinetics and Toxicity of the best hits were assessed using databases implemented in softwares that create models based on chemical structures taking into account consideration about the toxicophoric groups. A wide variety of pharmaceutical relevant properties are determined in order to make decisions about molecular suitability. After screening and analysis, the 6 most promising PAD4 inhibitors are suggested, with strong interactions (pi-stacking, hydrogen bonds, hydrophobic contacts) and suitable pharmacotherapeutic profile as well.

Molecular modeling and statistical analysis in the design of derivatives of human dipeptidyl peptidase IV.

Human dipeptidyl peptidase IV (hDDP-IV) has a considerable importance in inactivation of glucagon-like peptide-1, which is related to type 2 diabetes. One approach for the treatment is the development of small hDDP-IV inhibitors. In order to design better inhibitors, we analyzed 5-(aminomethyl)-6-(2,4-dichlrophenyl)-2-(3,5-dimethoxyphenyl)pyrimidin-4-amine and a set of 24 molecules found in the BindingDB web database for model designing. The analysis of their molecular properties allowed the design of a multiple linear regression model for activity prediction. Their docking analysis allowed visualization of the interactions between the pharmacophore regions and hDDP-IV. After both analyses were performed, we proposed a set of nine molecules in order to predict their activity. Four of them displayed promising activity, and thus, had their docking performed, as well as, the pharmacokinetic and toxicological study. Two compounds from the proposed set showed suitable pharmacokinetic and toxicological characteristics, and therefore, they were considered promising for future synthesis and in vitro studies.