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.

In Silico Evaluation of Ibuprofen and Two Benzoylpropionic Acid Derivatives with Potential Anti-Inflammatory Activity.

Inflammation is a complex reaction involving cellular and molecular components and an unspecific response to a specific aggression. The use of scientific and technological innovations as a research tool combining multidisciplinary knowledge in informatics, biotechnology, chemistry and biology are essential for optimizing time and reducing costs in the drug design. Thus, the integration of these in silico techniques makes it possible to search for new anti-inflammatory drugs with better pharmacokinetic and toxicological profiles compared to commercially used drugs. This in silico study evaluated the anti-inflammatory potential of two benzoylpropionic acid derivatives (MBPA and DHBPA) using molecular docking and their thermodynamic profiles by molecular dynamics, in addition to predicting oral bioavailability, bioactivity and toxicity. In accordance to our predictions the derivatives proposed here had the potential capacity for COX-2 inhibition in the human and mice enzyme, due to containing similar interactions with the control compound (ibuprofen). Ibuprofen showed toxic predictions of hepatotoxicity (in human, mouse and rat; toxicophoric group 2-arylacetic or 3-arylpropionic acid) and irritation of the gastrointestinal tract (in human, mouse and rat; toxicophoric group alpha-substituted propionic acid or ester) confirming the literature data, as well as the efficiency of the DEREK 10.0.2 program. Moreover, the proposed compounds are predicted to have a good oral bioavailability profile and low toxicity (LD50 < 700 mg/kg) and safety when compared to the commercial compound. Therefore, future studies are necessary to confirm the anti-inflammatory potential of these compounds.

Alzheimer's Disease: A Review from the Pathophysiology to Diagnosis, New Perspectives for Pharmacological Treatment.

Dementia is characterized by the impairment of cognition and behavior of people over 65 years. Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder in the world, as approximately 47 million people are affected by this disease and the tendency is that this number will increase to 62% by 2030. Two microscopic features assist in the characterization of the disease, the amyloid plaques and neurofibrillary agglomerates. All these factors are responsible for the slow and gradual deterioration of memory that affect language, personality or cognitive control. For the AD diagnosis, neuropsychological tests are performed in different spheres of cognitive functions but since not all cognitive functions may be affected, cerebrospinal fluid biomarkers are used along with these tests. To date, cholinesterase inhibitors are used as treatment, they are the only drugs that have shown significant improvements in the cognitive functions of AD patients. Despite the proven effectiveness of cholinesterase inhibitors, an AD carrier, even while being treated, is continually subjected to progressive degeneration of the neuronal tissue. For this reason, other biochemical pathways associated with the pathophysiology of AD have been explored as alternatives to the treatment of this condition such as inhibition of ß-secretase and glycogen synthase kinase-3ß. The present study aims to conduct a review of the epidemiology, pathophysiology, symptoms, diagnosis and treatment of Alzheimer's disease, emphasizing the research and development of new therapeutic approaches.

Computational design of new protein kinase 2 inhibitors for the treatment of inflammatory diseases using QSAR, pharmacophore-structure-based virtual screening, and molecular dynamics.

Receptor-interacting protein kinase 2 (RIPK2) plays an essential role in autoimmune response and is suggested as a target for inflammatory diseases. A pharmacophore model was built from a dataset with ponatinib (template) and 18 RIPK2 inhibitors selected from BindingDB database. The pharmacophore model validation was performed by multiple linear regression (MLR). The statistical quality of the model was evaluated by the correlation coefficient (R), squared correlation coefficient (R2), explanatory variance (adjusted R2), standard error of estimate (SEE), and variance ratio (F). The best pharmacophore model has one aromatic group (LEU24 residue interaction) and two hydrogen bonding acceptor groups (MET98 and TYR97 residues interaction), having a score of 24.739 with 14 aligned inhibitors, which were used in virtual screening via ZincPharmer server and the ZINC database (selected in function of the RMSD value). We determined theoretical values of biological activity (logRA) by MLR, pharmacokinetic and toxicology properties, and made molecular docking studies comparing binding affinity (kcal/mol) results with the most active compound of the study (ponatinib) and WEHI-345. Nine compounds from the ZINC database show satisfactory results, yielding among those selected, the compound ZINC01540228, as the most promising RIPK2 inhibitor. After binding free energy calculations, the following molecular dynamics simulations showed that the receptor protein's backbone remained stable after the introduction of ligands.

Reverse Induced Fit-Driven MAS-Downstream Transduction: Looking for Metabotropic Agonists.

BACKGROUND: Protective effects of MAS activation have spurred clinical interests in developing MAS agonists. However, current bases that drive this process preclude that physiological concentrations of peptide MAS agonists induce an atypical signaling that does not reach the metabotropic efficacy of constitutive activation. Canonical activation of MAS-coupled G proteins is only achieved by supraphysiological concentrations of peptide MAS agonists or physiological concentrations of chemically modified analogues. These pleiotropic differences are because of two overlapped binding domains: one non-metabotropic site that recognizes peptide agonists and one metabotropic domain that recognizes modified analogues. OBJECTIVE: It is feasible that supraphysiological concentrations of peptide MAS agonists undergo to chemical modifications required for binding to metabotropic domain. Receptor oligomerization enhances pharmacological parameters coupled to metabotropic signaling. The formation of receptor-signalosome complex makes the transduction of agonists more adaptive. Considering the recent identification of MAS-signalosome, we aimed to postulate the reverse induced fit hypothesis in which MAS-signalosome would trigger chemical modifications required for agonists bind to MAS metabotropic domain. METHODS: Here we cover rational perspectives for developing novel metabotropic MAS agonists in the view of the reverse induced-fit hypothesis. RESULTS: Predicting a 3D model of MAS metabotropic domain may guide the screening of chemical modifications required for metabotropic efficacy. Pharmacophore-based virtual screening would select potential metabotropic MAS agonists from virtual libraries from human proteome. CONCLUSIONS: Rational perspectives that consider reverse induced fit hypothesis during MAS activation for developing metabotropic MAS agonists represents the best approach in providing MAS ligands with constitutive efficacy at physiological concentrations.