N-aryltetrahydroisoquinoline derivatives as HA-CD44 interaction inhibitors: Design, synthesis, computational studies, and antitumor effect.

Hyaluronic acid (HA) plays a crucial role in tumor growth and invasion through its interaction with cluster of differentiation 44 (CD44), a non-kinase transmembrane glycoprotein, among other hyaladherins. CD44 expression is elevated in many solid tumors, and its interaction with HA is associated with cancer and angiogenesis. Despite efforts to inhibit HA-CD44 interaction, there has been limited progress in the development of small molecule inhibitors. As a contribution to this endeavour, we designed and synthesized a series of N-aryltetrahydroisoquinoline derivatives based on existing crystallographic data available for CD44 and HA. Hit 2e was identified within these structures for its antiproliferative effect against two CD44+ cancer cell lines, and two new analogs (5 and 6) were then synthesized and evaluated as CD44-HA inhibitors by applying computational and cell-based CD44 binding studies. Compound 2-(3,4,5-trimethoxybenzyl)-1,2,3,4-tetrahydroisoquinolin-5-ol (5) has an EC50 value of 0.59 µM against MDA-MB-231 cells and is effective to disrupt the integrity of cancer spheroids and reduce the viability of MDA-MB-231 cells in a dose-dependent manner. These results suggest lead 5 as a promising candidate for further investigation in cancer treatment.

Galantamine Based Novel Acetylcholinesterase Enzyme Inhibitors: A Molecular Modeling Design Approach.

Acetylcholinesterase (AChE) enzymes play an essential role in the development of Alzheimer's disease (AD). Its excessive activity causes several neuronal problems, particularly psychopathies and neuronal cell death. A bioactive pose on the hAChE B site of the human acetylcholinesterase (hAChE) enzyme employed in this investigation, which was obtained from the Protein Data Bank (PDB ID 4EY6), allowed for the prediction of the binding affinity and free binding energy between the protein and the ligand. Virtual screening was performed to obtain structures similar to Galantamine (GNT) with potential hAChE activity. The top 200 hit compounds were prioritized through the use of filters in ZincPharmer, with special features related to the pharmacophore. Critical analyses were carried out, such as hierarchical clustering analysis (HCA), ADME/Tox predictions, molecular docking, molecular simulation studies, synthetic accessibility (SA), lipophilicity, water solubility, and hot spots to confirm the stable binding of the two promising molecules (ZINC16951574-LMQC2, and ZINC08342556-LMQC5). The metabolism prediction, with metabolites M3-2, which is formed by Glutathionation reaction (Phase II), M1-2, and M2-2 formed from the reaction of S-oxidation and Aliphatic hydroxylation (Phase I), were both reactive but with no side effects. Theoretical synthetic routes and prediction of synthetic accessibility for the most promising compounds are also proposed. In conclusion, this study shows that in silico modeling can be used to create new drug candidate inhibitors for hAChE. The compounds ZINC16951574-LMQC2, and ZINC08342556-LMQC5 are particularly promising for oral administration because they have a favorable drug-likeness profile, excellent lipid solubility, high bioavailability, and adequate pharmacokinetics.

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 Insect Growth Inhibitor against Aedes aegypti: A Bioinformatics Approach.

Aedes aegypti is the main vector that transmits viral diseases such as dengue, hemorrhagic dengue, urban yellow fever, zika, and chikungunya. Worldwide, many cases of dengue have been reported in recent years, showing significant growth. The best way to manage diseases transmitted by Aedes aegypti is to control the vector with insecticides, which have already been shown to be toxic to humans; moreover, insects have developed resistance. Thus, the development of new insecticides is considered an emergency. One way to achieve this goal is to apply computational methods based on ligands and target information. In this study, sixteen compounds with acceptable insecticidal activities, with 100% larvicidal activity at low concentrations (2.0 to 0.001 mg·L−1), were selected from the literature. These compounds were used to build up and validate pharmacophore models. Pharmacophore model 6 (AUC = 0.78; BEDROC = 0.6) was used to filter 4793 compounds from the subset of lead-like compounds from the ZINC database; 4142 compounds (dG < 0 kcal/mol) were then aligned to the active site of the juvenile hormone receptor Aedes aegypti (PDB: 5V13), 2240 compounds (LE < −0.40 kcal/mol) were prioritized for molecular docking from the construction of a chitin deacetylase model of Aedes aegypti by the homology modeling of the Bombyx mori species (PDB: 5ZNT), which aligned 1959 compounds (dG < 0 kcal/mol), and 20 compounds (LE < −0.4 kcal/mol) were predicted for pharmacokinetic and toxicological prediction in silico (Preadmet, SwissADMET, and eMolTox programs). Finally, the theoretical routes of compounds M01, M02, M03, M04, and M05 were proposed. Compounds M01−M05 were selected, showing significant differences in pharmacokinetic and toxicological parameters in relation to positive controls and interaction with catalytic residues among key protein sites reported in the literature. For this reason, the molecules investigated here are dual inhibitors of the enzymes chitin synthase and juvenile hormonal protein from insects and humans, characterizing them as potential insecticides against the Aedes aegypti mosquito.

Selective Anticancer Therapy Based on a HA-CD44 Interaction Inhibitor Loaded on Polymeric Nanoparticles.

Hyaluronic acid (HA), through its interactions with the cluster of differentiation 44 (CD44), acts as a potent modulator of the tumor microenvironment, creating a wide range of extracellular stimuli for tumor growth, angiogenesis, invasion, and metastasis. An innovative antitumor treatment strategy based on the development of a nanodevice for selective release of an inhibitor of the HA-CD44 interaction is presented. Computational analysis was performed to evaluate the interaction of the designed tetrahydroisoquinoline-ketone derivative (JE22) with CD44 binding site. Cell viability, efficiency, and selectivity of drug release under acidic conditions together with CD44 binding capacity, effect on cell migration, and apoptotic activity were successfully evaluated. Remarkably, the conjugation of this CD44 inhibitor to the nanodevice generated a reduction of the dosis required to achieve a significant therapeutic effect.

Identification of novel potential cyclooxygenase-2 inhibitors using ligand- and structure-based virtual screening approaches.

Cyclooxygenase 2 (COX-2) is a well-established target for the design of anti-inflammatory intermediates. Celecoxib was selected as a template molecule to perform ligand-based virtual screening, i.e. to search for structures with similarity in shape and electrostatic potential, with a gradual increase in accuracy through the combined fitting of several steps using eight commercial databases. The molecules ZINC408709 and ZINC2090319 reproduced values within the limits established in an initial study of absorption and distribution in the body. No alert was fired for possible toxic groups when these molecules were subjected to toxicity prediction. Molecular docking results with these compounds showed a higher binding affinity in comparison to rofecoxib for the COX-2 target. Additionally, ZINC408709 and ZINC2090319 were predicted to be potentially biologically active. In in silico prediction of endocrine disruption potential, it was established that the molecule ZINC2090319 binds strongly to the target related to cardiovascular risk in a desirable way as a non-steroidal antagonist and ZINC408709 binds strongly to the target that is associated with the treatment of inflammatory pathologies and similar to celecoxib. Metabolites generated from these compounds are less likely to have side effects. Simulations were used to evaluate the interaction of compounds with COX-1 and COX-2 during 200 ns. Despite the differences, ZINC408709 molecule showed better stability for COX-2 during molecular dynamics simulation. In the calculations of free energy MM/PBSA, the molecule ZINC408709 ΔGbind value has a higher affinity to celecoxib and rofecoxib COX-2. This demonstrates that the selected substances can be considered as promising COX-2 inhibitors. Communicated by Ramaswamy H. Sarma.

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.