Putative mechanism of a multivitamin treatment against insulin resistance.

Insulin resistance is caused by the abnormal secretion of proinflammatory cytokines in adipose tissue, which is induced by an increase in lipid accumulation in adipocytes, hepatocytes, and myocytes. The inflammatory pathway involves multiple targets such as nuclear factor kappa B, inhibitor of nuclear factor κ-B kinase, and mitogen-activated protein kinase. Vitamins are micronutrients with anti-inflammatory activities that have unclear mechanisms. The present study aimed to describe the putative mechanisms of vitamins involved in the inflammatory pathway of insulin resistance. The strategy to achieve this goal was to integrate data mining and analysis, target prediction, and molecular docking simulation calculations to support our hypotheses. Our results suggest that the multitarget activity of vitamins A, B1, B2, B3, B5, B6, B7, B12, C, D3, and E inhibits nuclear factor kappa B and mitogen-activated protein kinase, in addition to vitamins A and B12 against inhibitor of nuclear factor κ-B kinase. The findings of this study highlight the pharmacological potential of using an anti-inflammatory and multitarget treatment based on vitamins and open new perspectives to evaluate the inhibitory activity of vitamins against nuclear factor kappa B, mitogen-activated protein kinase, and inhibitor of nuclear factor κ-B kinase in an insulin-resistant context.

Ivermectin as an inhibitor of cancer stem­like cells.

The aim of the present study was to demonstrate that ivermectin preferentially inhibited cancer stem­like cells (CSC) in breast cancer cells and downregulated the expression of 'stemness' genes. Computational searching of DrugBank, a database of approved drugs, was performed using the principles of two­dimensional similarity searching; the chemical structure of salinomycin was used as a query. Growth inhibition of the breast cancer cell lin e MDA­MB­231 by ivermectin was investigated in the total cell population, in cell spheroids and in sorted cells that expressed cluster of differentiation (CD)44+/CD24­. The effects of ivermectin treatment on the expression of pluripotency and self­renewal transcription factors, such as homeobox protein nanog (nanog), octamer­binding protein 4 (oct­4) and SRY­box 2 (sox­2), were evaluated by reverse transcription­quantitative polymerase chain reaction and western blotting. Ivermectin exhibited a similarity value of 0.78 in reference to salinomycin. Ivermectin demonstrated an inhibitory effect upon the growth of MDA­MB­231 cells in the range of 0.2­8 µM. Ivermectin preferentially inhibits the viability of CSC­enriched populations (CD44+/CD24­ and cells growing in spheroids) compared with the total cell population. The opposite pattern was observed with paclitaxel treatment. Ivermectin exposure reduced the expression of nanog, oct­4 and sox­2 at the mRNA and protein levels. Ivermectin preferentially inhibited the CSC subpopulation in the MDA­MB­231 cells and downregulated the expression of genes involved in the maintenance of pluripotency and self­renewal.

Insights into the structure and inhibition of Giardia intestinalis arginine deiminase: homology modeling, docking, and molecular dynamics studies.

Giardia intestinalis arginine deiminase (GiADI) is an important metabolic enzyme involved in the energy production and defense of this protozoan parasite. The lack of this enzyme in the human host makes GiADI an attractive target for drug design against G. intestinalis. One approach in the design of inhibitors of GiADI could be computer-assisted studies of its crystal structure, such as docking; however, the required crystallographic structure of the enzyme still remains unresolved. Because of its relevance, in this work, we present a three-dimensional structure of GiADI obtained from its amino acid sequence using the homology modeling approximation. Furthermore, we present an approximation of the most stable dimeric structure of GiADI identified through molecular dynamics simulation studies. An in silico analysis of druggability using the structure of GiADI was carried out in order to know if it is a good target for design and optimization of selective inhibitors. Potential GiADI inhibitors were identified by docking of a set of 3196 commercial and 19 in-house benzimidazole derivatives, and molecular dynamics simulation studies were used to evaluate the stability of the ligand-enzyme complexes.

Ribavirin as a tri-targeted antitumor repositioned drug.

The aim of the present study was to demonstrate that ribavirin, a known inhibitor of eIF4E and inosine 5'-phosphate dehydrogenase (IMPDH), also inhibits histone methyltransferase zeste homolog 2 (EZH2). A computational searching revealed that ribavirin has a high structural similarity to 3-deazaneplanocin A (DZNep). The growth inhibitory effects of ribavirin as well as its effects upon epigenetic enzymes were evaluated in various cancer cell lines. siRNA assays were used to downregulate eIF4E, EZH2 and IMPDH to determine the contribution of these targets to the growth inhibitory effects of ribavirin. Ribavirin decreased EZH2 expression, inhibited histone methyltransferase activity and decreased H3K27 trimethylation. Ribavirin induced variable growth inhibition in a number of cell lines and downregulation of the targets, EZH2, eIF4E and IMPDH1 and 2 by siRNA led to comparable growth inhibition while no significant further reduction in viability was observed when siRNA transfected cells were treated with ribavirin. The results showed that ribavirin inhibits these cancer targets and should thus be studied for cancer therapy.

Towards the chemoinformatic-based identification of DNA methyltransferase inhibitors: 2D- and 3D-similarity profile of screening libraries.

DNA methyltransferases (DNMTs) are emerging targets for the treatment of cancer and other diseases. The quinolone-based compound, SGI-1027, is a promising inhibitor of DNMT1 with a distinct mode of action and it is an attractive starting point for further research. Several experimental and computational approaches can be used to further develop novel DNMT1 inhibitors based on SGI-1027. In this work, we used a chemoinformatic-based approach to explore the potential to identify novel inhibitors in large screening collections of natural products and synthetic commercial libraries. Using the principles of similarity searching, the similarity profile to the active reference compound SGI-1027 was computed for four different screening libraries using a total of 22 two- and three- dimensional representations and two similarity metrics. The compound library with the overall highest similarity profile to the probe molecule was identified as the most promising collection for experimental testing. Individual compounds with high similarity to the reference were also selected as suitable candidates for experimental validation. During the course of this work, the 22 two- and three- dimensional representations were compared to each other and classified based on the similarity values computed with the reference compound. This classification is valuable to select structure representations for similarity searching of any other screening library. This work represents a step forward to further advance epigenetic therapies using computational approaches.

Synthesis, in vitro and computational studies of protein tyrosine phosphatase 1B inhibition of a small library of 2-arylsulfonylaminobenzothiazoles with antihyperglycemic activity.

The 2-arylsulfonylaminobenzothiazole derivatives 1-27 were prepared using a one step reaction. The in vitro inhibitory activity of the compounds against protein tyrosine phosphatase 1B (PTP-1B) was evaluated. Compounds 4 and 16 are rapid reversible (mixed-type) inhibitors of PTP-1B with IC(50) values in the low micromolar range. The most active compounds (4 and 16) were docked into the crystal structure of PTP-1B. Docking results indicate potential hydrogen bond interactions between the nitro group in both compounds and the catalytic amino acid residues Arg 221 and Ser 216. Both compounds were evaluated for their in vivo antihyperglycemic activity in a type 2 diabetes mellitus rat model, showing significant lowering of plasma glucose concentration, during the 7h post-intragastric administration.

The prince and the pauper. A tale of anticancer targeted agents.

Cancer rates are set to increase at an alarming rate, from 10 million new cases globally in 2000 to 15 million in 2020. Regarding the pharmacological treatment of cancer, we currently are in the interphase of two treatment eras. The so-called pregenomic therapy which names the traditional cancer drugs, mainly cytotoxic drug types, and post-genomic era-type drugs referring to rationally-based designed. Although there are successful examples of this newer drug discovery approach, most target-specific agents only provide small gains in symptom control and/or survival, whereas others have consistently failed in the clinical testing. There is however, a characteristic shared by these agents: -their high cost-. This is expected as drug discovery and development is generally carried out within the commercial rather than the academic realm. Given the extraordinarily high therapeutic drug discovery-associated costs and risks, it is highly unlikely that any single public-sector research group will see a novel chemical "probe" become a "drug". An alternative drug development strategy is the exploitation of established drugs that have already been approved for treatment of non-cancerous diseases and whose cancer target has already been discovered. This strategy is also denominated drug repositioning, drug repurposing, or indication switch. Although traditionally development of these drugs was unlikely to be pursued by Big Pharma due to their limited commercial value, biopharmaceutical companies attempting to increase productivity at present are pursuing drug repositioning. More and more companies are scanning the existing pharmacopoeia for repositioning candidates, and the number of repositioning success stories is increasing. Here we provide noteworthy examples of known drugs whose potential anticancer activities have been highlighted, to encourage further research on these known drugs as a means to foster their translation into clinical trials utilizing the more limited public-sector resources. If these drug types eventually result in being effective, it follows that they could be much more affordable for patients with cancer; therefore, their contribution in terms of reducing cancer mortality at the global level would be greater.

Antidiabetic activity of N-(6-substituted-1,3-benzothiazol-2-yl)benzenesulfonamides.

N-(6-Substituted-1,3-benzothiazol-2-yl)benzenesulfonamide derivatives 1-8 were synthesized and evaluated for their in vivo antidiabetic activity in a non-insulin-dependent diabetes mellitus rat model. Several compounds synthesized showed significant lowering of plasma glucose level in this model. As a possible mode of action, the compounds were in vitro evaluated as 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) inhibitors. The most active compounds (3 and 4) were docked into the crystal structure of 11beta-HSD1. Docking results indicate potential hydrogen bond interactions with catalytic amino acid residues.

Large compound databases for structure-activity relationships studies in drug discovery.

Large libraries of chemical compounds reflect the exponentially growing data-enrichment in drug discovery that trends towards fully automated informatics solutions to study structure - activity relationships by screening docked ligand candidates to biological target structures. We review otherwise disseminated user descriptions of mainly public databases with free access and also our integrated data mining tool GPDBnet for phyto-pharmacology.

Single nucleotide polymorphisms in the promoter region of the E-cadherin gene in gastric cancer: case-control study in a young Mexican population.

BACKGROUND: Gastric cancer has a tendency to present at early age in the Mexican population, and it is frequently associated with a family history. A polymorphism at position -160 at the CDH1 promoter region has been reported to lead to transcriptional downregulation of the gene in vitro, with possible increase in the risk of gastric cancer. We evaluated the role of the -160A allele in the risk of gastric cancer in a young Mexican population. METHODS: Peripheral blood sample of Mexican patients younger than 45 years old with diagnosis of diffuse gastric cancer were obtained. We performed DNA extraction and analyzed the frequencies of -160 promoter polymorphism of E-cadherin gene by polymerase chain reaction-single strand conformational polymorphism. These frequencies were compared with those of healthy controls. The chi2 test for association was used to test differences of the genotype frequencies between normal controls and patients with gastric cancer. Findings were considered significant at P < .05. RESULTS: The frequency of the -160 A allele was significantly higher (P = .002) in 39 patients with diffuse gastric cancer compared with 78 matched controls. The odds ratio associated with the A-allele was 1.98 for C/A heterozygotes (95% CI 1.01-3.98) and 6.5 for A/A homozygotes (95% CI 2.1-19.6). We found an increased risk of diffuse gastric cancer according to family history, independent of the expression of the polymorphism. CONCLUSIONS: The -160 C/A polymorphism of the E-cadherin has a direct effect on the risk of diffuse gastric cancer at young age in Mexican population.

Molecular modeling of some 1H-benzimidazole derivatives with biological activity against Entamoeba histolytica: a comparative molecular field analysis study.

Comparative molecular field analysis (CoMFA) was performed on a set of 1H-benzimidazole derivatives. Molecular modeling and 3D-QSAR were employed to determine the tautomeric form that would probably fit a target receptor in Entamoeba histolytica. CoMFA results suggest that the antiamoebic activity is favored with steric bulk at position 5 of the benzimidazole ring and low electron density on the group at position 2. To the best of our knowledge this is the first 3D-QSAR study performed for benzimidazoles as antiamoebic agents. The CoMFA models derived will be very valuable to design new and more potent compounds against E. histolytica.

Hierarchical strategy for identifying active chemotype classes in compound databases.

A general methodology is presented for analyzing patterns of activity in compound databases, which is based on the use of structural chemotypes and provides a focused, hierarchical classification of active compounds. Each node in the hierarchical tree corresponds to a specific chemotype and is labeled by a unique code or identifier. All chemotypes at a given level of the hierarchy define equivalence classes, and those of higher structural resolution have a strict parent-child (i.e. subset) relationship to those of lower resolution. Active chemotypes contain a relatively high proportion of actives and are characterized through the use of enrichment plots. These plots show the relationship of occupancy to activity enrichment for a set of chemotypes at a given level of structural resolution. Paths through the hierarchy from chemotypes of lower to those of higher structural resolution (e.g. reduced cyclic system skeletons --> cyclic system skeletons --> cyclic systems --> complete molecules) are unique. Unique paths in the hierarchy that only pass through active chemotypes are called chains or paths of actives. These chains provide links for identifying structurally related active compounds at increasing levels of structural resolution. Analysis of actives can also be carried out at any specific level of structural resolution deemed appropriate by the investigator. Chemotype codes can be used to search compound databases for new molecules possessing these codes or sets of hierarchically related codes. An example, based on the NCI AIDS database, is presented that illustrates the general approach and provides a more detailed description of several interesting classes of active chemotypes and their inter-relationships.

Quantitative structure-activity relationship analysis of pyridinone HIV-1 reverse transcriptase inhibitors using the k nearest neighbor method and QSAR-based database mining.

We have developed quantitative structure-activity relationship (QSAR) models for 44 non-nucleoside HIV-1 reverse transcriptase inhibitors (NNRTIs) of the pyridinone derivative type. The k nearest neighbor (kNN) variable selection approach was used. This method utilizes multiple descriptors such as molecular connectivity indices, which are derived from two-dimensional molecular topology. The modeling process entailed extensive validation including the randomization of the target property (Y-randomization) test and the division of the dataset into multiple training and test sets to establish the external predictive power of the training set models. QSAR models with high internal and external accuracy were generated, with leave-one-out cross-validated R2 (q2) values ranging between 0.5 and 0.8 for the training sets and R2 values exceeding 0.6 for the test sets. The best models with the highest internal and external predictive power were used to search the National Cancer Institute database. Derivatives of the pyrazolo[3,4-d]pyrimidine and phenothiazine type were identified as promising novel NNRTIs leads. Several candidates were docked into the binding pocket of nevirapine with the AutoDock (version 3.0) software. Docking results suggested that these types of compounds could be binding in the NNRTI binding site in a similar mode to a known non-nucleoside inhibitor nevirapine.

Molecular docking of the highly hypolipidemic agent alpha-asarone with the catalytic portion of HMG-CoA reductase.

Docking experiments using a number of published crystal structures of HMG-CoA reductase with the potent hypocholesterolemic agent alpha-asarone are described. The results indicate that alpha-asarone binds in the enzyme's active site. The methoxy groups play a key role in the binding and probably also in its biological activity, as shown by extensive SAR studies reported for analogues of alpha-asarone. The docking results will be valuable for the structure-based design of novel hypolipidemic agents.

Flexible docking of pyridinone derivatives into the non-nucleoside inhibitor binding site of HIV-1 reverse transcriptase.

Potent non-nucleoside reverse transcriptase inhibitors (NNRTIs) of the pyridinone derivative type were docked into nine NNRTIs binding pockets of HIV-1 reverse transcriptase (RT) structures. The docking results indicate that pyridinone analogues adopt a butterfly conformation and share the same binding mode as the crystal inhibitors in the pocket geometries of nevirapine, 1051U91, 9-Cl-TIBO, Cl-alpha-APA, efavirenz, UC-781, and S-1153. The results are in agreement with the data concerning mutational and structure-activity relationships available for pyridinone analogues and aid in the understanding, at the molecular level, of the biological response of published hybrid pyridinone molecules. Strategies to design further pyridinone derivatives active against RT containing mutations are discussed.