Current Topics in Medicinal Chemistry - Volume 17, Issue 26, 2017

This review discusses the substantial cyclopentenyl fatty acid class of naturally occurring lipids. These compounds are historically important and have recently been shown to exhibit remarkable biological activity relevant to producing new antibiotic agents. Information about the history of cyclopentenyl fatty acids, their use in traditional and modern medicine, as well as biological activity, and methods for their synthesis are given.

Prostate cancer is the most common male cancer in the world. The diagnosis, staging, prognosis and monitoring are usually done with Prostate Specific Antigen (PSA). Biosensors are emerging as a novel analytical technology for PSA detection. They provide several advantages for clinical applications and will benefit clinicians, patients and forensic workers in the future. Among them, electrochemical immunosensors have gained growing interests. Hence, their sensitivity is often improved by modifying them with nanoparticles especially iron oxide (IONP). Functionalized IONP attracted much attention in the fabrication of biosensing systems, due to their multiple properties, such as biocompatibility and signal amplification, and their ability to bind covalently to antibodies via their functional groups. In the present study, two electrochemical immunosensors were investigated for PSA detection. The first one was functionalized with 3- glycidoxypropyltrimethoxysilane self-assembled monolayer, while the second one was based on iron oxide nanoparticles functionalized with 3-aminopropyltriethoxysilane. Square wave voltammetry (SWV) has been investigated to follow-up the PSA detection in a phosphate buffer solution, in an artificial serum and in a human serum. The limit of detection (LOD) of both immunosensors was found of order of 10 fg/ml. When estimated in human serum this value increases up to 50 pg/ml.

Cissampelos sympodialis Eichl is used in folk medicine for the treatment of various inflammatory diseases; several alkaloids have been isolated from this species and some of them have anti-allergic, immunomodulatory and spasmolytic activities. Treatment of rats with the total tertiary alkaloid fraction showed an antidepressant effect. One of the depression causes can be the deficiency of monoamines, which is a factor displayed in patients with Alzheimer's disease. Theoretical studies using in silico methods have aided in the process of drug discovery. From this perspective, we applied ligand-based-virtual associated with structure-based-virtual screening of alkaloids from C. sympodialis Eichl and 101 derivatives proposed by us are promising leads against some important targets (BACE, GSK-3μ and MAO-A). From the ChEMBL database, we selected a diverse set of 724, 1898 and 1934 structures, which had been tested against BACE, GSK-3μ and MAO-A, to create Random Forest (RF) models with good overall prediction rate, over 78%, for cross-validation and test set. Compounds 24 and 47 presented activity against GSK-3β and MAO-A simultaneously. The natural alkaloids roraimine and simpodialine-μ-N-oxide presented activity against BACE and liriodenine against MAO-A. The top 20 compounds with best docking performance per enzyme were selected and validated through the RF model. All 9 compounds classified as active in RF model for BACE are bisbenzylisoquinoline alkaloids and were present in the top docking scoring, demonstrating a consensus on results. Affinities of bisbenzylisoquinoline alkaloids, including two secondary metabolites (roraimine and simpodialine-μ-N-oxide), with BACE suggest that this skeleton can be used as a model to design new antagonists of this enzyme.

Inflammation is a complex phenomenon necessary in human defense mechanisms but also involved in the development of some human diseases. The discovery of cyclooxygenase-2 (COX- 2) improved the pharmacology of nonsteroidal anti-inflammatory drugs (NSAID) giving a clear mechanism for prostaglandin regulation in vivo and providing a new target for the development of COX-2-selective drugs without gastrointestinal side-effects. Keeping in view the importance of this pharmacological class, several literature reports have underlined the impact of these antiinflammatory compounds in therapeutics. The present review considers the most recently published literature concerning COX-2 inhibitors until 2016. Through a wide chemical classification, the last developments concerning this therapeutic family by highlighting structure-activity relationships insights and mechanisms are presented. A summary of the principal adverse effects observed and an overview of the new potential therapeutic indications for COX-2 inhibitors are also reported.

Background: There are a great number of tools that can be used in QSAR/QSPR studies; they are implemented in several programs that are reviewed in this report. The usefulness of new tools can be proved through comparison, with previously published approaches. In order to perform the comparison, the most usual is the use of several benchmark datasets such as DRAGON and Sutherland’s datasets. Methods: Here, an exploratory study of Atomic Weighted Vectors (AWVs), a new tool useful for drug discovery using different datasets, is presented. In order to evaluate the performance of the new tool, several statistics and QSAR/QSPR experiments are performed. Variability analyses are used to quantify the information content of the AWVs obtained from the tool, by means of an information theory-based algorithm. Results: Principal components analysis is used to analyze the orthogonality of these descriptors, for which the new MDs from AWVs provide different information from those codified by DRAGON descriptors (0-2D). The QSAR models are obtained for every Sutherland's dataset, according to the original division into training/test sets, by means of the multiple linear regression with genetic algorithm (MLR-GA). These models have been validated and compared favorably to several previously published approaches, using the same benchmark datasets. Conclusion: The obtained results show that this tool should be a useful strategy for the QSAR/QSPR studies, despite its simplicity.

This study evaluated the antioxidative effects of magnolol based on the mouse model induced by Enterotoxigenic Escherichia coli (E. coli, ETEC). All experimental mice were equally treated with ETEC suspensions (3.45×109 CFU/ml) after oral administration of magnolol for 7 days at the dose of 0, 100, 300 and 500 mg/kg Body Weight (BW), respectively. The oxidative metabolites and antioxidases for each sample (organism of mouse) were determined: Malondialdehyde (MDA), Nitric Oxide (NO), Glutathione (GSH), Myeloperoxidase (MPO), Catalase (CAT), Superoxide Dismutase (SOD), and Glutathione Peroxidase (GPx). In addition, we also determined the corresponding mRNA expressions of CAT, SOD and GPx as well as the Total Antioxidant Capacity (T-AOC). The experiment was completed with a theoretical study that predicts a series of 79 ChEMBL activities of magnolol with 47 proteins in 18 organisms using a Quantitative Structure- Activity Relationship (QSAR) classifier based on the Moving Averages (MAs) of Rcpi descriptors in three types of experimental conditions (biological activity with specific units, protein target and organisms). Six Machine Learning methods from Weka software were tested and the best QSAR classification model was provided by Random Forest with True Positive Rate (TPR) of 0.701 and Area under Receiver Operating Characteristic (AUROC) of 0.790 (test subset, 10-fold crossvalidation). The model is predicting if the new ChEMBL activities are greater or lower than the average values for the magnolol targets in different organisms.

CML originates due to reciprocal translocation in Philadelphia chromosome leading to the formation of fusion product BCR-ABL which constitutively activates tyrosine kinase signaling pathways eventually leading to abnormal proliferation of granulocytic cells. As a therapeutic strategy, BCR-ABL inhibitors have been clinically approved which terminates its phosphorylation activity and retards cancer progression. However, a number of patients develop resistance to inhibitors which demand for the discovery of new inhibitors. Given the drawbacks of present inhibitors, by high throughput virtual screening approaches, present study pursues to identify high affinity compounds targeting BCR-ABL1 anticipated to have safer pharmacological profiles. Five established BCR-ABL inhibitors formed the query compounds for identification of structurally similar compounds by Tanimoto coefficient based linear fingerprint search with a threshold of 95% against PubChemdatabase. Assisted by MolDock algorithm all compounds were docked against BCR-ABL protein in order to retrieve high affinity compounds. The parents and similars were further tested for their ADMET propertiesand bioactivity. Rebastinib formed higher affinity inhibitor than rest of the four established compound investigated in the study. Interestingly, Rebastinib similar compound with Pubchem ID: 67254402 was also shown to have highest affinity than other similars including the similars of respective five parents. In terms of ADMET properties Pubchem ID: 67254402 had appreciable ADMET profile and bioactivity. However, Rebastinib still stood as the best inhibitor in terms of binding affinity and ADMET properties than Pubchem ID: 67254402. Nevertheless, owing to the similar pharmacological properties with Rebastinib, Pubchem ID: 67254402 can be expected to form potential BCR-ABL inhibitor.