scholarly journals Image-Based Marker-Free Screening of GABAA Agonists, Antagonists, and Modulators

2019 ◽  
Vol 25 (5) ◽  
pp. 458-470 ◽  
Author(s):  
Benjamin Rappaz ◽  
Pascal Jourdain ◽  
Damiano Banfi ◽  
Fabien Kuttler ◽  
Pierre Marquet ◽  
...  

The ionotropic GABAA receptors represent the main target for different groups of widely used drugs having hypnotic and anxiolytic effects. So far, most approaches used to assess GABA activity involve invasive low -throughput electrophysiological techniques or rely on fluorescent dyes, preventing the ability to conduct noninvasive and thus nonperturbing screens. To address this limitation, we have developed an automated marker-free cell imaging method, based on digital holographic microscopy (DHM). This technology allows the automatically screening of compounds in multiple plates without having to label the cells or use special plates. This methodological approach was first validated by screening the GABAA receptor expressed in HEK cells using a selection of active compounds in agonist, antagonist, and modulator modes. Then, in a second blind screen of a library of 3041 compounds (mostly composed of natural products), 5 compounds having a specific agonist action on the GABAA receptor were identified. The hits validated from this unbiased screen were the natural products muscimol, neurosteroid alphaxalone, and three compounds belonging to the avermectin family, all known for having an agonistic effect on the GABAA receptor. The results obtained were exempt from false negatives (structurally similar unassigned hits), and false-positive hits were detected and discarded without the need for performing electrophysiological measurements. The outcome of the screen demonstrates the applicability of our screening by imaging method for the discovery of new chemical structures, particularly regarding chemicals interacting with the ionotropic GABAA receptor and more generally with any ligand-gated ion channels and transporters.

2018 ◽  
Author(s):  
William A. Shirley ◽  
Brian P. Kelley ◽  
Yohann Potier ◽  
John H. Koschwanez ◽  
Robert Bruccoleri ◽  
...  

This pre-print explores ensemble modeling of natural product targets to match chemical structures to precursors found in large open-source gene cluster repository antiSMASH. Commentary on method, effectiveness, and limitations are enclosed. All structures are public domain molecules and have been reviewed for release.


2020 ◽  
Vol 26 ◽  
Author(s):  
Shaik Ibrahim Khalivulla ◽  
Arifullah Mohammed ◽  
Kokkanti Mallikarjuna

Background: Diabetes is a chronic disease affecting a large population worldwide and stands as one of the major global health challenges to be tackled. According to World Health Organization, about 400 million are having diabetes worldwide and it is the seventh leading cause of deaths in 2016. Plant based natural products had been in use from ancient time as ethnomedicine for the treatment of several diseases including diabetes. As a result of that, there are several reports on plant based natural products displaying antidiabetic activity. In the current review, such antidiabetic potential compounds reported from all plant sources along with their chemical structures are collected, presented and discussed. This kind of reports are essential to pool the available information to one source followed by statistical analysis and screening to check the efficacy of all known compounds in a comparative sense. This kind of analysis can give rise to few numbers of potential compounds from hundreds, whom can further be screened through in vitro and in vivo studies, and human trails leading to the drug development. Methods: Phytochemicals along with their potential antidiabetic property were classified according to their basic chemical skeleton. The chemical structures of all the compounds with antidiabetic activities were elucidated in the present review. In addition to this, the distribution and their other remarkable pharmacological activities of each species is also included. Results: The scrutiny of literature led to identification of 44 plants with antidiabetic compounds (70) and other pharmacological activities. For the sake of information, the distribution of each species in the world is given. Many plant derivatives may exert antidiabetic properties by improving or mimicking the insulin production or action. Different classes of compounds including sulfur compounds (1-4), alkaloids (5-11), phenolic compounds (12-17), tannins (18-23), phenylpropanoids (24-27), xanthanoids (28-31), amino acid (32), stilbenoid (33), benzofuran (34), coumarin (35), flavonoids (36-49) and terpenoids (50-70) were found to be active potential compounds for antidiabetic activity. Of the 70 listed compounds, majorly 17 compounds are from triterpenoids, 13 flavonoids and 7 are from alkaloids. Among all the 44 plant species, maximum number (7) of compounds are reported from Lagerstroemia speciosa followed by Momordica charantia (6) and S. oblonga with 5 compounds. Conclusion: This is the first paper to summarize the established chemical structures of phytochemicals that have been successfully screened for antidiabetic potential and their mechanisms of inhibition. The reported compounds could be considered as potential lead molecules for the treatment of type-2 diabetes. Further, molecular and clinical trials are required to select and establish the therapeutic drug candidates.


2019 ◽  
Vol 16 (10) ◽  
pp. 1130-1137
Author(s):  
Hayrettin Ozan Gulcan ◽  
Serkan Yigitkan ◽  
Ilkay Erdogan Orhan

High cholesterol and triglyceride levels are mainly related to further generation of lifethreating metabolism disorders including cardiovascular system diseases. Therefore, hypercholesterolemia (i.e., also referred to as hyperlipoproteinemia) is a serious disease state, which must be controlled. Currently, the treatment of hypercholesterolemia is mainly achieved through the employment of statins in the clinic, although there are alternative drugs (e.g., ezetimibe, cholestyramine). In fact, the original statins are natural products directly obtained from fungi-like molds and mushrooms and they are potent inhibitors of hydroxymethylglutaryl-CoA reductase, the key enzyme in the biosynthesis of cholesterol. This review focuses on the first identification of natural statins, their synthetic and semi-synthetic analogues, and the validation of hydroxymethylglutaryl-CoA reductase as a target in the treatment of hypercholesterolemia. Furthermore, other natural products that have been shown to possess the potential to inhibit hydroxymethylglutaryl-CoA reductase are also reviewed with respect to their chemical structures.


2021 ◽  
Vol 270 ◽  
pp. 113872
Author(s):  
Tao Hou ◽  
Fangfang Xu ◽  
Xingrong Peng ◽  
Han Zhou ◽  
Xiuli Zhang ◽  
...  

Metabolites ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 48
Author(s):  
Marc Feuermann ◽  
Emmanuel Boutet ◽  
Anne Morgat ◽  
Kristian Axelsen ◽  
Parit Bansal ◽  
...  

The UniProt Knowledgebase UniProtKB is a comprehensive, high-quality, and freely accessible resource of protein sequences and functional annotation that covers genomes and proteomes from tens of thousands of taxa, including a broad range of plants and microorganisms producing natural products of medical, nutritional, and agronomical interest. Here we describe work that enhances the utility of UniProtKB as a support for both the study of natural products and for their discovery. The foundation of this work is an improved representation of natural product metabolism in UniProtKB using Rhea, an expert-curated knowledgebase of biochemical reactions, that is built on the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Knowledge of natural products and precursors is captured in ChEBI, enzyme-catalyzed reactions in Rhea, and enzymes in UniProtKB/Swiss-Prot, thereby linking chemical structure data directly to protein knowledge. We provide a practical demonstration of how users can search UniProtKB for protein knowledge relevant to natural products through interactive or programmatic queries using metabolite names and synonyms, chemical identifiers, chemical classes, and chemical structures and show how to federate UniProtKB with other data and knowledge resources and tools using semantic web technologies such as RDF and SPARQL. All UniProtKB data are freely available for download in a broad range of formats for users to further mine or exploit as an annotation source, to enrich other natural product datasets and databases.


2020 ◽  
Vol 5 (8) ◽  
Author(s):  
Fidele Ntie-Kang ◽  
Daniel Svozil

AbstractThe discovery of a new drug is a multidisciplinary and very costly task. One of the major steps is the identification of a lead compound, i.e. a compound with a certain degree of potency and that can be chemically modified to improve its activity, metabolic properties, and pharmacokinetics profiles. Terrestrial sources (plants and fungi), microbes and marine organisms are abundant resources for the discovery of new structurally diverse and biologically active compounds. In this chapter, an attempt has been made to quantify the numbers of known published chemical structures (available in chemical databases) from natural sources. Emphasis has been laid on the number of unique compounds, the most abundant compound classes and the distribution of compounds in terrestrial and marine habitats. It was observed, from the recent investigations, that ~500,000 known natural products (NPs) exist in the literature. About 70 % of all NPs come from plants, terpenoids being the most represented compound class (except in bacteria, where amino acids, peptides, and polyketides are the most abundant compound classes). About 2,000 NPs have been co-crystallized in PDB structures.


F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 993 ◽  
Author(s):  
J. Jesús Naveja ◽  
Mariel P. Rico-Hidalgo ◽  
José L. Medina-Franco

Background: Food chemicals are a cornerstone in the food industry. However, its chemical diversity has been explored on a limited basis, for instance, previous analysis of food-related databases were done up to 2,200 molecules. The goal of this work was to quantify the chemical diversity of chemical compounds stored in FooDB, a database with nearly 24,000 food chemicals. Methods: The visual representation of the chemical space of FooDB was done with ChemMaps, a novel approach based on the concept of chemical satellites. The large food chemical database was profiled based on physicochemical properties, molecular complexity and scaffold content. The global diversity of FooDB was characterized using Consensus Diversity Plots. Results: It was found that compounds in FooDB are very diverse in terms of properties and structure, with a large structural complexity. It was also found that one third of the food chemicals are acyclic molecules and ring-containing molecules are mostly monocyclic, with several scaffolds common to natural products in other databases. Conclusions: To the best of our knowledge, this is the first analysis of the chemical diversity and complexity of FooDB. This study represents a step further to the emerging field of “Food Informatics”. Future study should compare directly the chemical structures of the molecules in FooDB with other compound databases, for instance, drug-like databases and natural products collections. An additional future direction of this work is to use the list of 3,228 polyphenolic compounds identified in this work to enhance the on-going polyphenol-protein interactome studies.


This exercises aims to familiarize students with chemical structures of natural products. Students will also use computational methods to learn about trends or the lack thereof in natural products.


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