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      Canagliflozin attenuates lipotoxicity in cardiomyocytes and protects diabetic mouse hearts by inhibiting the mTOR/HIF-1α pathway

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          Summary

          Lipotoxicity plays an important role in the development of diabetic heart failure (HF). Canagliflozin (CAN), a marketed sodium-glucose co-transporter 2 inhibitor, has significantly beneficial effects on HF. In this study, we evaluated the protective effects and mechanism of CAN in the hearts of C57BL/6J mice induced by high-fat diet/streptozotocin (HFD/STZ) for 12 weeks in vivo and in HL-1 cells (a type of mouse cardiomyocyte line) induced by palmitic acid (PA) in vitro. The results showed that CAN significantly ameliorated heart functions and inflammatory responses in the hearts of the HFD/STZ-induced diabetic mice. CAN significantly attenuated the inflammatory injury induced by PA in the HL-1 cells. Furthermore, CAN seemed to bind to the mammalian target of rapamycin (mTOR) and then inhibit mTOR phosphorylation and hypoxia-inducible factor-1α (HIF-1α) expression. These results indicated that CAN might attenuate lipotoxicity in cardiomyocytes by inhibiting the mTOR/HIF-1α pathway and then show protective effects on diabetic hearts.

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          Highlights

          • Canagliflozin ameliorated heart dysfunctions in HFD/STZ-induced diabetic mice

          • Canagliflozin inhibited lipotoxicity in palmitic acid-induced HL-1 cardiomyocytes

          • mTOR-HIF-1α pathway mediated lipotoxicity in cardiomyocytes

          • Canagliflozin bound to mTOR and inhibited mTOR-HIF-1α pathway

          Abstract

          Human metabolism; Molecular biology

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          Most cited references57

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          UCSF Chimera--a visualization system for exploratory research and analysis.

          The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/. Copyright 2004 Wiley Periodicals, Inc.
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            ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

            Summary: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in. Availability: http://www.ici.upmc.fr/cluego/cluegoDownload.shtml Contact: jerome.galon@crc.jussieu.fr Supplementary information: Supplementary data are available at Bioinformatics online.
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              SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules

              Abstract SwissTargetPrediction is a web tool, on-line since 2014, that aims to predict the most probable protein targets of small molecules. Predictions are based on the similarity principle, through reverse screening. Here, we describe the 2019 version, which represents a major update in terms of underlying data, backend and web interface. The bioactivity data were updated, the model retrained and similarity thresholds redefined. In the new version, the predictions are performed by searching for similar molecules, in 2D and 3D, within a larger collection of 376 342 compounds known to be experimentally active on an extended set of 3068 macromolecular targets. An efficient backend implementation allows to speed up the process that returns results for a druglike molecule on human proteins in 15–20 s. The refreshed web interface enhances user experience with new features for easy input and improved analysis. Interoperability capacity enables straightforward submission of any input or output molecule to other on-line computer-aided drug design tools, developed by the SIB Swiss Institute of Bioinformatics. High levels of predictive performance were maintained despite more extended biological and chemical spaces to be explored, e.g. achieving at least one correct human target in the top 15 predictions for >70% of external compounds. The new SwissTargetPrediction is available free of charge (www.swisstargetprediction.ch).
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                Author and article information

                Contributors
                Journal
                iScience
                iScience
                iScience
                Elsevier
                2589-0042
                07 May 2021
                25 June 2021
                07 May 2021
                : 24
                : 6
                : 102521
                Affiliations
                [1 ]Open FIESTA Center, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
                [2 ]State Key Laboratory of Chemical Oncogenomic, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
                [3 ]Key Lab in Health Science and Technology, Institute of Biopharmaceutical and Health Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
                Author notes
                []Corresponding author xiewd@ 123456sz.tsinghua.edu.cn
                [4]

                These authors contributed equally

                [5]

                Lead contact

                Article
                S2589-0042(21)00489-2 102521
                10.1016/j.isci.2021.102521
                8188479
                34142035
                3f21dc4e-7396-4ec2-b67c-33e2a5a9ca8f
                © 2021 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 4 February 2021
                : 12 April 2021
                : 5 May 2021
                Categories
                Article

                human metabolism,molecular biology
                human metabolism, molecular biology

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