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      Integrated Network Pharmacology Analysis and Experimental Validation to Reveal the Mechanism of Anti-Insulin Resistance Effects of Moringa oleifera Seeds

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          Abstract

          Background and Purpose

          Insulin resistance (IR) is one of the factors that results in metabolic syndrome, type 2 diabetes mellitus and different aspects of cardiovascular diseases. Moringa oleifera seeds (MOS), traditionally used as an antidiabetic food and traditional medicine in tropical Asia and Africa, have exhibited potential effects in improving IR. To systematically explore the pharmacological mechanism of the anti-IR effects of MOS, we adopted a network pharmacology approach at the molecular level.

          Methods

          By incorporating compound screening and target prediction, a feasible compound-target-pathway network pharmacology model was established to systematically predict the potential active components and mechanisms of the anti-IR effects of MOS. Biological methods were then used to verify the results of the network pharmacology analysis.

          Results

          Our comprehensive systematic approach successfully identified 32 bioactive compounds in MOS and 44 potential targets of these compounds related to IR, as well as 37 potential pathways related to IR. Moreover, the network pharmacology analysis revealed that glycosidic isothiocyanates and glycosidic benzylamines were the major active components that improved IR by acting on key targets, such as SRC, PTPN1, and CASP3, which were involved in inflammatory responses and insulin-related pathways. Further biological research demonstrated that the anti-IR effects of MOS were mediated by increasing glucose uptake and modulating the expression of SRC and PTPN1.

          Conclusion

          Our study successfully predicts the active ingredients and potential targets of MOS for improving IR and helps to illustrate mechanism of action at a systemic level. This study not only provides new insights into the chemical basis and pharmacology of MOS but also demonstrates a feasible method for discovering potential drugs from traditional medicines.

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          Most cited references 68

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          Network pharmacology: the next paradigm in drug discovery.

          The dominant paradigm in drug discovery is the concept of designing maximally selective ligands to act on individual drug targets. However, many effective drugs act via modulation of multiple proteins rather than single targets. Advances in systems biology are revealing a phenotypic robustness and a network structure that strongly suggests that exquisitely selective compounds, compared with multitarget drugs, may exhibit lower than desired clinical efficacy. This new appreciation of the role of polypharmacology has significant implications for tackling the two major sources of attrition in drug development--efficacy and toxicity. Integrating network biology and polypharmacology holds the promise of expanding the current opportunity space for druggable targets. However, the rational design of polypharmacology faces considerable challenges in the need for new methods to validate target combinations and optimize multiple structure-activity relationships while maintaining drug-like properties. Advances in these areas are creating the foundation of the next paradigm in drug discovery: network pharmacology.
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            Tumor necrosis factor-alpha induces skeletal muscle insulin resistance in healthy human subjects via inhibition of Akt substrate 160 phosphorylation.

            Most lifestyle-related chronic diseases are characterized by low-grade systemic inflammation and insulin resistance. Excessive tumor necrosis factor-alpha (TNF-alpha) concentrations have been implicated in the development of insulin resistance, but direct evidence in humans is lacking. Here, we demonstrate that TNF-alpha infusion in healthy humans induces insulin resistance in skeletal muscle, without effect on endogenous glucose production, as estimated by a combined euglycemic insulin clamp and stable isotope tracer method. TNF-alpha directly impairs glucose uptake and metabolism by altering insulin signal transduction. TNF-alpha infusion increases phosphorylation of p70 S6 kinase, extracellular signal-regulated kinase-1/2, and c-Jun NH(2)-terminal kinase, concomitant with increased serine and reduced tyrosine phosphorylation of insulin receptor substrate-1. These signaling effects are associated with impaired phosphorylation of Akt substrate 160, the most proximal step identified in the canonical insulin signaling cascade regulating GLUT4 translocation and glucose uptake. Thus, excessive concentrations of TNF-alpha negatively regulate insulin signaling and whole-body glucose uptake in humans. Our results provide a molecular link between low-grade systemic inflammation and the metabolic syndrome.
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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

                Journal
                Drug Des Devel Ther
                Drug Des Devel Ther
                dddt
                dddt
                Drug Design, Development and Therapy
                Dove
                1177-8881
                02 October 2020
                2020
                : 14
                : 4069-4084
                Affiliations
                [1 ]Department of Pharmacy, Xiangya Hospital, Central South University , Changsha 410008, People’s Republic of China
                [2 ]Institute of Hospital Pharmacy, Central South University , Changsha 410008, People’s Republic of China
                [3 ]Institute for Rational and Safe Medication Practices, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University , Changsha 410008, People’s Republic of China
                Author notes
                Correspondence: Shao Liu; Yueping Jiang Department of Pharmacy, Xiangya Hospital, Central South University , 87 Xiangya Road, Changsha, Hunan4100080, People’s Republic of China Email liushao999@csu.edu.cn; jiangyueping@126.com
                [*]

                These authors contributed equally to this work

                Article
                265198
                10.2147/DDDT.S265198
                7539042
                © 2020 Huang et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                Page count
                Figures: 10, Tables: 2, References: 68, Pages: 16
                Categories
                Original Research

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