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      Computational and In Vitro Analysis of Plumbagin’s Molecular Mechanism for the Treatment of Hepatocellular Carcinoma

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          Abstract

          Hepatocellular carcinoma (HCC) is the fifth most common malignant tumor and the second leading cause of cancer-related death in the world. Plumbagin (PL) is a small molecule naphthoquinone compound isolated from Plumbago zeylanica L . that has important anticancer properties, but its mechanism requires further investigation. In this study, we used a comprehensive network pharmacology approach to study the mechanism of action of PL for the treatment of HCC. The method includes the construction of multiple networks; moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify biological processes and signaling pathways. Subsequently, in vitro experiments were performed to verify the predicted molecular mechanisms obtained from the network pharmacology-based analysis. Network pharmacological analysis showed that PL may exert anti-HCC effects by enhancing reactive oxygen species (ROS) production to generate oxidative stress and by regulating the PI3K/Akt and MAPK signaling pathways. In vitro experiments confirmed that PL mainly mediates the production of ROS, regulates the PI3K/Akt and MAPK signaling pathways to promote apoptosis and autophagy, and shows significant therapeutic effects on HCC. In conclusion, our work proposes a comprehensive systems pharmacology approach to explore the potential mechanism of PL for the treatment of HCC.

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          Most cited references42

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible

            A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein–protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein–protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.
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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
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                12 April 2021
                2021
                : 12
                : 594833
                Affiliations
                Department of Physiology, Guangxi University of Chinese Medicine, Nanning, China
                Author notes

                Edited by: Marcus Scotti, Federal University of Paraíba, Brazil

                Reviewed by: Xianbin Zhang, Shenzhen University, China

                Yashi Mi, University of Arizona, United States

                *Correspondence: Delun Huang, huangdelun0621@ 123456foxmail.com

                This article was submitted to Ethnopharmacology, a section of the journal Frontiers in Pharmacology

                [†]

                These authors have contributed equally to this work

                Article
                594833
                10.3389/fphar.2021.594833
                8072012
                33912033
                d8f0b41b-6e46-4156-bb8a-d55e6ab54f2c
                Copyright © 2021 Wei, Lin, Chen, Liu, Jin and Huang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 August 2020
                : 18 February 2021
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 81760757
                Funded by: Natural Science Foundation of Guangxi Province 10.13039/501100004607
                Award ID: 2019JJD140032
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                plumbagin,hepatocellular carcinoma,network pharmacology,ros,pi3k/akt pathway,mapk pathway

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