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      An Investigation of the Molecular Mechanisms Underlying the Analgesic Effect of Jakyak-Gamcho Decoction: A Network Pharmacology Study

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          Abstract

          Herbal drugs have drawn substantial interest as effective analgesic agents; however, their therapeutic mechanisms remain to be fully understood. To address this question, we performed a network pharmacology study to explore the system-level mechanisms that underlie the analgesic activity of Jakyak-Gamcho decoction (JGd; Shaoyao-Gancao-Tang in Chinese and Shakuyaku-Kanzo-To in Japanese), an herbal prescription consisting of Paeonia lactiflora Pallas and Glycyrrhiza uralensis Fischer. Based on comprehensive information regarding the pharmacological and chemical properties of the herbal constituents of JGd, we identified 57 active chemical compounds and their 70 pain-associated targets. The JGd targets were determined to be involved in the regulation of diverse biological activities as follows: calcium- and cytokine-mediated signalings, calcium ion concentration and homeostasis, cellular behaviors of muscle and neuronal cells, inflammatory response, and response to chemical, cytokine, drug, and oxidative stress. The targets were further enriched in various pain-associated signalings, including the PI3K-Akt, estrogen, ErbB, neurotrophin, neuroactive ligand-receptor interaction, HIF-1, serotonergic synapse, JAK-STAT, and cAMP pathways. Thus, these data provide a systematic basis to understand the molecular mechanisms underlying the analgesic activity of herbal drugs.

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          Most cited references358

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            KEGG: kyoto encyclopedia of genes and genomes.

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            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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              STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

              Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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                Author and article information

                Contributors
                Journal
                Evid Based Complement Alternat Med
                Evid Based Complement Alternat Med
                ECAM
                Evidence-based Complementary and Alternative Medicine : eCAM
                Hindawi
                1741-427X
                1741-4288
                2020
                1 December 2020
                1 December 2020
                : 2020
                : 6628641
                Affiliations
                1The Fore, 87 Ogeum-ro, Songpa-gu, Seoul 05542, Republic of Korea
                2Forest Hospital, 129 Ogeum-ro, Songpa-gu, Seoul 05549, Republic of Korea
                3Forestheal Hospital, 173 Ogeum-ro, Songpa-gu, Seoul 05641, Republic of Korea
                Author notes

                Academic Editor: Xia Wang

                Author information
                https://orcid.org/0000-0002-3198-9881
                Article
                10.1155/2020/6628641
                7732394
                51f10c2b-e156-4dd1-8229-fd53eeda0376
                Copyright © 2020 Ho-Sung Lee et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 9 October 2020
                : 5 November 2020
                : 24 November 2020
                Categories
                Research Article

                Complementary & Alternative medicine
                Complementary & Alternative medicine

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