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      Prediction of the Molecular Mechanisms Underlying Erlong Zuoci Treatment of Age-Related Hearing Loss via Network Pharmacology-Based Analyses Combined with Experimental Validation

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          Abstract

          Background: The traditional Chinese medicine formula ErLong ZuoCi (ELZC) has been extensively used to treat age-related hearing loss (ARHL) in clinical practice in China for centuries. However, the underlying molecular mechanisms are still poorly understood.

          Objective: Combine network pharmacology with experimental validation to explore the potential molecular mechanisms underlying ELZC with a systematic viewpoint.

          Methods: The chemical components of ELZC were collected from the Traditional Chinese Medicine System Pharmacology database, and their possible target proteins were predicted using the SwissTargetPrediction database. The putative ARHL-related target proteins were identified from the database: GeneCards and OMIM. We constructed the drug-target network as well as drug-disease specific protein-protein interaction networks and performed clustering and topological property analyses. Functional annotation and signaling pathways were performed by gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. Finally, in vitro experiments were also performed to validate ELZC’s key target proteins and treatment effects on ARHL.

          Results: In total, 63 chemical compounds from ELZC and 365 putative ARHL-related targets were identified, and 1860 ARHL-related targets were collected from the OMIM and GeneCards. A total of 145 shared targets of ELZC and ARHL were acquired by Venn diagram analysis. Functional enrichment analysis suggested that ELZC might exert its pharmacological effects in multiple biological processes, such as cell proliferation, apoptosis, inflammatory response, and synaptic connections, and the potential targets might be associated with AKT, ERK, and STAT3, as well as other proteins. In vitro experiments revealed that ELZC pretreatment could decrease senescence-associated β-galactosidase activity in hydrogen peroxide-induced auditory hair cells, eliminate DNA damage, and reduce cellular senescence protein p21 and p53. Finally, Western blot analysis confirmed that ELZC could upregulate the predicted target ERK phosphorylation.

          Conclusion: We provide an integrative network pharmacology approach, in combination with in vitro experiments to explore the underlying molecular mechanisms governing ELZC treatment of ARHL. The protective effects of ELZC against ARHL were predicted to be associated with cellular senescence, inflammatory response, and synaptic connections which might be linked to various pathways such as JNK/STAT3 and ERK cascade signaling pathways. As a prosperous possibility, our experimental data suggest phosphorylation ERK is essential for ELZC to prevent degeneration of cochlear.

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          Most cited references62

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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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            TCMSP: a database of systems pharmacology for drug discovery from herbal medicines

            Background Modern medicine often clashes with traditional medicine such as Chinese herbal medicine because of the little understanding of the underlying mechanisms of action of the herbs. In an effort to promote integration of both sides and to accelerate the drug discovery from herbal medicines, an efficient systems pharmacology platform that represents ideal information convergence of pharmacochemistry, ADME properties, drug-likeness, drug targets, associated diseases and interaction networks, are urgently needed. Description The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was built based on the framework of systems pharmacology for herbal medicines. It consists of all the 499 Chinese herbs registered in the Chinese pharmacopoeia with 29,384 ingredients, 3,311 targets and 837 associated diseases. Twelve important ADME-related properties like human oral bioavailability, half-life, drug-likeness, Caco-2 permeability, blood-brain barrier and Lipinski’s rule of five are provided for drug screening and evaluation. TCMSP also provides drug targets and diseases of each active compound, which can automatically establish the compound-target and target-disease networks that let users view and analyze the drug action mechanisms. It is designed to fuel the development of herbal medicines and to promote integration of modern medicine and traditional medicine for drug discovery and development. Conclusions The particular strengths of TCMSP are the composition of the large number of herbal entries, and the ability to identify drug-target networks and drug-disease networks, which will help revealing the mechanisms of action of Chinese herbs, uncovering the nature of TCM theory and developing new herb-oriented drugs. TCMSP is freely available at http://sm.nwsuaf.edu.cn/lsp/tcmsp.php.
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              An automated method for finding molecular complexes in large protein interaction networks

              Background Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. Results This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Conclusion Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from .
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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
                23 November 2021
                2021
                : 12
                : 719267
                Affiliations
                [ 1 ]School of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai, China
                [ 2 ]Experimental Teaching Center, Shanghai University of Traditional Chinese Medicine, Shanghai, China
                Author notes

                Edited by: Zhiyu Wang, Guangzhou University of Chinese Medicine, China

                Reviewed by: Gao Zhu Ye, China Academy of Chinese Medical Sciences, China

                Yibin Feng, The University of Hong Kong, Hong Kong, SAR China

                Hansen Chen, Stanford University, United States

                *Correspondence: Jianrong Shi, sjr@ 123456shutcm.edu.cn
                [ † ]

                These authors have contributed equally to this work and share first authorship.

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

                Article
                719267
                10.3389/fphar.2021.719267
                8650627
                34887749
                1503d36a-c9e6-4d85-ae21-2ae7fbe81579
                Copyright © 2021 Liu, Li, Yang, Yan, Dong, Peng and Shi.

                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
                : 02 June 2021
                : 06 October 2021
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                erlong zuoci,age-related hearing loss,network pharmacology,experimental validation,cellular senescence,inflammatory response,synaptic connections

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