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      Building the drug-GO function network to screen significant candidate drugs for myasthenia gravis

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          Abstract

          Myasthenia gravis (MG) is an autoimmune disease. In recent years, considerable evidence has indicated that Gene Ontology (GO) functions, especially GO-biological processes, have important effects on the mechanisms and treatments of different diseases. However, the roles of GO functions in the pathogenesis and treatment of MG have not been well studied. This study aimed to uncover the potential important roles of risk-related GO functions and to screen significant candidate drugs related to GO functions for MG. Based on MG risk genes, 238 risk GO functions and 42 drugs were identified. Through constructing a GO function network, we discovered that positive regulation of NF-kappaB transcription factor activity (GO:0051092) may be one of the most important GO functions in the mechanism of MG. Furthermore, we built a drug-GO function network to help evaluate the latent relationship between drugs and GO functions. According to the drug-GO function network, 5 candidate drugs showing promise for treating MG were identified. Indeed, 2 out of 5 candidate drugs have been investigated to treat MG. Through functional enrichment analysis, we found that the mechanisms between 5 candidate drugs and associated GO functions may involve two vital pathways, specifically hsa05332 (graft-versus-host disease) and hsa04940 (type I diabetes mellitus). More interestingly, most of the processes in these two pathways were consistent. Our study will not only reveal a new perspective on the mechanisms and novel treatment strategies of MG, but also will provide strong support for research on GO functions.

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          Most cited references42

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          DAVID: Database for Annotation, Visualization, and Integrated Discovery.

          Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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            DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

            The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.
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              The genetic association database.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: Formal analysisRole: Visualization
                Role: ConceptualizationRole: Formal analysisRole: Visualization
                Role: Investigation
                Role: Investigation
                Role: Data curation
                Role: Data curation
                Role: Data curation
                Role: Software
                Role: Investigation
                Role: Software
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                4 April 2019
                2019
                : 14
                : 4
                : e0214857
                Affiliations
                [1 ] Department of Neurology, The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang Province, China
                [2 ] Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
                [3 ] College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China
                Chuo University, JAPAN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-2782-4010
                Article
                PONE-D-18-28143
                10.1371/journal.pone.0214857
                6448860
                30947317
                12425d19-a99e-40ce-a3ff-aace3959b818
                © 2019 Li et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 September 2018
                : 22 March 2019
                Page count
                Figures: 6, Tables: 0, Pages: 17
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81820108014
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81571166
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81771361
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81701190
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81701155
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81801190
                Award Recipient :
                Funded by: The Applied Technique Research and Development Project of Harbin
                Award ID: 2016RAXYJ067
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100008978, Health and Family Planning Commission of Heilongjiang Province;
                Award ID: 2016-052
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100008978, Health and Family Planning Commission of Heilongjiang Province;
                Award ID: 2016-072
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100008978, Health and Family Planning Commission of Heilongjiang Province;
                Award ID: 2017-079
                Award Recipient :
                Funded by: The Fundamental Research Funds for the Provincial Universities
                Award ID: 2017LCZX57
                Award Recipient :
                Funded by: The Fundamental Research Funds for the Provincial Universities
                Award ID: 2017LCZX65
                Award Recipient :
                Funded by: The Fundamental Research Funds for the Provincial Universities
                Award ID: 2017LCZX48
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100004027, Postdoctoral Foundation of Hei Long Jiang Province;
                Award ID: LBH-Z17138
                Award Recipient :
                This work was supported by the National Natural Science Foundation of China (Grant nos. 81820108014 to LW, 81571166 to LW, 81771361 to LW, 81701190 to JW, 81701155 to XL and 81801190 to YC), The applied technique research and development project of Harbin (2016RAXYJ067 to LW), Health and Family Planning Commission of Heilongjiang Province (2016-052 to JW, 2016-072 to HZ and 2017-079 to XL), The Fundamental Research Funds for the Provincial Universitie (2017LCZX57 to JW, 2017LCZX65 to HZ and 2017LCZX48 to XL), The Postdoctoral Foundation of Heilongjiang Province(LBH-Z17138 to HZ).
                Categories
                Research Article
                Medicine and Health Sciences
                Clinical Medicine
                Clinical Immunology
                Autoimmune Diseases
                Myasthenia Gravis
                Biology and Life Sciences
                Immunology
                Clinical Immunology
                Autoimmune Diseases
                Myasthenia Gravis
                Medicine and Health Sciences
                Immunology
                Clinical Immunology
                Autoimmune Diseases
                Myasthenia Gravis
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Gene Ontologies
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Gene Ontologies
                Biology and Life Sciences
                Genetics
                Gene Identification and Analysis
                Genetic Networks
                Computer and Information Sciences
                Network Analysis
                Genetic Networks
                Biology and Life Sciences
                Genetics
                Gene Expression
                Medicine and Health Sciences
                Pharmacology
                Drug Screening
                Medicine and Health Sciences
                Pharmacology
                Drug Research and Development
                Drug Discovery
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogenesis
                Medicine and Health Sciences
                Pharmacology
                Drug Research and Development
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

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                Uncategorized

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