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

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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… Click to show full 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.

Keywords: candidate drugs; drug function; function network

Journal Title: PLoS ONE
Year Published: 2019

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