Identification of Potential Therapeutic Agents for Primary Amebic Meningoencephalitis Using Text Mining and Bioinformatics Analyses.

Naegleria fowleri, the brain-eating ameba, causes primary amebic meningoencephalitis (PAM), a fatal infectious disease that affects the central nervous system (CNS). We aimed to evaluate the functions and potential drugs targeting PAM using text mining and bioinformatics analyses. PAM-associated genes were identified using a disease database and mined from literature. To identify candidate drugs targeting PAM, 218 genes were analyzed using PanDrugs, drug Manually Annotated Targets and Drugs Online Resource (MATADOR), and the drug Comparative Toxicogenomics Database (CTD) by text mining. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) functional analyses were performed to examine the mechanism of action of PAM. The GO functions of genes involved in PAM identified by text mining were leukocyte differentiation and the regulation of cytokine production. Disease-related PAM analyses indicated association with Zellweger syndrome, peroxisomal disease, periodontitis, and leishmaniasis. KEGG enrichment included pathways related to inflammatory bowel disease, malaria, interleukin (IL)-17 signaling pathway, Yersinia infection, Chagas disease, amebiasis, rheumatoid arthritis, pathogenic Escherichia coli infection, lipids, atherosclerosis, and peroxisomes. In addition, arsenic trioxide, bortezomib, dasatinib, bosutinib, bevacizumab, paclitaxel, midostaurin, tamoxifen, copanlisib, and pazopanib were identified as potential drugs targeting PAM using PanDrugs software. Our analyses revealed that text mining-related PAM genes were enriched in several pathways, such as peroxisomes and protein localization. We suggest that PAM is linked to other diseases, such as Zellweger's syndrome, leishmaniasis, and periodontitis, and provide potential drugs for effective treatment.