Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0917801 (insomnia)
 10,606 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Metabolomics represents an emerging and powerful discipline that provides an accurate and dynamic picture of the phenotype of biosystems through the study of potential metabolites that could be used for therapeutic targets and discovery of new drugs. Metabolomic network construction has led to the integration of metabolites associated with the caused perturbation of multiple pathways. Herein, we present a method for the construction of efficient networks with regard to that Jujuboside B (JuB) protects against insomnia as a case study. UPLC/ESI-SYNAPT-HDMS coupled with pattern recognition methods including PCA, PLS-DA, OPLS-DA, and computational systems analysis were integrated to obtain comprehensive metabolomic profiling and pathways of the large biological data sets. Among the regulated pathways, twelve biomarkers were identified and tryptophan metabolism, phenylalanine, tyrosine, tryptophan biosynthesis, arachidonic acid metabolism, and phenylalanine metabolism related network were acutely perturbed. Results not only supplied a systematic view of the development and progression of insomnia but also were used to analyze the therapeutic effects of JuB, a widely used anti-insomina medicine in clinics. The results showed that JuB administration could provide satisfactory effects on insomnia through partially regulating the perturbed pathway. We have constructed a metabolomic feature network of JuB to protect against insomnia. The most promising use in the near future would be to clarify pathways for the drugs and get biomarkers for these pathways, to help guide testable predictions, provide insights into drug action mechanisms, and enable us to increase research productivity toward metabolomic drug discovery.
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PMID:Pattern recognition approaches and computational systems tools for ultra performance liquid chromatography-mass spectrometry-based comprehensive metabolomic profiling and pathways analysis of biological data sets. 2213 38

Potential metabolites from the metabolic pathways could be therapeutic targets and useful for the discovery of broad spectrum drugs. UPLC/ESI-SYNAPT-HDMS coupled with pattern recognition methods including PCA, PLS-DA, OPLS-DA and Heatmap were integrated to examine the global metabolic signature of insomnia and intervention effects of Jujuboside A (JuA). Six unique pathways of the insomnia were identified using Ingenuity Pathway Analysis (IPA) software. The VIP-value threshold cutoff of the metabolites was set to 10, above this threshold, were filtered out as potential target biomarkers. Sixteen distinct metabolites were identified from these pathways, and 6 of them can be considered for rational drug design. It was further experimental validation that the changes in metabolic profiling were restored to their baseline values after JuA treatment according to the multivariate data analysis. Potential metabolite network of the insomnia was preliminarily predicted JuA-target interaction networks, and could be further explored for in silico docking studies with suitable drugs. Thus, our method is an efficient procedure for drug target identification through metabolic analysis. It can guide testable predictions, provide insights into drug action mechanisms and enable us to increase research productivity toward metabolomic drug discovery.
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PMID:Potential drug targets on insomnia and intervention effects of Jujuboside A through metabolic pathway analysis as revealed by UPLC/ESI-SYNAPT-HDMS coupled with pattern recognition approach. 2213 58