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System biology-based assessment of the molecular mechanism of IMPHY000797 in Parkinson’s disease: a network pharmacology and in-silico evaluation
System biology-based assessment of the molecular mechanism of IMPHY000797 in Parkinson’s disease: a network pharmacology and in-silico evaluation
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System biology-based assessment of the molecular mechanism of IMPHY000797 in Parkinson’s disease: a network pharmacology and in-silico evaluation
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System biology-based assessment of the molecular mechanism of IMPHY000797 in Parkinson’s disease: a network pharmacology and in-silico evaluation
System biology-based assessment of the molecular mechanism of IMPHY000797 in Parkinson’s disease: a network pharmacology and in-silico evaluation

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System biology-based assessment of the molecular mechanism of IMPHY000797 in Parkinson’s disease: a network pharmacology and in-silico evaluation
System biology-based assessment of the molecular mechanism of IMPHY000797 in Parkinson’s disease: a network pharmacology and in-silico evaluation
Journal Article

System biology-based assessment of the molecular mechanism of IMPHY000797 in Parkinson’s disease: a network pharmacology and in-silico evaluation

2024
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Overview
IMPHY000797 derivatives have been well known for their efficacy in various diseases. Moreover, IMPHY000797 derivatives have been found to modulate such genes involved in multiple neurological disorders. Hence, this study seeks to identify such genes and the probable molecular mechanism that could be involved in the pathogenesis of Parkinson’s disease. The study utilized various biological tools such as DisGeNET, STRING, Swiss target predictor, Cytoscape, AutoDock 4.2, Schrodinger suite, ClueGo, and GUSAR. All the reported genes were obtained using DisGeNET, and further, the common genes were incorporated into the STRING to get the KEGG pathway, and all the data was converted to a protein/pathway network via Cytoscape. The clustering of the genes was performed for the gene-enriched data using two-sided hypergeometrics (p-value). The binding affinity of the IMPHY000797 was verified with the highest regulated 25 proteins via utilizing the “Monte Carlo iterated search technique” and the “ Emodel and Glide score ” function. Three thousand five hundred eighty-three genes were identified for Parkinson’s disease and 31 genes for IMPHY000797 compound, among which 25 common genes were identified. Further, the “FOXO-signaling pathway” was identified to be a modulated pathway. Among the 25 proteins, the highest modulated genes and highest binding affinity were exhibited by SIRT3, FOXO1, and PPARGC1A with the compound IMPHY000797. Further, rat toxicity analysis provided the efficacy and safety of the compound. The study was required to identify the probable molecular mechanism, which needs more confirmation from other studies, which is still a significant hit-back.