Revealing the Underlying Mechanism of Acacia Nilotica against Asthma from a Systematic Perspective: A Network Pharmacology and Molecular Docking Study.
Taghreed S AlnusaireSumera QasimMohammad M Al-SaneaOmnia HendawyAmbreen Malik UttraShaimaa R AhmedPublished in: Life (Basel, Switzerland) (2023)
Acacia Nilotica (AN) has long been used as a folk cure for asthma, but little is known about how AN could possibly modulate this disease. Thus, an in-silico molecular mechanism for AN's anti-asthmatic action was elucidated utilizing network pharmacology and molecular docking techniques. DPED, PubChem, Binding DB, DisGeNET, DAVID, and STRING were a few databases used to collect network data. MOE 2015.10 software was used for molecular docking. Out of 51 searched compounds of AN, eighteen compounds interacted with human target genes, a total of 189 compounds-related genes, and 2096 asthma-related genes were found in public databases, with 80 overlapping genes between them. AKT1, EGFR, VEGFA, and HSP90AB were the hub genes, whereas quercetin and apigenin were the most active components. p13AKT and MAPK signaling pathways were found to be the primary target of AN. Outcomes of network pharmacology and molecular docking predicted that AN might exert its anti-asthmatic effect probably by altering the p13AKT and MAPK signaling pathway.
Keyphrases
- molecular docking
- signaling pathway
- lung function
- pi k akt
- molecular dynamics simulations
- chronic obstructive pulmonary disease
- induced apoptosis
- epithelial mesenchymal transition
- bioinformatics analysis
- genome wide
- small cell lung cancer
- allergic rhinitis
- big data
- cell proliferation
- healthcare
- network analysis
- air pollution
- cystic fibrosis
- oxidative stress
- tyrosine kinase
- adipose tissue
- emergency department
- type diabetes
- machine learning
- gene expression
- genome wide analysis
- skeletal muscle
- deep learning
- insulin resistance
- transcription factor
- heat shock