Molecular Recognition of Moringa oleifera Active Compounds for Stunted Growth Prevention Using Network Pharmacology and Molecular Modeling Approach

利用网络药理学和分子建模方法对辣木活性化合物进行分子识别,以预防生长发育迟缓

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Abstract

In this study, network pharmacology was used to analyze the active compounds of Moringa oleifera as food supplements for stunted growth prevention. Thirty-eight important proteins were discovered that may be strongly related to stunting. Those proteins were uploaded to several online tool platforms in order to determine the shared genes' pathways. Six pathways were identified that may be correlated with human growth. Furthermore, ligands for molecular docking analysis were retrieved from the top 5 active substances discovered through experimental investigation. In the meantime, the first-degree rank based on the protein-protein interaction (PPI) topological analysis was utilized to choose albumin protein (ALB) as a receptor. Our docking results showed that every ligand binds to the receptors, indicating that they can bind to the binding site of the ALB protein to form a complex formation. Further, MD simulation was used to verify the stability of the ligand in complex with the protein in the TIP3P water model. Based on the validation parameters, our results suggested that all models achieved a stable phase along the simulation. Additionally, the MM-GBSA method was used to calculate the binding energies of all models. Ligands 2 and 4 have strong binding to the binding pocket of ALB, followed by ligands 3, 5, and 2, suggesting that those ligands could be promising food supplements that can be utilized for the prevention of stunted growth in children.

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