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find Keyword "molecular docking" 3 results
  • Application of an R-group Search Strategy into Three-dimensional Quantitative Structure-activity Relationship of HEA β-secretase Inhibitors and Molecular Virtual Screening

    The β-secretase is one of prospective targets against Alzheimer's disease (AD). A three-dimensional quantitative structure-activity relationship (3D-QSAR) model of Hydroethylamines (HEAs) as β-secretase inhibitors was established using Topomer CoMFA. The multiple correlation coefficient of fitting, cross validation and external validation were r2=0.928, qloo2=0.605 and rpred2=0.626, respectively. The 3D-QSAR model was used to search R groups from ZINC database as the source of structural fragments. As a result, a series of R groups with relatively high activity contribution was obtained to design a total of 15 new compounds, with higher activity than that of the template molecule. The molecular docking was employed to study the interaction mode between the new compounds as ligands and β-secretase as receptors, displaying that hydrogen bond and hydrophobicity played important roles in the binding affinity between the new compounds and β-secretase. The results showed that Topomer CoMFA and Topomer Search could be effectively used to screen and design new molecules of HEAs as β-secretase inhibitors, and the designed compounds could provide new candidates for drug design targeting AD.

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  • Study on the potential molecular mechanism of Rhodiola crenulata for type 2 diabetes mellitus and Alzheimer’s disease based on network pharmacology and molecular docking

    Objective To explore the potential molecular mechanism of Rhodiola crenulata (RC) for type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD) by network pharmacology and molecular docking. Methods The target genes of T2DM and AD, the effective active components and targets of RC were identified through multiple public databases during March to August, 2022. The main active components and core genes of RC anti T2DM-AD were screened. The key genes were enrichment analyzed by gene ontology function and Kyoto gene and Kyoto Encyclopedia of Genes and Genomes. AutoDock Vina was used for molecular docking and binding energy calculation. Results A total of 5189 T2DM related genes and 1911 AD related genes were obtained, and the intersection result showed that there were 1418 T2DM-AD related genes. There were 48 active components of RC and 617 corresponding target genes. There were 220 crossing genes between RC and T2DM-AD. The main active components of RC anti T2DM-AD included kaempferol, velutin, and crenulatin. The key genes for regulation include ESR1, EGFR, and AKT1, which were mainly enriched in the hypoxia-inducible factor-1 signal pathway, estrogen signal pathway, and vascular endothelial growth factor signal pathway. The docking binding energies of the main active components of RC and key gene molecules were all less than −1.2 kcal/mol (1 kcal=4.2 kJ). Conclusions RC may play a role in influencing T2DM and AD by regulating the hypoxia-inducible factor-1 signaling pathway, estrogen signaling pathway, and vascular endothelial growth factor signaling pathway.

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  • Exploration of the potential mechanisms of Da Chaihu Decoction in treating acute pancreatitis based on network pharmacology and molecular docking

    Objective To identify the therapeutic targets and molecular mechanisms of Da Chaihu Decoction in the treatment of acute pancreatitis (AP) based on network pharmacology and molecular docking. Methods From March to May 2024, the active compounds and targets of Da Chaihu Decoction were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and the targets related to AP were obtained from the GeneCards database. The intersection of these yielded the common targets of Da Chaihu Decoction for AP treatment. The STRING platform was used to construct a protein-protein interaction network, and Cytoscape 3.9.1 software was employed for network topology analysis to identify core targets and compounds. The Metascape platform was applied for gene ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, with bubble charts generated using Python 3.8 software. Molecular docking was conducted using AutoDock 1.5.6 software to predict binding affinities between core compounds and targets. Results A total of 84 common targets of Da Chaihu Decoction for AP treatment were identified. The core compounds included quercetin, β-sitosterol, kaempferol, luteolin, and baicalein. The key proteins included AKT1, B-cell leukemia/lymphoma 2 (BCL2), Jun proto-oncogene (JUN), interleukin 1 Beta (IL1B), and nuclear factor kappa B subunit 1 (NFKB1), all of which were enriched in pathways such as lipid and atherosclerosis, PI3K-Akt signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, tumor necrosis factor (TNF) signaling pathway, and apoptosis. The binding energies of some core compounds with key proteins were below –5.0 kJ/mol. Conclusion Da Chaihu Decoction may exert anti-inflammatory and anti-apoptotic effects in AP by modulating key protein targets, including AKT1, BCL2, JUN, IL1B, and NFKB1, within pathways such as lipid and atherosclerosis, PI3K-Akt signaling, MAPK signaling, TNF signaling, and apoptosis.

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