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.
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.