AUTHOR=Chen Peng-Yu , Han Lin-Tao 

TITLE=Study on the molecular mechanism of anti-liver cancer effect of Evodiae fructus by network pharmacology and QSAR model

JOURNAL=Frontiers in Chemistry

VOLUME=Volume 10 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/chemistry/articles/10.3389/fchem.2022.1060500

DOI=10.3389/fchem.2022.1060500

ISSN=2296-2646

ABSTRACT=Evodiae Fructus (EF) is the dried, near ripe fruit of Euodia rutaecarpa (Juss.)Benth in Rutaceae. Numerous studies have demonstrated its anti-liver cancer properties. However, The molecular mechanism of EF against liver cancer and its structure-activity connection still require clarification. We utilized network pharmacology and a QSAR (2- and 3-dimensional) model to study the anti-liver cancer effect of EF. First, by using network pharmacology to screen the active substances and targets of EF, we investigated the signaling pathways involved in the anti-liver cancer actions of EF. The 2D-QSAR pharmacophore model was then used to predict the pIC50 values of compounds. The hiphop method was used to create an ideal 3D-QSAR pharmacophore model for the prediction of EF compounds. Finally, molecular docking was used to validate the rationality of the pharmacophore, and molecular dynamics was used to disclose the stability of the compounds by assessing the trajectories in 10 ns using RMSD, RMSF, Rg, and hydrogen bonding metrics. In total, 27 compounds were acquired from the TCMSP and TCM-ID databases, and 45 intersection targets were compiled using Venn diagrams. Network integration analysis was used in this study to identify SRC as a primary target. Key pathways were discovered by KEGG pathway analysis, including PD-L1 expression and PD-1 checkpoint pathway, EGFR tyrosine kinase inhibitor resistance, and ErbB signaling pathway. Using a 2D-QSAR pharmacophore model and the MLR approach to predict chemical activity, ten highly active compounds were found. Two hydrophobic features and one hydrogen bond acceptor feature in the 3D-QSAR pharmacophore model were validated by training set chemicals. The results of molecular docking revealed that 10 active compounds had better docking scores with SRC and were linked to residues via hydrogen and hydrophobic bonds. Molecular dynamics was used to show the structural stability of obacunone, beta-sitosterol, and sitosterol.