Uncovering Active Ingredients and Mechanisms of Pholiota adiposa in the Treatment of Alzheimer's disease: A Study Based on Network Pharmacology and Bioinformatics

Abstract

Background Pholiota adiposa is being studied for its health benefits in Alzheimer's disease, but the exact mechanism is unknown. We aim to identify active components using network pharmacology and Machine Learning to understand its effects on AD development through molecular docking and dynamics simulation. Methods Multiple databases and platforms, including TCMSP, CTD, SuperPred, SEA, GeneCards, Omim, STRING, and DAVID, were used to search for target protein interactions to treat AD. Gene enrichment analysis was done on the DAVID database, followed by GO and KEGG functional analysis on Hiplot. Potential targets were identified using degrees analysis in Cytoscape, and the Aging Atlas database was used to analyze genes related to aging among these potential targets.We used GEO databases to find treatment targets and performed molecular docking with AutoDock Vina. We used LASSO regression and random forest to identify main targets for AD treatment. Gromacs2022.3 was used for molecular dynamics simulations.. Results Pholiota adiposa may affect multiple genes and proteins, including STAT3, PRKCA, NF-κB1, CDK1, TERT, CFTR, PIK3R1, HIF1A, ITGB1, ITGB3, HSP90AA1, MTOR, ESR1, PRKAA1, and RXRA. It may inhibit protein phosphorylation and play a role in neuron membrane formation and RNA polymerase II activity.KEGG data analysis revealed that Pholiota adiposa targets cancer pathways, hypoxia signaling, and PI3K-Akt signaling. Promising targets like STAT3, PRKCA, NF-κB1, and CDK1 were identified, along with TERT targets associated with aging.The results of machine learning show that STAT3 and NFKB1 serve as pivotal targets in the diagnosis of Alzheimer's disease.Molecular docking revealed that carnosol, carnosic acid, and clovane diol are key components in Pholiota adiposa's effectiveness against AD.Binding carnosol condensed STAT3 protein, reducing surface area and forming hydrogen bonds. Conclusion Network pharmacology and Machine Learning studies suggest Pholiota adiposa may help manage Alzheimer's disease by impacting pathways and signaling mechanisms, showing potential in addressing neurodegenerative disorders.