Uncovering active ingredients and mechanisms of Pholiota adiposa in the treatment of Alzheimer's disease based on network pharmacology and bioinformatics.

ABSTRACT: Pholiota adiposa is recognized for its health benefits, particularly in Alzheimer's disease (AD), but its molecular mechanism remains elusive. Our study employs network pharmacology and machine learning to uncover its therapeutic potential. We constructed a network of AD-relevant target proteins using databases like TCMSP, CTD, and GeneCards, and performed gene enrichment and functional analysis with DAVID, GO, and KEGG via Hiplot. Targets were identified through Cytoscape's degree analysis and the Aging Atlas database for aging-related genes. Clinical targets were confirmed with GEO, and molecular docking was executed using AutoDock Vina. LASSO regression and random forest algorithms were applied for target model selection, and molecular dynamics simulations were run with Gromacs2022.3. O

SUBMITTER: Xiaoying M 

PROVIDER: S-EPMC12314080 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature