PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 14, 2026Current Pharmaceutical Design0 citations

Mechanistic Insights into the Qingge Formula for the Treatment of Alzheimer's Disease: A Network Pharmacology and Molecular Docking Study

View Full Paper
JMJing MaTLTao LiuFLFangzhou Liu

Key Points

  • This research aims to uncover the therapeutic mechanisms of Qingge Formula for Alzheimer's disease using computational approaches.
  • Identified active components and targets through TCMSP, Swiss ADME, and GeneCards databases.
  • Conducted PPI networks, GO, and KEGG analyses followed by molecular docking studies.
  • Analyzed binding affinities of key components to core targets.
  • Core targets included EGFR and others related to neuroinflammation.
  • Identified 222 GO terms and 65 KEGG pathways associated with the treatment.
  • Molecular docking demonstrated strong binding of components, particularly to EGFR.

Abstract

Introduction: Alzheimer’s disease (AD) affects millions globally. This study explores the therapeutic mechanisms of Qingge Formula (QGF) against AD using network pharmacology and molecular docking. Methods: Active components and targets were identified via TCMSP, Swiss ADME, and GeneCards databases. PPI networks, GO, and KEGG analyses were performed, followed by molecular docking. Results: Core targets included PTGS2, EGFR, ESR1, STAT3, and SRC. GO identified 222 terms; KEGG revealed 65 pathways. Molecular docking revealed that the six key components bind to the core targets with energetically favorable conformations, among which SRC showed the highest affinity for all the components. Discussion: QGF likely modulates neuroinflammation, immunity, and synaptic plasticity pathways, with SRC as a crucial target. Conclusion: QGF demonstrates multi-component, multi-target therapeutic potential against AD.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Ma et al. (2026) studied this question.

synapsesocial.com/papers/69b4b9fb18185d8a39802493https://doi.org/10.2174/0113816128403988251202073700
Ask AI
Helpful
Bookmark
Share
View Full Paper