Computational Insights into Ribavirin's Potential Impact on Major Depressive Disorder: A Network Toxicology Study

Area of Science:

• Computational biology
• Neuropharmacology
• Systems biology

Background:

• Ribavirin is an antiviral medication with potential neuropsychiatric side effects.
• Major Depressive Disorder (MDD) is a complex condition with poorly understood molecular underpinnings.
• Identifying shared molecular pathways between drugs and diseases can reveal mechanisms of action and side effects.

Purpose of the Study:

• To identify molecular targets common to ribavirin and MDD.
• To generate hypotheses on ribavirin's impact on neuropsychiatric safety and MDD mechanisms.
• To prioritize key molecular players for further experimental validation.

Main Methods:

• Integrated ribavirin targets and MDD genes using multiple databases.
• Performed Venn analysis to find overlapping candidates.
• Constructed and analyzed a protein-protein interaction network.
• Conducted functional enrichment (GO, KEGG), cell type annotation, molecular docking, and transcriptomic validation.

Main Results:

• Identified five core targets (CCND1, SIRT1, NFKB1, EP300, MAPK1) linking ribavirin and MDD.
• Enrichment analyses revealed MDD-relevant pathways like HIF-1 signaling and ferroptosis.
• Core targets were associated with neurons and immune cells; docking suggested direct interactions.
• Transcriptomic data supported the overlap and altered expression of core targets in MDD.

Conclusions:

• Ribavirin may interact with key biological axes of MDD through identified core targets.
• Findings support assessing neuropsychiatric risks and monitoring depressive symptoms in patients using ribavirin.
• Results are hypothesis-generating, guiding future experimental and clinical research.