Activation of S1PR1 by Ponesimod for Multiple Sclerosis Therapy: Uncovering MAPK and PI3K Pathway Mechanisms and Repurposing Potential

Yue Ran, Xiao Nan Niu, Ying Jie Wang, Wei Hai Xu, Jian Hua Liang*, Yan Xu*, Shi Lu Chen*, Ming Jia Yu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Multiple sclerosis (MS), affecting over 2 million people globally, primarily causes neurological disability in individuals under 40. This autoimmune disorder involves the immune system attacking the myelin sheath in the central nervous system. Sphingosine-1-phosphate receptor 1 (S1PR1) is a promising therapeutic target, with approved drugs like ponesimod acting as S1PR1 agonists. However, the exact mechanism of ponesimod's action on S1PR1 and its therapeutic effects in MS remains unclear. Our study, combining metadynamics, single-cell transcriptomics, and drug repurposing, shows that ponesimod binds to S1PR1, causing the W2696.48 amino acid to flip downward. This flip weakens interactions within the phosphorylation-independent binding (PIF) motif while maintaining the N3077.49-F2656.44 interaction, activating Gi signaling. The downstream effects primarily involve the MAPK/ERK and PI3K-Akt pathways, which inhibit lymphocyte migration to lymph nodes, a crucial factor in ponesimod's clinical efficacy. Single-cell transcriptomic analysis further elucidates the regulatory network and pathways modulated by ponesimod in MS. Notably, due to potential hepatotoxicity, we identified valproic acid (VPA) as a potential adjunct therapy through drug repurposing. VPA reduces hepatotoxicity and demonstrates efficacy in treating MS in animal studies. This research provides valuable insights into ponesimod's mechanism in MS treatment and highlights the potential of drug repurposing to improve MS therapy.

Original languageEnglish
JournalChemistry - A European Journal
DOIs
Publication statusAccepted/In press - 2025
Externally publishedYes

Keywords

  • ADMET
  • computer drug design
  • molecular dynamics simulation
  • network pharmacology
  • single-cell transcriptome

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