ePoster

APETX2-DERIVED PEPTIDES AS MODULATORS OF ACID-SENSING ION CHANNELS

Dahui Wangand 8 co-authors

Universitat de Barcelona

FENS Forum 2026 (2026)
Barcelona, Spain
Board PS01-07AM-442

Presentation

Date TBA

Board: PS01-07AM-442

Poster preview

APETX2-DERIVED PEPTIDES AS MODULATORS OF ACID-SENSING ION CHANNELS poster preview

Event Information

Poster Board

PS01-07AM-442

Abstract

Acid-sensing ion channels (ASICs) are voltage-independent cation channels activated by extracellular protons and implicated in pain and other CNS functions. Among ASIC subunits, ASIC3 is considered a key sensor of acid-evoked pain and contributes to inflammatory pain in models of rheumatoid arthritis and osteoarthritis. Identifying new ASIC3 modulators and defining their mechanisms may enable strategies to counteract maladaptive ASIC3 activity in chronic pain. Here, we report APETx2-based short peptides guided by the APETx2–ASIC3 interaction. Computational modelling and docking predicted two APETx2 regions mediating ASIC3 binding. We designed peptides targeting the ASIC3–APETx2 interface and identified the hexapeptide YWFYRP, which inhibits the transient component of rat ASIC3 currents while markedly prolonging the inactivation time constant. The effect was state dependent: pre-application before acidic stimulation (closed state) produced both effects, whereas co-application during acidic stimulation (open state) abolished the slowing of inactivation while still reducing peak current amplitude. To assess selectivity, we expressed other rat ASIC subunits in CHO cells. YWFYRP strongly inhibited ASIC1a, with no detectable effect on ASIC1b or ASIC2a. To test activity under native conditions, we recorded acid-evoked ASIC-like currents from primary rat dorsal root ganglion (DRG) neurons in the presence of YWFYRP and used PcTx1 and APETx2 to pharmacologically dissect subunit contributions. YWFYRP reduced peak current amplitude in DRG neurons without an apparent change in inactivation kinetics. Overall, these data highlight the utility of computational approaches for discovering novel ASIC-targeting peptides and support further optimization toward improved modulators for pathophysiological conditions.

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