<p>Extracellular acidification opens the Na<sup>+</sup>-selective acid-sensing ion channels (ASICs), which are key players in neuronal excitation, learning, pain perception, fear conditioning, and ischemic stroke-induced cell death. Their agonists – protons – can theoretically bind to almost any titratable residue, complicating the study of ASIC’s activation mechanism. To identify proton binding sites, we developed an ensemble-based computational approach combining Poisson–Boltzmann electrostatics with multiple short MD simulations to calculate pKa values across ASIC1a structures of closed, open, and desensitized states. This method preserves local ion environments and captures solvation-sensitive conformational variability. Predicted pH-sensing residues were conservatively mutated and functionally tested. Residues whose mutation altered pH sensitivity were further analyzed via a palette of substitutions and mathematical modeling, revealing the key side-chain features governing their role. This computational and experimental strategy identified H73 of the wrist, K211 and E242 of the acidic pocket and E375, E413 and E418 of the palm as pH sensors for activation, and E242, E375 and E413 as pH sensors for steady-state desensitization, and revealed how residues of these clusters contribute to channel function. Our findings offer a comprehensive map of pH sensing in ASIC1a and introduce a robust method for investigating pH-dependent mechanisms in other proteins.</p>

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Molecular mechanisms and hotspots of pH sensing in ASIC1a revealed by computational and functional analysis

  • Olivier Bignucolo,
  • Ophélie Molton,
  • Ivan Gautschi,
  • Stephan Kellenberger

摘要

Extracellular acidification opens the Na+-selective acid-sensing ion channels (ASICs), which are key players in neuronal excitation, learning, pain perception, fear conditioning, and ischemic stroke-induced cell death. Their agonists – protons – can theoretically bind to almost any titratable residue, complicating the study of ASIC’s activation mechanism. To identify proton binding sites, we developed an ensemble-based computational approach combining Poisson–Boltzmann electrostatics with multiple short MD simulations to calculate pKa values across ASIC1a structures of closed, open, and desensitized states. This method preserves local ion environments and captures solvation-sensitive conformational variability. Predicted pH-sensing residues were conservatively mutated and functionally tested. Residues whose mutation altered pH sensitivity were further analyzed via a palette of substitutions and mathematical modeling, revealing the key side-chain features governing their role. This computational and experimental strategy identified H73 of the wrist, K211 and E242 of the acidic pocket and E375, E413 and E418 of the palm as pH sensors for activation, and E242, E375 and E413 as pH sensors for steady-state desensitization, and revealed how residues of these clusters contribute to channel function. Our findings offer a comprehensive map of pH sensing in ASIC1a and introduce a robust method for investigating pH-dependent mechanisms in other proteins.