Integrating Parallel-Bias Metadynamics-Metainference and Relaxation Dispersion NMR to Resolve Hidden Conformational...

Area of Science:

• Biophysics
• Computational Chemistry
• Structural Biology

Background:

• Conformational dynamics of toxin inhibitors significantly influence ion channel affinity.
• The multidimensional energy landscapes of toxins are largely unexplored, hindering a complete understanding of their interactions.

Purpose of the Study:

• To define the thermodynamics and kinetics of the Hui1 toxin at atomistic resolution.
• To explore the multidimensional energy landscape of a de novo three-disulfide toxin targeting K+-channels.
• To establish a computational framework for mapping coupled disulfide and backbone dynamics in toxins.

Main Methods:

• Parallel-bias metadynamics-metainference (PBMetaD) simulations utilizing 48 replicas for extensive sampling (16.2 μs).
• Analysis of three disulfide χ3 dihedrals as collective variables to generate a 3D free-energy surface.
• 15N R1ρ relaxation dispersion NMR measurements to validate kinetic parameters.
• Key Interaction Finder (KIF) approach to analyze residue interaction networks.

Main Results:

• A fully converged 3D free-energy surface for Hui1, revealing eight distinct conformers (four low-energy, four high-energy).
• Identified rota-isomerization of Cys3-Cys35 as the rate-determining step in conformational changes.
• NMR data confirmed distinct residue clusters exhibiting intermediate and faster exchange processes, correlating with specific conformations.
• Discovered that Cys17-Cys32 conformation influences interaction networks and accessibility of key residues for channel interaction.

Conclusions:

• PBMetaD is a powerful framework for mapping coupled disulfide and backbone dynamics in toxins.
• Specific Hui1 conformers and their associated interactions are critical for K+-channel recognition.
• The study provides atomistic insights into toxin-channel interactions, crucial for drug design and understanding channel function.