Exploring voltage-gated sodium channel conformations and protein-protein interactions using AlphaFold2

Area of Science:

• Structural Biology
• Computational Biology
• Pharmacology

Background:

• Voltage-gated sodium (NaV) channels are crucial for electrical signaling in excitable cells.
• NaV channels are therapeutic targets, but drug development is hindered by conserved structures.
• Cryo-EM has advanced NaV channel structure determination, yet capturing dynamic conformational states remains a challenge.

Purpose of the Study:

• To evaluate AlphaFold2's ability to predict multiple NaV channel conformations.
• To assess AlphaFold Multimer's accuracy in modeling NaV channel complexes with protein partners.
• To investigate how protein partners influence NaV channel conformational dynamics.

Main Methods:

• Utilized AlphaFold2 for conformational sampling of NaV channels.
• Employed a subsampled multiple sequence alignment approach and varied recycles for enhanced sampling.
• Applied AlphaFold Multimer to model interactions between NaV α-subunits, β-subunits, and calmodulin.

Main Results:

• AlphaFold2 successfully modeled known and novel NaV channel conformations, including potential intermediate states.
• AlphaFold Multimer accurately predicted NaV channel complexes with auxiliary β-subunits and calmodulin.
• Protein partners significantly altered the conformational landscape of the NaV α-subunit.

Conclusions:

• Deep learning methods like AlphaFold2 offer powerful tools for exploring NaV channel structure and dynamics.
• Accurate modeling of NaV channel complexes provides insights into channel modulation.
• These findings have significant implications for advancing NaV channel-targeted drug discovery.