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

Voltage-gated sodium (Na _V ) channels are vital regulators of electrical activity in excitable cells, playing critical roles in generating and propagating action potentials. Given their importance in physiology, Na _V channels are key therapeutic targets for treating numerous conditions, yet developing subtype-selective drugs remains challenging due to the high sequence and structural conservation among Na _V family members. Recent advances in cryo-electron microscopy have resolved nearly all human Na _V channels, providing valuable insights into their structure and function. However, limitations persist in fully capturing the complex conformational states that underlie Na _V channel gating and modulation. This study explores the capability of AlphaFold2 to sample multiple Na _V channel conformations and assess AlphaFold Multimer’s accuracy in modeling interactions between the Na _V α-subunit and its protein partners, including auxiliary β-subunits and calmodulin. We enhance conformational sampling to explore Na _V channel conformations using a subsampled multiple sequence alignment approach and varying the number of recycles. Our results demonstrate that AlphaFold2 models multiple Na _V channel conformations, including those from experimental structures, new states not yet experimentally identified, and potential intermediate states. Furthermore, AlphaFold Multimer models Na _V complexes with auxiliary β-subunits and calmodulin with high accuracy, and the presence of protein partners significantly alters the conformational landscape of the Na _V α-subunit. These findings highlight the potential of deep learning-based methods to expand our understanding of Na _V channel structure, gating, and modulation, with significant implications for future drug discovery efforts.