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

Voltage-gated sodium (Na) 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 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 family members. Recent advances in cryo-electron microscopy have resolved nearly all human Na channels, providing valuable insights into their structure and function. However, limitations persist in fully capturing the complex conformational states that underlie Na channel gating and modulation. This study explores the capability of AlphaFold2 to sample multiple Na channel conformations and assess AlphaFold Multimer's accuracy in modeling interactions between the Na α-subunit and its protein partners, including auxiliary β-subunits and calmodulin. We enhance conformational sampling to explore Na channel conformations using a subsampled multiple sequence alignment approach and varying the number of recycles. Our results demonstrate that AlphaFold2 models multiple Na channel conformations, including those from experimental structures, new states not yet experimentally identified, and potential intermediate states. Furthermore, AlphaFold Multimer models Na complexes with auxiliary β-subunits and calmodulin with high accuracy, and the presence of protein partners significantly alters the conformational landscape of the Na α-subunit. These findings highlight the potential of deep learning-based methods to expand our understanding of Na channel structure, gating, and modulation, with significant implications for future drug discovery efforts.