Lopez-Mateos Diego, Narang Kush, Yarov-Yarovoy Vladimir
Department of Physiology and Membrane Biology, University of California School of Medicine, Davis, CA 95616.
Biophysics Graduate Group, University of California School of Medicine, Davis, CA 95616.
bioRxiv. 2024 Oct 18:2024.10.15.618559. doi: 10.1101/2024.10.15.618559.
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.
电压门控钠（Na）通道是可兴奋细胞电活动的重要调节因子，在动作电位的产生和传播中发挥关键作用。鉴于其在生理学中的重要性，Na通道是治疗多种疾病的关键治疗靶点，但由于Na家族成员之间高度的序列和结构保守性，开发亚型选择性药物仍然具有挑战性。冷冻电子显微镜技术的最新进展解析了几乎所有人类Na通道，为其结构和功能提供了有价值的见解。然而，在完全捕捉Na通道门控和调节背后的复杂构象状态方面仍然存在局限性。本研究探索了AlphaFold2对多种Na通道构象进行采样的能力，并评估了AlphaFold Multimer在模拟Naα亚基与其蛋白质伙伴（包括辅助β亚基和钙调蛋白）之间相互作用时的准确性。我们通过使用二次采样的多序列比对方法和改变循环次数来增强构象采样，以探索Na通道构象。我们的结果表明，AlphaFold2可以模拟多种Na通道构象，包括来自实验结构的构象、尚未通过实验鉴定的新状态以及潜在的中间状态。此外，AlphaFold Multimer能够高精度地模拟Na与辅助β亚基和钙调蛋白的复合物，并且蛋白质伙伴的存在显著改变了Naα亚基的构象格局。这些发现凸显了基于深度学习的方法在扩展我们对Na通道结构、门控和调节的理解方面的潜力，对未来的药物发现工作具有重要意义。
