标题： 带有通用神经网络势的钾离子通道模拟 显示英文标题

标题： A potassium ion channel simulated with a universal neural network potential

摘要： 钾离子通道是生物学中的关键组成部分。 它们以惊人的速度和选择性传导钾离子穿过细胞膜。 理解它们是如何做到这一点的是神经科学、医学和材料科学应用中至关重要的。 然而，关于它们使用的机制仍有许多基本问题未解决，部分原因是由于所需的模拟规模和复杂性，计算建模极其困难。 在这里，使用Orb-D3，一种最近发布的通用神经网络势能，对KcsA钾离子通道的选择性过滤器（SF）进行了模拟。 观察到一种之前未报告的氢键，即SF中的水与SF入口处的T75羟基侧链之间的氢键。 这种氢键似乎稳定了SF中的水，使得水与钾离子共同通过SF进行软敲击传输机制，具有合理的电导率（80 $\pm$ 20 pS）。 在SF的新位置也观察到了酰胺主链翻转。 这项工作展示了通用神经网络势能在提供关于复杂系统的问题见解方面的潜力，这些问题远远超出其训练数据分布范围。 显示英文摘要

摘要： Potassium ion channels are critical components of biology. They conduct potassium ions across the cell membrane with remarkable speed and selectivity. Understanding how they do this is crucially important for applications in neuroscience, medicine, and materials science. However, many fundamental questions about the mechanism they use remain unresolved, partly because it is extremely difficult to computationally model due to the scale and complexity of the necessary simulations. Here, the selectivity filter (SF) of the KcsA potassium ion channel is simulated using Orb-D3, a recently released universal neural network potential. A previously unreported hydrogen bond between water in the SF and the T75 hydroxyl side group at the entrance to the SF is observed. This hydrogen bond appears to stabilize water in the SF, enabling a soft knock-on transport mechanism where water is co-transported through the SF with a reasonable conductivity (80 $\pm$ 20 pS). Carbonyl backbone flipping is also observed at new sites in the SF. This work demonstrates the potential of universal neural network potentials to provide insights into previously intractable questions about complex systems far outside their training data distribution.