Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the 3-dimensional electron density of a protein, as it would be deter- mined by cryo-EM or X-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density- driven molecular dynamics methodologies that determine only the best map-model fits, our work uses the recently developed Multi-Map methodology to monitor concerted move- ments within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along reaction coordinates derived from electron densities can serve to induce conformational transitions between known intermediates. The simulated pathways appear reversible, with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution (~5 Å) density information coupled to comparatively large structural transitions. Practical considerations for generating transitions with multiple intermediate atomic density distributions are also discussed.

中文翻译：

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数据指导的多图变量，用于分子电影的整体优化

以数据为指导的集体变量驱动分子动力学模拟提供了一种有前途的策略，可以从以结构为中心的实验中恢复热力学信息。在这里，蛋白质的3维电子密度（通过冷冻EM或X射线晶体学确定）被用来同时获得构象转变和精细原子结构的自由能成本。与以前的密度驱动的分子动力学方法仅确定最佳的图模型拟合不同，我们的工作使用最近开发的多图方法来监视平衡，非平衡和增强采样模拟中的协调运动。沿着Multi-Map变量的选定值构造所有原子的集合体，可以同时估计平均性质，以及对这些平均值做出贡献的结构的实际空间优化。使用增加大小的三种蛋白质，我们证明了沿着源自电子密度的反应坐标的偏向模拟可以用来诱导已知中间体之间的构象转变。模拟的路径看起来是可逆的，具有最小的滞后，并且仅需要低分辨率的密度信息即可指导过渡。诱发的跃迁还可以产生自由能差异的估计值，可以将其与实验可观察物和种群分布直接比较。与在蛋白质数据库中找到的模型相比，改进后的模型质量更好。我们发现使用中等分辨率（〜5Å）的密度信息与相对较大的结构转换结合可获得具有实验自由能差异的最佳定量协议。还讨论了生成具有多个中间原子密度分布的跃迁的实际考虑。