TR&D Project 4. The Imaging Stage: Multiscale Spatiotemporal Modeling of Macromolecular Systems in Cellular Neighborhoods

项目摘要 TR&D项目4.建模阶段：大分子系统的多尺度时空建模 在蜂窝小区 在这里，我们关注的建模（i）静态结构的大分子机器和（ii） 涉及这些机器的动态过程。这些模型的准确性、精确度和完整性可以 原则上可以通过使用所有可用的信息（即综合建模）来改进，包括来自各种 实验、物理理论、统计分析和先验模型。我们将在以下几个方面进行改进： 综合建模，调整这些改进的生物系统和数据中描述的TR&Ds，DBPs， 和C& SP，然后在我们的开源集成建模平台（IMP）包中实现它们。到 提高大分子复合物结构的整体模拟，我们将：（i）发展整体的 建模依赖于近原子分辨率低温电子显微镜密度图;（ii）开发明确的原子- 化学交联的分辨率表示;（iii）开发一个评分函数，用于 来自多个物种的相关复合物;以及（iv）开发用于评估 模型对冷冻EM单粒子图像。提高大分子动力学的一体化建模水平 系统，我们将：（一）估计动力学速率常数的变化，在结构和组成的基础上的时间- 依赖cryo-EM图像;和（ii）开发长的大分子过程的综合建模， 时空数据的满意度。最后，我们还将通过支持 IMP的其他开发人员和用户。

PROJECT SUMMARY TR&D Project 4. The Modeling Stage: Multiscale Spatiotemporal Modeling of Macromolecular Systems in Cellular Neighborhoods Here, we are concerned with the modeling of (i) static structures of large macromolecular machines and (ii) dynamic processes involving these machines. The accuracy, precision, and completeness of these models can in principle be improved by using all available information (ie, integrative modeling), including from various experiments, physical theories, statistical analyses, and prior models. We will improve several aspects of integrative modeling, tuning these improvements to the biological systems and data described in TR&Ds, DBPs, and C&SPs, and then implementing them in our open-source Integrative Modeling Platform (IMP) package. To improve integrative modeling of structures of macromolecular complexes, we will: (i) develop integrative modeling relying on near-atomic resolution cryo-electron microscopy density maps; (ii) develop explicit atomic- resolution representation of chemical cross-links; (iii) develop a scoring function for integrative modeling of related complexes from multiple species; and (iv) develop a sensitive Bayesian scoring function for assessing a model against cryo-EM single particle images. To improve integrative modeling of dynamics of macromolecular systems, we will: (i) estimate kinetic rate constants for changes in structure and composition based on time- dependent cryo-EM images; and (ii) develop integrative modeling of long macromolecular processes by satisfaction of spatiotemporal data. Finally, we will also leverage our method development efforts by supporting other developers and users of IMP.