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

项目总结 研发项目4.建模阶段：大分子体系的多尺度时空建模 在蜂窝社区 在这里，我们关注(I)大分子机器的静态结构和(Ii)的建模。 涉及这些机器的动态过程。这些模型的准确性、精确度和完备性可以 原则上，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、统计分析和先前的模型。我们要做好几个方面的工作 综合建模，将这些改进调整到在《R&D》、《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。至 改进大分子络合物结构的综合模拟，我们将：(I)发展综合模拟 基于近原子分辨率冷冻电子显微镜密度图的建模；(Ii)开发显式原子- 化学交联链的分辨率表示；(Iii)开发了用于综合建模的评分函数 来自多个物种的相关络合物；以及(Iv)开发一个敏感的贝叶斯评分函数来评估 针对低温电磁单粒子图像的模型。完善大分子动力学的综合建模 我们将：(I)根据时间估算结构和组成变化的动力学速率常数。 依赖的低温电子显微镜图像；以及(Ii)通过以下方式开发长大分子过程的综合模型 时空数据的满意度。最后，我们还将通过支持以下方式利用我们的方法开发工作 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.