Integrative spatiotemporal modeling of biomolecular processes: Application to the assembly of the nuclear pore complex

• 成果类型: Article
• 署名作者: Latham, Andrew P.; Zhang, Wanlu; Tempkin, Jeremy O. B.; Otsuka, Shotaro; Ellenberg, Jan; Sali, Andrej
• 署名单位: University of California System; University of California San Francisco; University of California System; University of California San Francisco; European Molecular Biology Laboratory (EMBL); Medical University of Vienna; University of Vienna; Vienna Biocenter (VBC); Max F. Perutz Laboratories (MFPL); Medical University of Vienna
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-12727
• DOI: 10.1073/pnas.2415674122
• 发表日期: 2025-03-18
• 关键词: molecular architecture; proteins; DYNAMICS; simulations; mechanisms; diffusion; kinetics; SYSTEM

摘要

Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. First, for each time point, a set of coarse models of compositional and structural heterogeneity is computed (heterogeneity models). Second, for each heterogeneity model, a set of static integrative structure models is computed (a snapshot model). Finally, these snapshot models are selected and connected into a series of trajectories that optimize the likelihood of both the snapshot models and transitions between them (a trajectory model). The method is demonstrated by application to the assembly process of the human nuclear pore complex in the context of the reforming nuclear envelope during mitotic cell division, based on live-cell correlated electron tomography, bulk fluorescence correlation spectroscopy-calibrated quantitative live imaging, and a structural model of the fully assembled nuclear pore complex. Modeling of the assembly process improves the model precision over static integrative structure modeling alone. The method is applicable to a wide range of time-dependent systems in cell biology and is available to the broader scientific community through an implementation in the open source Integrative Modeling Platform (IMP) software.