Project Summary The human nuclear pore complex (NPC) consists of !1000 proteins of !30 different types. It is embedded in the nuclear envelope, and controls macromolecular transport between the nucleus and cytoplasm. Mutations in constituent proteins of the NPC have been connected to various human diseases including autoimmune dys- functions, neurological diseases, cardiovascular disorders, and cancer. While static structures of the NPC have been modeled, additional research is necessary to understand the assembly process of the NPC. An improved understanding of NPC assembly pathways may elucidate the crucial role the NPC has played in eukaryotic evo- lution and eventually decode the link between genetic alterations in NPC associated proteins and a variety of human diseases. However, the size of the NPC complex and timescales approaching one hour for assembly completion have posed challenges to previous studies. To overcome these difficulties, we propose to compute a spatiotemporal integrative model of human NPC assembly in collaboration with experimental characterization from Jan Ellenberg at the European Microbiology Laboratory, Heidelberg. To build our spatiotemporal integrative model of NPC assembly, we will model static snapshots of intermediate states throughout interphase NPC as- sembly, connect snapshots to produce assembly trajectories, and refine our model based on new experimental characterization. Our initial snapshots of NPC assembly will be modeled by a Bayesian posterior model density that explicitly scores our model based on its agreement with both experimental data and physical theories. Our model at each time step will be informed by the coarse-grained structure of the fully assembled NPC, atomic struc- tures of its components, physical theories, and cryo-electron tomograms and fluorescence correlation spectra of the intermediate states. Next, we will consider implicit connections between these modeled intermediate states to form trajectories. We will score this ensemble of trajectories based on both the probability of static structures sampled along the trajectory and the probability of the implicit transitions between static structures. Finally, we will verify our model through experimental collaboration with Dr. Ellenberg. Specifically, we will predict proteins crucial for rate limiting steps in NPC assembly, and then test our model’s predictions with new auxin-degradation experiments and correlative light-electron microscopy. If our model cannot sufficiently describe NPC assembly, we can refine our model by reflecting this new data as a new likelihood function, incorporating this likelihood into our Bayesian posterior model density, and reweighting our integrative model. This entire process will be re- peated iteratively until we reach sufficient agreement between simulation and experiment. The end result will be an experimentally informed and validated molecular model of NPC assembly. Moreover, we will have produced a gener...