Multi-Resolution Docking Methods for Electron Microscopy



 DESCRIPTION (provided by applicant): In the past decade, significant progress was made in 3D imaging of macromolecular assemblies via electron microscopy and in the development of computational algorithms that relate the resulting volumetric maps to atomic-resolution structures. The overall goal of the proposed research is to further develop computational fitting and validation tools for electron microscopy (EM). We intend to establish new modeling, visualization, and simulation techniques that would serve as bridges between atomic structures and EM densities. The proposed multi-scale software will aid in the routine determination of large-scale structures of biomolecular assemblies and in the validation of structural models that will be deposited to public databases such as the Protein Data Bank (PDB) and the EM Data Bank (EMDB). Key questions to be addressed include the following: (i) How can one improve, validate, and disseminate well-established matching algorithms for intermediate-resolution (8-15 Å) cryo-electron microscopy? (ii) How can one accurately identify and segment geometric features of subcellular assemblies in low-resolution (4-5 nm) cryo-electron tomograms or in focused ion beam milling of resin-embedded specimen blocks? (iii) Given the recent increase in resolution achieved with direct detection cameras, how can one systematically characterize high-resolution (2-10 Å) density patterns and validate atomic models based on local signatures in the data? We will adapt a new modeling paradigm for these studies, namely simultaneous refinement of multiple subunits. This approach is based on a "systems" perspective because biological assemblies exhibit "emergent behavior" in the spatial domain, that is, the whole is more than the sum of its parts. The new paradigm, in combination with docking protocols, improves model accuracy and opens the door to new global fitting applications in the above three areas. In addition, we will use statistical analysis and machine learning of local signatures to complement the global strategies. The collaborative efforts supported by this grant will include refinement of cytoskeletal filaments, molecular motors, chromatin fibers, and hair cell stereocilia. The algorithmic and methodological developments will be distributed freely through the established internet-based mechanisms used by the Situs and Sculptor packages.