An increasing number of cryo-electron microscopy (cryo-EM) density maps are being generated with suitable resolution to trace the protein backbone and guide sidechain placement. Generating and evaluating atomic models based on such maps would be greatly facilitated by independent validation metrics for assessing the fit of the models to the data. We describe such a metric based on the fit of atomic models with independent test maps from single particle reconstructions not used in model refinement. The metric provides a means to determine the proper balance between the fit to the density and model energy and stereochemistry during refinement, and is likely to be useful in determining values of model building and refinement metaparameters quite generally.
[Show abstract][Hide abstract] ABSTRACT: Natural protein assemblies have many sophisticated architectures and functions, creating nanoscale storage containers, motors and pumps. Inspired by these systems, protein monomers have been engineered to self-assemble into supramolecular architectures including symmetrical, metal-templated and cage-like structures. The complexity of protein machines, however, has made it difficult to create assemblies with both defined structures and controllable functions. Here we report protein assemblies that have been engineered to function as light-controlled nanocontainers. We show that an adenosine-5'-triphosphate-driven group II chaperonin, which resembles a barrel with a built-in lid, can be reprogrammed to open and close on illumination with different wavelengths of light. By engineering photoswitchable azobenzene-based molecules into the structure, light-triggered changes in interatomic distances in the azobenzene moiety are able to drive large-scale conformational changes of the protein assembly. The different states of the assembly can be visualized with single-particle cryo-electron microscopy, and the nanocages can be used to capture and release non-native cargos. Similar strategies that switch atomic distances with light could be used to build other controllable nanoscale machines.
[Show abstract][Hide abstract] ABSTRACT: While performing their functions, biological macromolecules often form large, dynamically changing macromolecular assemblies. Only a relatively small number of such assemblies have been accessible to the atomic-resolution techniques X-ray crystallography and NMR. Electron microscopy in conjunction with image reconstruction has become the preferred alternative for revealing the structures of such macromolecular complexes. However, for most assemblies the achievable resolution is too low to allow accurate atomic modeling directly from the data. Yet, useful models often can be obtained by fitting atomic models of individual components into a low-resolution reconstruction of the entire assembly. Several algorithms for achieving optimal fits in this context were developed recently, many allowing considerable degrees of flexibility to account for binding-induced conformational changes of the assembly components. This chapter describes the advantages and potential pitfalls of these methods and puts them into perspective with alternative approaches such as iterative modular fitting of rigid-body domains.
Advances in Experimental Medicine and Biology 01/2014; 805:137-155. DOI:10.1007/978-3-319-02970-2_6 · 1.96 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Cryo-electron microscopy is a central tool for studying the architecture of macromolecular complexes at subnanometer resolution. Interpretation of an electron microscopy map requires its computational integration with data about the structure's components from all available sources, notably atomic models. Selecting a protocol for EM density-guided integrative structural modeling depends on the resolution and quality of the EM map as well as the available complimentary datasets. Here, we review rigid, flexible, and de novo integrative fitting into EM maps and provide guidelines and considerations for the design of modeling experiments. Finally, we discuss efforts towards establishing unified criteria for map and model assessment and validation.
Current Opinion in Structural Biology 05/2014; 25C:118-125. DOI:10.1016/j.sbi.2014.04.001 · 7.20 Impact Factor
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