Computational protocol: Atomic model of a non-enveloped virus reveals pH sensors for a coordinated process of cell entry

Similar protocols

Protocol publication

[…] From a total of 3309 recorded micrographs, 1630 were selected and 12,513 images of individual particles were boxed for image processing. The under focus values of these micrographs were determined to range between 0.8μm to 4.5μm using using CTFFIND. The 2x binned data set was used in the global search while the original data set was used in the local refinement. The orientation and center parameters of each of the 12,513 particle images were first determined by a global search by maximizing the cross-correlation coefficient of the particle image with projections generated from the input density model. After each cycle, three-dimensional (3D) reconstructions were carried out using a GPU-based reconstruction program, G3D, and the effective resolution was estimated and used as a resolution cutoff in the next alignment cycle until no further improvement could be obtained. Then, we refined these orientation and center parameters iteratively until no further improvement could be obtained. The final map was reconstructed using the top 5,008 (40%) of the 12,513 particles based on their phase residuals using Frealign. The quality of the maps of the receptor binding protein VP2 and the membrane penetration protein VP5 were further improved by averaging the three VP2 and six VP5 monomers in each asymmetric unit.The effective resolution of the whole virion is estimated to be ~3.5 Å based on FSC (≥0.143), and the resolution for the averaged VP2 and VP5 densities is estimated to be better than 3.5 Å based on the R-factor criterion–the R factor given by Phenix reaches 0.5 at 3.5 Å for both VP2 and VP5 densities (). These estimated resolutions are consistent with the observed structural features of the density maps ( and –). The capsid and averaged maps were filtered to the spatial frequency of 1/(3.4 Å) and sharpened with a reverse B-factor of −150Å2. This B-factor was chosen with a trial-and-error method based on optimization of noise level, backbone density continuity, and emergence of side-chain densities. Visualization and segmentation of density maps were done with UCSF Chimera. [...] Based on the averaged density maps of VP2 and VP5, we first built initial Cα and full atom models for VP2 and VP5 with Coot without referring to any existing models of other proteins. The initial full atom models were regularized by constraining Ramachandran geometry and secondary structures in Coot.These initial full atom models were iteratively refined using structural information of both amplitude and phase (from Fourier transformation of the cryoEM maps) in the following three steps: The first step (automatic) was performed in Phenix using Ramachandran restraint. The second step (automatic) was also performed in Phenix to regularize the new model. To regularize the model, hydrogens were added to all atoms of the model from the last refinement, followed by regularization and removal of hydrogens. The latest models were refined iteratively until no further improvement was apparent based on both Ramachandran geometry and R-factors. Then in the third (manual) step, amino acid residues with invalid Ramachandran backbone geometries were identified and manually corrected in Coot. This process of automatic and manual model refinement steps was iterated until no further improvement on both Ramachandran geometry and R-factors was evident. […]

Pipeline specifications

Software tools CTFFIND, Frealign, PHENIX, UCSF Chimera, Coot
Applications cryo-EM, Protein structure analysis
Organisms Bluetongue virus
Diseases HIV Infections
Chemicals Zinc