Refinement of protein structures by iterative comparative modeling and CryoEM density fitting.
We developed a method for structure characterization of assembly components by iterative comparative protein structure modeling and fitting into cryo-electron microscopy (cryoEM) density maps. Specifically, we calculate a comparative model of a given component by considering many alternative alignments between the target sequence and a related template structure while optimizing the fit of a model into the corresponding density map. The method relies on the previously developed Moulder protocol that iterates over alignment, model building, and model assessment. The protocol was benchmarked using 20 varied target-template pairs of known structures with less than 30% sequence identity and corresponding simulated density maps at resolutions from 5A to 25A. Relative to the models based on the best existing sequence profile alignment methods, the percentage of C(alpha) atoms that are within 5A of the corresponding C(alpha) atoms in the superposed native structure increases on average from 52% to 66%, which is half-way between the starting models and the models from the best possible alignments (82%). The test also reveals that despite the improvements in the accuracy of the fitness function, this function is still the bottleneck in reducing the remaining errors. To demonstrate the usefulness of the protocol, we applied it to the upper domain of the P8 capsid protein of rice dwarf virus that has been studied by cryoEM at 6.8A. The C(alpha) root-mean-square deviation of the model based on the remotely related template, bluetongue virus VP7, improved from 8.7A to 6.0A, while the best possible model has a C(alpha) RMSD value of 5.3A. Moreover, the resulting model fits better into the cryoEM density map than the initial template structure. The method is being implemented in our program MODELLER for protein structure modeling by satisfaction of spatial restraints and will be applicable to the rapidly increasing number of cryoEM density maps of macromolecular assemblies.
Topf
Maya
M
Department of Biopharmaceutical Sciences, California Institute for Quantitative Biomedical Research, QB3, 1700 4th Street, Suite 503B, University of California at San Francisco, San Francisco, CA 94143-2552, USA.
Baker
Matthew L
ML
Marti-Renom
Marc A
MA
Chiu
Wah
W
Sali
Andrej
A
D000595:Amino Acid Sequence; D020285:Cryoelectron Microscopy; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010942:Plant Viruses / Q000737:chemistry; D011487:Protein Conformation; D012984:Software; D014764:Viral Proteins / Q000737:chemistry* / Q000235:genetics
D014764:Viral Proteins