A fragment based method for modeling of protein segments into cryo-EM density maps

Jochen Ismer,Peter W Hildebrand,Johanna K S Tiemann,Alexander S Rose

doi:10.1186/s12859-017-1904-5

Abstract

BackgroundSingle-particle analysis of electron cryo-microscopy (cryo-EM) is a key technology for elucidation of macromolecular structures. Recent technical advances in hardware and software developments significantly enhanced the resolution of cryo-EM density maps and broadened the applicability and the circle of users. To facilitate modeling of macromolecules into cryo-EM density maps, fast and easy to use methods for modeling are now demanded.ResultsHere we investigated and benchmarked the suitability of a classical and well established fragment-based approach for modeling of segments into cryo-EM density maps (termed FragFit). FragFit uses a hierarchical strategy to select fragments from a pre-calculated set of billions of fragments derived from structures deposited in the Protein Data Bank, based on sequence similarly, fit of stem atoms and fit to a cryo-EM density map. The user only has to specify the sequence of the segment and the number of the N- and C-terminal stem-residues in the protein. Using a representative data set of protein structures, we show that protein segments can be accurately modeled into cryo-EM density maps of different resolution by FragFit. Prediction quality depends on segment length, the type of secondary structure of the segment and local quality of the map.ConclusionFast and automated calculation of FragFit renders it applicable for implementation of interactive web-applications e.g. to model missing segments, flexible protein parts or hinge-regions into cryo-EM density maps.

Highlights

Single-particle analysis of electron cryo-microscopy is a key technology for elucidation of macromolecular structures
To test the applicability of our fragment based approach for modeling of loops, helices or β-sheets into Cryo electron microscopy (cryo-EM) density maps, we evaluated the gain in prediction quality of classical fragment modeling when cryo-EM densities are employed as experimental restraints
We find a significant improvement of prediction quality depending on length and secondary structure of a missing segment as well as on the quality of cryo-EM density maps

Summary

Introduction

Single-particle analysis of electron cryo-microscopy (cryo-EM) is a key technology for elucidation of macromolecular structures. Several methods have been established for structure prediction of protein segments, especially for the purpose of loop modeling [13, 16, 17] These methods can be divided into forcefield- [17] and fragment-based approaches [13]. Forcefield-based methods have the general advantage that, in principle, new polypeptide folds can be predicted. These tools are, computationally expensive [18], and are usually not applicable for instant visual control of the results in interactive web-applications. Fragment based methods allow for comparably fast assessment of results because searches leverage databases of pre-calculated fragments. The latter databases are typically either derived from third party databases of protein structures such as the Protein Data Bank (PDB) [12, 19] or from concatenating small fragments in a structural database [20, 21]

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Results

Conclusion