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

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

BMC Bioinformatics

Institute of Medical Physics and Biophysics, University Medicine Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Published: November 2017

AI Article Synopsis

Article Abstract

Background: Single-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.

Results: Here 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.

Conclusion: Fast 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5683378PMC
http://dx.doi.org/10.1186/s12859-017-1904-5DOI Listing

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