PEM-fitter: A coarse-grained method to validate protein candidate models

Kamal Al Nasr, Christopher Jones, Feras Yousef, Ruba Jebril

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


The volumetric images produced by Cryo-Electron Microscopy (cryo-EM) technique are used to model macromolecular assemblies and machines. De novo protein modeling uses these images to computationally model the structure of the molecules. Many candidate conformations are usually generated during the intermediate step. Conventionally, each of these candidates is evaluated by time-consuming approaches such as potential energy. We introduce an initial version of a geometrical screening method that uses the skeleton of the cryo-EM images to evaluate candidate structures. The aim of this method is to reduce the number of native-like candidate conformations and, therefore, reduce the time required for structural evaluation by energy calculations. A test of two datasets was performed. The first dataset contains 10 proteins and shows that our method can successfully detect the correct native structure for the given skeleton among a set of different protein structures. The second dataset contains 12 proteins and shows that our method can filter slightly modified decoy conformations of the same protein. The efficiency of the method is also reported.

Original languageEnglish (US)
Pages (from-to)21-32
Number of pages12
JournalJournal of Computational Biology
Issue number1
StatePublished - Jan 2018
Externally publishedYes


  • Cryo-electron microscopy
  • Iterative closest point
  • Protein evaluation
  • Protein modeling
  • Skeleton

ASJC Scopus subject areas

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics


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