FINDMOL: automated identification of macromolecules in electron-density maps | Academic Article individual record
abstract

Automating the determination of novel macromolecular structures via X-ray crystallographic methods involves building a model into an electron-density map. Unfortunately, the conventional crystallographic asymmetric unit volumes are usually not well matched to the biological molecular units. In most cases, the facets of the asymmetric unit cut the molecules into a number of disconnected fragments, rendering interpretation by the crystallographer significantly more difficult. The FINDMOL algorithm is designed to quickly parse the arrangement of trace points (pseudo-atoms) derived from a skeletonized electron-density map without requiring higher level prior information such as sequence information or number of molecules in the asymmetric unit. The algorithm was tested with a variety of density-modified maps computed with medium- to low-resolution data. Typically, the resulting volume resembles the biological unit. In the remaining cases the number of disconnected fragments is very small. In all examples, secondary-structural elements such as alpha-helices or beta-sheets are easily identifiable in the defragmented arrangement. FINDMOL can greatly assist a crystallographer during manual model building or in cases where automatic model building can only build partial models owing to limitations of the data such as low resolution and/or poor phases.

author list (cited authors)
McKee, E. W., Kanbi, L. D., Childs, K. L., Grosse-Kunstleve, R. W., Adams, P. D., Sacchettini, J. C., & Ioerger, T. R.
publication date
2005
keywords
  • AlgorithmsAlpha-globulinsCluster AnalysisCrystallography, X-RayElectronsMacromolecular SubstancesModels, Molecular