Automated detection of disulfide bridges in electron density maps using linear discriminant analysis Academic Article uri icon


  • The ability to recognize disulfide bridges automatically in electron density maps would be useful to both protein crystallographers and automated model-building programs. A computational method is described for recognizing disulfide bridges in uninterpreted maps based on linear discriminant analysis. For each localized spherical region in a map, a vector of rotation-invariant numeric features is calculated that captures various aspects of the local pattern of density. These features values are then input into a linear equation, with coefficients computed to optimize discrimination of a set of training examples (disulfides and non-disulfides), and compared with a decision threshold. The method is shown to be highly accurate at distinguishing disulfides from non-disulfides in both the original training data and in real (experimental) electron density maps of other proteins.

published proceedings


author list (cited authors)

  • Ioerger, T. R.

citation count

  • 3

complete list of authors

  • Ioerger, TR

publication date

  • February 2005