title: SESAME: a least-squares approach to the evaluation of protein structures computed from NMR data.
abstract: A method is proposed for defining a probability distribution on an ensemble of protein conformations from a 2D NOE spectrum, while at the same time back-calculating the experimental spectrum from the ensemble. This enables one to assess the relative quality and significance of the conformations, and to test the consistency of the ensemble as a whole with the experimental spectrum. The method eliminates the need to integrate the cross-peak intensities and is surprisingly insensitive to random noise in the spectrum. In this communication, these advantages are demonstrated by applying the method to simulated data, for which the correct result is already known.
authors.affiliation: Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115.
authors.forename: J X
authors.initials: JX
authors.lastname: Yang
authors.forename: T F
authors.initials: TF
authors.lastname: Havel
mesh_terms: D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008433:Mathematics; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D011506:Proteins