title: CASA: an efficient automated assignment of protein mainchain NMR data using an ordered tree search algorithm.
abstract: Rapid analysis of protein structure, interaction, and dynamics requires fast and automated assignments of 3D protein backbone triple-resonance NMR spectra. We introduce a new depth-first ordered tree search method of automated assignment, CASA, which uses hand-edited peak-pick lists of a flexible number of triple resonance experiments. The computer program was tested on 13 artificially simulated peak lists for proteins up to 723 residues, as well as on the experimental data for four proteins. Under reasonable tolerances, it generated assignments that correspond to the ones reported in the literature within a few minutes of CPU time. The program was also tested on the proteins analyzed by other methods, with both simulated and experimental peaklists, and it could generate good assignments in all relevant cases. The robustness was further tested under various situations.
authors.affiliation: Department of Physics, University of Michigan, Ann Arbor, MI 48109-1120, USA.
authors.forename: Jianyong
authors.initials: J
authors.lastname: Wang
authors.forename: Tianzhi
authors.initials: T
authors.lastname: Wang
authors.forename: Erik R P
authors.initials: ER
authors.lastname: Zuiderweg
authors.forename: Gordon M
authors.initials: GM
authors.lastname: Crippen
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D004578:Electron Spin Resonance Spectroscopy; D008969:Molecular Sequence Data; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D011506:Proteins