title: Histogram-based scoring schemes for protein NMR resonance assignment.
abstract: In NMR protein structure determination, after the resonance peaks have been identified and chemical shifts from peaks across multiple spectra have been grouped into spin systems, associating these spin systems to their host residues is the key toward the success of structural information extraction and thus the key to the success of the structure calculation. To achieve accurate enough structure calculation, a near complete and accurate assignment is a prerequisite. There are two pieces of information that can be used into the assignment, one of which is the adjacency information among the spin systems and the other is the signature information of the spin systems. The signature information reflects the fact that, generally speaking, for one type of amino acid residing in a specific local structural environment, the chemical shifts for the atoms inside the amino acid fall into some very narrow distinct ranges. In most of the existing work, normal distributions are assumed with means and standard deviations statistically collected from the available data. In this paper, we followed a simple yet effective histogram-based way to estimate for every spin system the probability that its host is a certain type of amino acid residing in a certain type of secondary structure. We used two combinations of chemical shifts to demonstrate the effectiveness of this type of histogram-based scoring schemes.
authors.affiliation: Protein Engineering Network Centers of Excellence, Bioinformatics Research Group, Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada. xiangwan@cs.ualberta.ca
authors.forename: Xiang
authors.initials: X
authors.lastname: Wan
authors.forename: Theodore
authors.initials: T
authors.lastname: Tegos
authors.forename: Guohui
authors.initials: G
authors.lastname: Lin
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008956:Models, Chemical; D008958:Models, Molecular; D015233:Models, Statistical; D008969:Molecular Sequence Data; D009716:Numerical Analysis, Computer-Assisted; D011487:Protein Conformation; D011506:Proteins / Q000032:analysis* / Q000737:chemistry* / Q000145:classification; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins