Protein sequential resonance assignments by combinatorial enumeration using 13C alpha chemical shifts and their (i, i-1) sequential connectivities.
The need for the structural characterization of proteins on a genomic scale has brought with it demands for new technology to speed the structure determination process. In NMR, one bottleneck is the sequential assignment of backbone resonances. In this paper, we explore the computational complexity of the sequential assignment problem using only 13C alpha chemical shift data and C alpha (i, i - 1) sequential connectivity information, all of which can potentially be obtained from a single three-dimensional NMR spectrum. Although it is generally believed that there is too much ambiguity in such data to provide sufficient information for sequential assignment, we show that a straightforward combinatorial search algorithm can be used to find correct and unambiguous sequential assignments in a reasonable amount of CPU time for small proteins (approximately 80 residues or smaller) when there is little missing data. The deleterious effect of missing or spurious peaks and the dependence on match tolerances is also explored. This simple algorithm could be used as part of a semi-automated, interactive assignment procedure, e.g., to test partial manually determined solutions for uniqueness and to extend these solutions.
Andrec
Michael
M
Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway 08854-8087, USA. andrec@lutece.rutgers.edu
Levy
Ronald M
RM
D000465:Algorithms; D000595:Amino Acid Sequence; D002247:Carbon Isotopes; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D011506:Proteins / Q000737:chemistry*; D013995:Time
D002247:Carbon Isotopes; D011506:Proteins