Protein sequential resonance assignments by combinatorial enumeration using 13Cα chemical shifts and their (i, i-1) sequential connectivities

被引:17
作者
Andrec, M [1 ]
Levy, RM [1 ]
机构
[1] Rutgers State Univ, Dept Chem & Biol Chem, Piscataway, NJ 08854 USA
关键词
computational complexity; high throughput; structural genomics; tree search; triple-resonance;
D O I
10.1023/A:1020236105735
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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 (13)Calpha chemical shift data and Calpha (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 fo uniqueness and to extend these solutions.
引用
收藏
页码:263 / 270
页数:8
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