NDLI: The NOESY jigsaw: automated protein secondary structure and main-chain assignment from sparse, unassigned NMR data

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The NOESY jigsaw: automated protein secondary structure and main-chain assignment from sparse, unassigned NMR data

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The NOESY jigsaw: automated protein secondary structure and main-chain assignment from sparse, unassigned NMR data

Content Provider	ACM Digital Library
Author	Berardi, Marcelo J. Kelley, John J. Bushweller, John H. Widge, Alik Bailey-Kellogg, Chris Donald, Bruce Randall
Abstract	High-throughput, data-directed computational protocols for Structural Genomics (or Proteomics) are required in order to evaluate the protein products of genes for structure and function at rates comparable to current gene-sequencing technology. This paper presents the JIGSAW algorithm, a novel high-throughput, automated approach to protein structure characterization with nuclear magnetic resonance (NMR). JIGSAW applies graph algorithms and probabilistic reasoning techniques, enforcing first-principles consistency rules in order to overcome a 5-10% signal-to-noise ratio. It consists of two main components: (1) graph-based secondary structure pattern identification in unassigned heteronuclear NMR data, and (2) assignment of spectral peaks by probabilistic alignment of identified secondary structure elements against the primary sequence. JIGSAW's deferment of assignment until after secondary structure identification differs greatly from traditional approaches, which begin by correlating peaks among dozens of experiments. By deferring assignment, JIGSAW not only eliminates this bottleneck, it also allows the number of experiments to be reduced from dozens to four, none of which requires $^{13}$ C-labeled protein. This in turn dramatically reduces the amount and expense of wet lab molecular biology for protein expression and purification, as well as the total spectrometer time to collect data.Our results for three test proteins demonstrate that we are able to identify and align approximately 80 percent of α-helical and 60 percent of β-sheet structure. JIGSAW is very fast, running in minutes on a Pentium-class Linux workstation. This approach yields quick and reasonably accurate (as opposed to the traditional slow and extremely accurate) structure calculations, utilizing a suite of graph analysis algorithms to compensate for the data sparseness. JIGSAW could be used for quick structural assays to speed data to the biologist early in the process of investigation, and could in principle be applied in an automation-like fashion to a large fraction of the proteome.
Starting Page	33
Ending Page	44
Page Count	12
File Format	PDF
ISBN	1581131860
DOI	10.1145/332306.332323
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2000-04-08
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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