|
|
|
Sorting signals
from protein NMR spectra: SPI, a Bayesian protocol for uncovering spin
systems.
|
Grishaev A, Llinas
M.
Department of Chemistry, Carnegie Mellon
University,
Pittsburgh, PA 15213,
U.S.A.
Abstract:Grouping
of spectral peaks into J-connected spin systems is essential in the analysis
of macromolecular NMR data as it provides the basis for disentangling
chemical shift degeneracies. It is a mandatory step before resonance and
NOESY cross-peak identities can be established. We have developed SPI,
a computational protocol that scrutinizes peak lists from homo- and hetero-nuclear
multidimensional NMR spectra and progressively assembles sets of resonances
into consensus J- and/or NOE-connected spin systems. SPI estimates the
likelihood of nuclear spin resonances appearing at defined frequencies
given sets of cross-peaks measured from multi-dimensional experiments.
It quantifies spin system matching probabilities via Bayesian inference.
The protocol takes advantage of redundancies in the number of connectivities
revealed by suites of diverse NMR experiments, systematically tracking
the adequacy of each grouping hypothesis. SPI was tested on 2D homonuclear
and 2D/3D(15)N-edited data recorded from two protein modules, the col 2
domain of matrix metalloproteinase-2 (MMP-2) and the kringle 2 domain of
plasminogen, of 60 and 83 amino acid residues, respectively. For these protein
domains SPI identifies approximately 95% unambiguous resonance frequencies,
a relatively good performance vis-a-vis the reported 'manual' (interactive)
analyses.Abbreviations and Acronyms: SPI, SPin Identification; BMRB, BioMagResBank
(Madison, WI). PMID: 12522308 [PubMed - in process]
J
Biomol NMR 2002 Nov;24(3):203-13
|
|