Protein structure elucidation from minimal NMR data: the CLOUDS approach.

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TitleProtein structure elucidation from minimal NMR data: the CLOUDS approach.
Publication TypeJournal Article
Year of Publication2005
AuthorsGrishaev, A, Llinás, M
JournalMethods Enzymol
Date Published2005
KeywordsBayes Theorem, Computer Simulation, Data Interpretation, Statistical, Magnetic Resonance Spectroscopy, Monte Carlo Method, Protein Structure, Tertiary, Proteins, Software

In this chapter we review automated methods of protein NMR data analysis and expand on the assignment-independent CLOUDS approach. As presented, given a set of reliable NOEs it is feasible to derive a spatial H-atom distribution that provides a low-resolution image of the protein structure. In order to generate such a list of unambiguous NOEs, a probabilistic assessment of the NOE identities (in terms of frequency-labeled H-atom sources) was developed on the basis of Bayesian inference. The methodology, encompassing programs SPI and BACUS, provides a list of "clean" NOEs that does not hinge on prior knowledge of sequence-specific resonance assignments or a preliminary structural model. As such, the combined SPI/BACUS approach, intrinsically adaptable to include 13C- and/or 15N-edited experiments, affords a useful tool for the analysis of NMR data irrespective of whether the adopted structure calculation protocol is assignment-dependent.

Alternate JournalMeth. Enzymol.
PubMed ID15808224
Grant ListGM67964 / GM / NIGMS NIH HHS / United States
HL29409 / HL / NHLBI NIH HHS / United States