Unknown

Dataset Information

0

Automated assignment in selectively methyl-labeled proteins.


ABSTRACT: Specific methyl labeling schemes and transverse relaxation optimized spectroscopy (TROSY) has extended the molecular size range for the application of NMR spectroscopy to very large proteins (up to approximately 1 MDa). Existing strategies for resonance assignment of methyl groups in large systems are based on NMR spectra recorded on smaller fragments and mutants. This is very time-consuming, and chemical shift changes due to mutation or truncation can often complicate interpretation. We have developed a new automated procedure able to rapidly assign the majority of methyl groups in very large proteins, without recourse to mutagenesis or truncated fragments (http://nmr.bc.ic.ac.uk/map-xs/). We demonstrate the effectiveness of this approach on the 300 kDa, ILV-labeled proteasome (alpha(7)alpha(7)) for which excellent spectra have been previously recorded. Of the observed methyl groups, 99% can be correctly assigned in a matter of minutes without manual intervention.

SUBMITTER: Xu Y 

PROVIDER: S-EPMC3518906 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature

altmetric image

Publications

Automated assignment in selectively methyl-labeled proteins.

Xu Yingqi Y   Liu Minhao M   Simpson Peter J PJ   Isaacson Rivka R   Cota Ernesto E   Marchant Jan J   Yang Daiwen D   Zhang Xiaodong X   Freemont Paul P   Matthews Stephen S  

Journal of the American Chemical Society 20090701 27


Specific methyl labeling schemes and transverse relaxation optimized spectroscopy (TROSY) has extended the molecular size range for the application of NMR spectroscopy to very large proteins (up to approximately 1 MDa). Existing strategies for resonance assignment of methyl groups in large systems are based on NMR spectra recorded on smaller fragments and mutants. This is very time-consuming, and chemical shift changes due to mutation or truncation can often complicate interpretation. We have de  ...[more]

Similar Datasets

| S-EPMC3212433 | biostudies-literature
| S-EPMC4254601 | biostudies-literature
| S-EPMC11320577 | biostudies-literature
| S-EPMC8667806 | biostudies-literature
| S-EPMC6820720 | biostudies-literature
| S-EPMC5764113 | biostudies-literature
| S-EPMC9742323 | biostudies-literature
| S-EPMC6554063 | biostudies-literature
| S-EPMC4288728 | biostudies-literature
| S-EPMC4452424 | biostudies-literature