Use of 13Calpha chemical shifts in protein structure determination.

J Phys Chem B

Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853-1301, USA.

Published: June 2007

A physics-based method aimed at determining protein structures by using NOE-derived distances together with observed and computed 13C chemical shifts is proposed. The approach makes use of 13Calpha chemical shifts, computed at the density functional level of theory, to obtain torsional constraints for all backbone and side-chain torsional angles without making a priori use of the occupancy of any region of the Ramachandran map by the amino acid residues. The torsional constraints are not fixed but are changed dynamically in each step of the procedure, following an iterative self-consistent approach intended to identify a set of conformations for which the computed 13Calpha chemical shifts match the experimental ones. A test is carried out on a 76-amino acid, all-alpha-helical protein; namely, the Bacillus subtilis acyl carrier protein. It is shown that, starting from randomly generated conformations, the final protein models are more accurate than an existing NMR-derived structure model of this protein, in terms of both the agreement between predicted and observed 13Calpha chemical shifts and some stereochemical quality indicators, and of similar accuracy as one of the protein models solved at a high level of resolution. The results provide evidence that this methodology can be used not only for structure determination but also for additional protein structure refinement of NMR-derived models deposited in the Protein Data Bank.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2597024PMC
http://dx.doi.org/10.1021/jp0683871DOI Listing

Publication Analysis

Top Keywords

chemical shifts
20
13calpha chemical
16
protein
9
protein structure
8
structure determination
8
torsional constraints
8
protein models
8
shifts
5
13calpha
4
shifts protein
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!