The assignment of the protein backbone resonances is necessary and sufficient for protein structure determination based on residual dipolar couplings, mapping of protein–protein interaction sites based on chemical shift mapping, and the determination of backbone dynamics on the subnanosecond and micro-second time scale. Although the potential for automation of assignments based on triple resonance has been realized, most NMR assignment processes are still performed by hand. This is mostly due to the fact that available automated assignment programs require a certain set of spectra, cannot deal with noisy, incomplete spectra, or with spectra of proteins in multiple slowly interchanging conformations, and run into convergence problems for the assignment of larger proteins.
University of Michigan researchers have introduced a new depth-first ordered tree search method of automated assignment, CASA, which uses hand-edited peak-pick lists of a flexible number of triple resonance experiments. The computer program was tested on 13 artificially simulated peak lists for proteins up to 723 residues, as well as on the experimental data for 4 proteins. It generated assignments that correspond to ones reported in the literature within a few minutes of CPU time. The program has also been tested on the proteins analyzed by other methods, with both simulated and experimental peaklists, and it could generate good assignments in all relevant cases.
Applications and Advantages
- Automated assignment of protein mainchain-nl-NMR data
- Fast and accurate assignment or data
- Robust software; able to handle proteins with-nl-incomplete NMR spectra or show multiple-nl-assignment pathways slow conformational-nl-exchange regions