MANI-LACS offers a new approach to NMR reference correction and outlier identification that achieves excellent results using only residue specific chemical shift assignment.
Server description from MANI-LACS homepage
- MANI-LACS is a component in a suite of tools for high-throughput structure determination using NMR.
- MANI-LACS with extended laboratory management functionality is available through the SESAME software.
- MANI-LACS currently achieves correct reference correction at a comparable level to tools that require structure. A database of corrected references is availabe.
- A service offered by the National Magnetic Resonance Facility at Madison.
- NOTE: Input file format is NMR-STAR format.
Wang L, Eghbalnia HR, Bahrami A, Markley JL.
National Magnetic Resonance Facility at Madison, Biochemistry Department, 433 Babcock Drive, 53706, Madison, WI, USA
J Biomol NMR. 2005 May;32(1):13-22.
Statistical analysis reveals that the set of differences between the secondary shifts of the alpha- and beta-carbons for residues i of a protein (Deltadelta(13)C(alpha) (i)- Deltadelta(13)C(beta) (i)) provides the means to detect and correct referencing errors for (1)H and (13)C nuclei within a given dataset. In a correctly referenced protein dataset, linear regression plots of Deltadelta(13)C(alpha) (i),Deltadelta(13)C(beta) (i), or Deltadelta(1)H(alpha) (i) vs. (Deltadelta(13)C(alpha) (i)- Deltadelta(13)C(beta) (i)) pass through the origin from two directions, the helix-to-coil and strand-to-coil directions. Thus, linear analysis of chemical shifts (LACS) can be used to detect referencing errors and to recalibrate the (1)H and (13)C chemical shift scales if needed. The analysis requires only that the signals be identified with distinct residue types (intra-residue spin systems). LACS allows errors in calibration to be detected and corrected in advance of sequence-specific assignments and secondary structure determinations. Signals that do not fit the linear model (outliers) deserve scrutiny since they could represent errors in identifying signals with a particular residue, or interesting features such as a cis-peptide bond. LACS provides the basis for the automated detection of such features and for testing reassignment hypotheses. Early detection and correction of errors in referencing and spin system identifications can improve the speed and accuracy of chemical shift assignments and secondary structure determinations. We have used LACS to create a database of offset-corrected chemical shifts corresponding to nearly 1800 BMRB entries: 300 with and 1500 without corresponding three-dimensional (3D) structures. This database can serve as a resource for future analysis of the effects of amino acid sequence and protein secondary and tertiary structure on NMR chemical shifts.