CombLabel: rational design of optimized sequence-specific combinatorial labeling schemes. Application to backbone assignment of membrane proteins with low stability.

Abstract

Assignment of backbone resonances is a necessary initial step in every protein NMR investigation. Standard assignment procedure is based on the set of 3D triple-resonance (1H-13C-15N) spectra and requires at least several days of experimental measurements. This limits its application to the proteins with low stability. To speed up the assignment procedure, combinatorial selective labeling (CSL) can be used. In this case, sequence-specific information is extracted from 2D spectra measured for several selectively 13C,15N-labeled samples, produced in accordance with a special CSL scheme. Here we review previous applications of the CSL approach and present novel deterministic 'CombLabel' algorithm, which generates CSL schemes minimizing the number of labeled samples and their price and maximizing assignment information that can be obtained for a given protein sequence. Theoretical calculations revealed that CombLabel software outperformed previously proposed stochastic algorithms. Current implementation of CombLabel robustly calculates CSL schemes containing up to six samples, which is sufficient for moderately sized (up to 200 residues) proteins. As a proof of concept, we calculated CSL scheme for the first voltage-sensing domain of human Nav1.4 channel, a 134 residue four helical transmembrane protein having extremely low stability in micellar solution (half-life ~ 24h at 45°C). Application of CSL doubled the extent of backbone resonance assignment, initially obtained by conventional approach. The obtained assignment coverage (~ 50%) is sufficient for ligand screening and mapping of binding interfaces.