Higher-dimensional Fourier transform (FT) NMR (Ernst et al. 1987; Cavanagh et al. 1996) is a key analytical technique in natural sciences but suffers from two major drawbacks. First, the minimal measurement time of an N-dimensional (ND) FT NMR experiment, which is constrained by the need to sample N-1 indirect dimensions, may exceed by far the measurement time required to achieve workable signal-to-noise (S/N) ratios. In this "sampling limited data collection regime" (Szyperski et al. 2002) valuable NMR spectrometer time is used to sample the indirect dimensions and not for achieving sufficient "signal averaging." Second, the comparably low digital resolution in the indirect dimensions limits the accuracy of the measurement of NMR parameters such as chemical shifts, ttese drawbacks have fostered the development of G-matrix FT (GFT) NMR as a technique for rapid sampling of multidimensional NMR data (Kim and Szyperski 2003). In GFT NMR, the conventional sampling of an ND time domain subspace is replaced by phase-sensitive joint sampling of all N chemical shift evolution periods spanning this subspace. tte ND FT is replaced by a "G-matrix" transformation for editing chemical shift multiplets arising from the joint sampling, followed by a ID FT. Since the chemical shifts are encoded in the chemical shifts in a redundant manner, greatly increased accuracy for the measurement of the shifts can be obtained. As a result, the GFT NMR data acquisition scheme affords highly precise 4D, 5D or higher-dimensional NMR spectral information within a few hours or less, and enables one to accurately adjust measurement times to sensitivity requirements, ttis makes GFT NMR particularly attractive for high-throughput structure determination in structural genomics (Montelione et al. 2000), and opens new perspectives to study dynamic processes such as slow protein folding and systems exhibiting a high degree of chemical shift degeneracy.

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