Computer optimized spectral aliasing in the indirect dimension of 1H-13C heteronuclear 2D NMR experiments.: A new algorithm and examples of applications to small molecules

A new algorithm for optimizing spectral width in the indirect dimension of heteronuclear 2D experiments is introduced. It takes a list of carbon chemical shifts as input and calculates the optimal spectral width and number of time increments to use in the carbon dimension of 2D experiments such as HSQC, HMBC, etc. When using optimized conditions where signals are better distributed along the carbon dimension, the number of time increments needed to resolve all of the signals is reduced by one to two orders of magnitude. This decreases the experimental time by the same factors and makes the acquisition of spectra such as HSQC-TOCSY, HSQC-NOESY, etc. more practical. The new algorithm allows users to limit the maximal t(1) evolution time when relaxation is a concern, and can take lists of carbons that do not need to be resolved. For any carbon, insights regarding the position of signals in the proton dimension increase the efficiency of the optimization by allowing the overlap of pairs of carbons with incompatible proton dispersions. The application of a second optimization using a fully-resolved spectrum as a source of proton dispersion for the carbons allows the number of time increments to be reduced further. Application to cyclosporine A shows that the time taken to acquire fully resolved HSQC spectra can be 126 times less than would be required in a full-width spectrum with the same resolution. The most interesting applications concern experiments where series of HSQC-based experiments have to be acquired, for example in relaxation time measurements. It is shown that the acquisition of quickly acquired series of selective-TOCSY-HSQC can facilitate assignment in carbohydrates. Computer-optimized spectral aliasing (COSA) generally requires no modification of the pulse sequence and can therefore be easily applied by non specialists. (C) 2007 Elsevier Inc. All rights reserved.