Efficient calculation of exact fine structure isotope patterns via the multidimensional Fourier transform

The isotope patterns of unknown analytes provide information that can be of great value in their identification as part of a mass spectrometry experiment. Determining the range of compounds that are consistent with an empirically observed isotope pattern requires, as an initial step, the calculation of the theoretical isotope patterns of all feasible candidate formulas, and this is not a trivial mathematical task. While algorithms based on the Fourier transform have been used for almost two decades to perform such calculation efficiently, they have hitherto not been able to provide the exact sets of masses and abundances that constitute the fundamental isotope pattern. This article presents a new approach to the treatment of such calculations, which involves arranging and manipulating the isotope patterns of distinct elements as multidimensional data structures. This enables the use of the multidimensional Fourier transform to calculate isotope patterns with an accuracy that is limited only by the errors of floating point arithmetic. The algorithm is both highly efficient and very easy to implement in many programming environments. An open-source implementation of the algorithm in the R programming language will be made publicly available and is also available upon request.