Toward a computer assisted analysis of NOESY spectra: a multivariate data analysis of an RNA NOESY spectrum

A multivariate data-representation of a portion of the H-NOESY spectrum of an RNA octamer duplex was used to explore the possibility of using Principal Component Analysis and Partial Least Squares Discrimination for pattern recognition. In this case, it is found that the methods can: (i) distinguish slices containing signal from those containing only noise, (ii) locate slices containing overlapping signals, and (iii) in some cases to segregate slices with unique aspects such as those from terminal nucleotides, overlapping signals, purine-H8, pyrimidine-H6 and adenine-H2 containing slices. These properties can easily be included in a scheme to automate spectral analysis. The formulation described here does not distinguish patterns needed to automate sequential assignment of resonances in NOESY spectra of RNA.