Structure-retention relationships: chromatographic behaviour and properties of nucleotide-cation complexes

Retention modification of nucleic acid constituents in reversed-phase high-performance liquid chromatography

Secondary equilibria in reversed-phase liquid chromatography have been investigated as a means of enhancing selectivity and optimizing separations of nucleic acid constituents. The retention behavior of various nucleotides, nucleosides and modified compounds has been examined as a function of five different metal ion additives in the mobile phase: K+, Mg2+, Mn2+, Ni2+ and Zn2+. Complexation of the solute molecules with the metal ions changes the electronic structure and alters solute-solvent interactions. Alkali and alkaline earth metals bind primarily to phosphate groups while transition metals also interact with the N7 of purine bases. All nucleotides were found to be eluted very close to the void volume of the high-performance liquid chromatographic column without any metal additive, but retention increased as the concentration of a given cation increased. The transition metals were found to have the greatest effect, with affinities for nucleotide monophosphates on the order of 100 times greater than potassium, and 10 times that of magnesium. Differences in affinity based upon phosphate structure (i.e., cyclic vs. linear), phosphate position (e.g., 2'- vs. 3'-monophosphates), and base modification were also noted. The retention of most nucleosides, unlike the charged compounds, remained relatively constant as the ionic strength or type of cation was varied. Also, improvements were obtained in the resolution of some oligonucleotides with the addition of divalent ions to a potassium buffer mobile phase.

Pattern recognition used to investigate multivariate data in analytical chemistry

Pattern recognition and allied multivariate methods provide an approach to the interpretation of the multivariate data often encountered in analytical chemistry. Widely used methods include mapping and display, discriminant development, clustering, and modeling. Each has been applied to a variety of chemical problems, and examples are given. The results of two recent studies are shown, a classification of subjects as normal or cystic fibrosis heterozygotes and simulation of chemical shifts of carbon-13 nuclear magnetic resonance spectra by linear model equations.