A general spectroscopic method is described that might be applied to validating amino acid sequences in peptides and protein fragments with a view to it becoming a routine procedure with which to characterize biotechnology drug products. The tripeptides are the L-enantiomers of GGA, GGH, GGI, GGL, GGF, GHG, LGG, and YGG. The simple procedure calls for their complexation with Cu(II) ion in strong aqueous base. Binding the first three residues in the sequence, beginning at the amine terminus, completes the coordination sphere of the Cu(II) ion, so duplication of the initial sequence from peptide to peptide could be an important limiting factor in determining the extent of differentiation that is possible. The analytical focus is the selectivity associated with the chirality properties of the peptides. Detection is by circular dichroism operating in the visible range. The eight analytes were chosen as representative of a series where the sequences are most similar and therefore potentially the most difficult to discriminate spectroscopically. All have just one chiral center. Using ellipticity data at all (n = 1500) wavelengths in the measured spectra, and two novel data reduction procedures, total discrimination among all eight analytes is achieved. The method has considerable potential for use in quality control of peptide and protein biotechnological drug forms, especially their enantiomeric purities.
The development of a convenient and very accurate procedure with which to discriminate among subsets of structurally similar peptides and proteins, and measure enantiomeric purities with very good accuracy, has been described in a series of recent articles. A factor preventing its general application to all peptide forms is that comparisons were originally limited to closed subsets of structurally similar types, e.g., dipeptides, tripeptides, and insulin drug forms. In the most recent of these articles, a modification to the method was described which did enable the comparisons to be extended between sets, in particular the di-and tripeptides. That same modification is extended even further in this article to include additional di- and tripeptides, glycylglycine oligomers, insulin drug forms, and neuropeptides. The same principal component analysis treatment used for data reduction and statistical comparisons in prior work enables the discrimination among 49 of the total of 51 analytes investigated.
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