A model for predicting slopes S in the basic equation for the linear-solvent-strength theory of peptide separation by reversed-phase high-performance liquid chromatography.

A model for predicting the slope (S) in the fundamental equation of linear-solvent-strength theory for peptidic compounds was developed. Our approach is based on the novel assumption that three well-defined molecular descriptors: peptide length (N), charge (Z) and hydrophobicity index (HI) are the major contributors to the value of S. Following the definition of the model's variables, the retention of a number of Arg-terminated synthetic peptides was investigated under isocratic elution conditions (100 A pore size C18 phase, 0.1% trifluoroacetic acid as ion-pairing modifier). The peptide sequences were systematically designed to span the properties of the typical tryptic peptides that are analyzed in proteomic experiments. Experimental data show that slopes S increase with the independent increase in both peptide charge and peptide length when the two other parameters are held constant. The influence of peptide hydrophobicity is more complex: depending on peptide length and charge, stronger RP-HPLC retention can either decrease or increase the values of S. We postulate a general function to explain this behavior: S=C1 x Z(C2)+C3 x N(C4)+C5 x HI(C6)+C7/Z+C8/N+C9/HI+C10 x ZN+C11 x ZHI+C12 x NHI+B. A simple optimization using a "random walk" through parameter-space was used to determine the optimal coefficients compared to the measured S-values of 37 peptides. The model gives a approximately 0.97 R(2) correlation between the measured and predicted S-values: it was verified against previously published data on a human growth hormone protein tryptic digest and some synthetic analogues from that mixture.