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 Å 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 × Z^C2 + C3 × N^C4 + C5 × HI^C6 + C7/Z + C8/N + C9/HI + C10 × ZN + C11 × ZHI + C12 × 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 ∼0.97 R² 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.