Predicting the kinetics of peptide-antibody interactions using a multivariate experimental design of sequence and chemical space.

A multivariate approach involving modifications in peptide sequence and chemical buffer medium was used as an attempt to predict the kinetics of peptide-antibody interactions. Using a BIACORE system the kinetic parameters of the interaction of Fab 57P with 18 peptide analogues of an epitope of tobacco mosaic virus protein were characterized in 20 buffers of various pH values and containing different chemical additives (NaCl, urea, EDTA, KSCN and DMSO). For multivariate peptide design, three amino acid positions were selected because their modification was known to moderately affect binding, without abolishing it entirely. Predictive mathematical models were developed which related kinetic parameters (k(a) or k(d)) measured in standard buffer to the amino acid sequence of the antigen. ZZ-scales and a helix-forming-tendency (HFT) scale were used as descriptors of the physico-chemical properties of amino acids in the peptide antigen. These mathematical models had good predictive power (Q(2) = 0.49 for k(a), Q(2) = 0.73 for k(d)). For the non-essential residues under study, HFT and charge were found to be the most important factors that influenced the activity. Experiments in 19 buffers were performed to assess the sensitivity of the interactions to buffer composition. The presence of urea, DMSO and NaCl in the buffer influenced binding properties, while change in pH and the presence of EDTA and KSCN had no effect. The chemical sensitivity fingerprints were different for the various peptides. The results indicate that multivariate experimental design and mathematical modeling can be applied to the prediction of interaction kinetics.