Kinetic and affinity predictions of a protein-protein interaction using multivariate experimental design.

We measured the influence of 14 mutations and 5 environmental variables (buffer perturbation) on the association and dissociation rate of a camel single domain antibody (cAb-Lys3) interacting with hen egg white lysozyme using a surface plasmon resonance-based biosensor. Based on this data set, we constructed quantitative predictive models for both kinetic (k(a) and k(d)) constants as for the affinity constant (K(d)). Mutations, after parameterization by quantitative descriptors, and buffers were selected using multivariate experimental design. These models were able to predict the corresponding parameters of four new variants of cAb-Lys3. Moreover, the models provide insights to the important chemical aspects of the interacting residues, which are difficult to deduce from the crystal structure. Our approach provides useful physicochemical information of protein-protein interactions in general. The information obtained from this kind of analysis complements and goes beyond that of conventional methods like alanine scanning and substitution by closely related amino acids. The mathematical modeling may contribute to a rational approach in the optimization of bio-molecules of biotechnological interest.