Climbing up and down binding landscapes: a high-throughput study of mutational effects in protein-protein complexes.

Quantifying the effects of various mutations on binding free energy is crucial to our understanding of protein evolution and would greatly facilitate protein engineering studies. Yet, measuring changes in binding free energy (ΔΔG_bind) remains a tedious task that requires expression of each mutant, its purification, and affinity measurements. We developed a new approach that allows us to quantify ΔΔG_bind for thousands of protein mutants in one experiment. Our protocol combines Yeast Surface Display technology, Next Generation Sequencing, and a few experimental ΔΔG_bind data points on purified proteins to generate ΔΔG_bind values for the remaining multiple mutants of the same protein complex. Using this methodology, we map the single- and double-mutant binding landscape of four homologous complexes between trypsin-like proteases and their inhibitor BPTI. While structurally very similar, the four complexes span more than nine orders of magnitude in binding affinity. The comprehensive data was used to compare the four binding landscapes with each other, to dissect the significance of each binding interface position in binding, and to analyze the additivity/cooperativity effects of single mutations.Our results bring invaluable insights on evolution of protein-protein interactions and facilitate design of novel protein-based therapeutic molecules.