Characterizing the binding selectivity landscape of interacting proteins is crucial both for elucidating the underlying mechanisms of their interaction and for developing selective inhibitors. However, current mapping methods are laborious and cannot provide a sufficiently comprehensive description of the landscape. We develop novel and efficient strategies for comprehensively mapping the binding landscape of proteins using a combination of experimental multi-target selective library screening and next-generation sequencing analysis. Our protocols combine protein randomization, yeast surface display technology, deep sequencing, and a few experimental ΔΔGbind data points on purified proteins to generate ΔΔGbind values for the remaining numerous mutants of the same protein complex.
Yeast-surface display of APPI-3M. (A) Schematic drawing of the pairwise selective screen using the YSD system. A naïve library of mutated APPI-3M variants was displayed on the yeast cell surface and presented to pairs of proteases. Each protease in the pair (denoted A or B) was labeled with a different fluorescent dye – Alexa Fluor-650 or Alexa Fluor-488 (represented by green and blue stars, respectively). (B) Pairwise selective screen. Flow cytometry sorting was used to screen the library to isolate APPI-3M variants with enhanced selectivity toward each of the four serine proteases (Meso: mesotrypsin; KLK6; Anionic: anionic trypsin; Cationic: cationic trypsin). In each sort, two variant populations were collected inside the black gates, yielding sorted library populations of protease-selective APPI-3M variants. Green and blue colors represent a high and low cell densities, respectively.
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