Protein–protein interactions (PPIs) are critical
for organizing
molecules in a cell and mediating signaling pathways. Dysregulation
of PPIs is often a key driver of disease. To better understand the
biophysical basis of such disease processesand to potentially
target themit is critical to understand the molecular determinants
of PPIs. Deep mutational scanning (DMS) facilitates the acquisition
of large amounts of biochemical data by coupling selection with high
throughput sequencing (HTS). The challenging and labor-intensive design
and optimization of a relevant selection platform for DMS, however,
limits the use of powerful directed evolution and selection approaches.
To address this limitation, we designed a versatile new phage-assisted
continuous selection (PACS) system using our previously reported proximity-dependent
split RNA polymerase (RNAP) biosensors, with the aim of greatly simplifying
and streamlining the design of a new selection platform for PPIs.
After characterization and validation using the model KRAS/RAF PPI,
we generated a library of RAF variants and subjected them to PACS
and DMS. Our HTS data revealed positions along the binding interface
that are both tolerant and intolerant to mutations, as well as which
substitutions are tolerated at each position. Critically, the “functional
scores” obtained from enrichment data through continuous selection
for individual variants correlated with K
D values measured in vitro, indicating that biochemical
data can be extrapolated from sequencing using our new system. Due
to the plug and play nature of RNAP biosensors, this method can likely
be extended to a variety of other PPIs. More broadly, this, and other
methods under development support the continued development of evolutionary
and high-throughput approaches to address biochemical problems, moving
toward a more comprehensive understanding of sequence–function
relationships in proteins.