Mapping functional regions of essential bacterial proteins with dominant-negative protein fragments

Abstract

Massively-parallel measurements of dominant negative inhibition by protein fragments have been used to map protein interaction sites and discover peptide inhibitors. However, the underlying principles governing fragment-based inhibition have thus far remained unclear. Here, we adapt a high-throughput inhibitory fragment assay for use in Escherichia coli, applying it to a set of ten essential proteins. This approach yielded single amino acid-resolution maps of inhibitory activity, with peaks localized to functionally important interaction sites, including oligomerization interfaces and folding contacts. Leveraging these data, we perform a systematic analysis to uncover principles of fragment-based inhibition. We determine a robust negative correlation between susceptibility to inhibition and cellular protein concentration, demonstrating that inhibitory fragments likely act primarily by titrating native protein interactions. We also characterize a series of trade-offs related to fragment length, showing that shorter peptides allow higher-resolution mapping but suffer from lower inhibitory activity. We employ an unsupervised statistical analysis to show that the inhibitory activities of protein fragments are largely driven not by generic properties such as charge, hydrophobicity, and secondary structure, but by the more specific characteristics of their bespoke macromolecular interactions. AlphaFold computational modeling of peptide complexes with one protein shows that the inhibitory activity of peptides is associated with their predicted ability to form native-like interactions. Overall, this work demonstrates fundamental characteristics of inhibitory protein fragment function and provides a foundation for understanding and controlling protein interactions in vivo. Significance StatementPeptide fragments derived from protein sequences can inhibit interactions of their parental proteins, providing a promising avenue for drug development. Here we employ a massively-parallel assay to measure in vivo inhibition by fragments that tile the full sequences of ten essential bacterial proteins. We leverage these data to decipher principles of fragment-based inhibition, showing how parental protein concentration drives activity and how protein fragment length interplays with activity and specificity. We employ statistical analysis to parse the roles of biophysical properties in fragment-to-fragment variation, and AlphaFold modeling to determine the relationship between measured inhibitory activity and predicted native-like binding. These results provide a path towards rational design of peptide inhibitors and broader principles of protein-protein interactions in living cells.