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

Andrew SavinovAndres N FernandezStanley Fields
Published in: Proceedings of the National Academy of Sciences of the United States of America (2022)
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 adapted a high-throughput inhibitory fragment assay for use in Escherichia coli , applying it to a set of 10 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 performed a systematic analysis to uncover principles of fragment-based inhibition. We determined 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 characterized a series of trade-offs related to fragment length, showing that shorter peptides allow higher-resolution mapping but suffer from lower inhibitory activity. We employed 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. Overall, this work demonstrates fundamental characteristics of inhibitory protein fragment function and provides a foundation for understanding and controlling protein interactions in vivo.
Keyphrases
  • amino acid
  • high throughput
  • protein protein
  • escherichia coli
  • binding protein
  • high resolution
  • high density
  • artificial intelligence
  • molecular dynamics simulations
  • pseudomonas aeruginosa