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Ligand interaction landscape of transcription factors and essential enzymes in E. coli

  • Hui Peng
  • , Sergei Kotelnikov
  • , Megan E. Egbert
  • , Shany Ofaim
  • , Grant C. Stevens
  • , Sadhna Phanse
  • , Tatiana Saccon
  • , Mikhail Ignatov
  • , Shubham Dutta
  • , Zoe Istace
  • , Mohamed Taha Moutaoufik
  • , Hiroyuki Aoki
  • , Neal Kewalramani
  • , Jianxian Sun
  • , Yufeng Gong
  • , Dzmitry Padhorny
  • , Gennady Poda
  • , Andrey Alekseenko
  • , Kathryn A. Porter
  • , George Jones
  • Irina Rodionova, Hongbo Guo, Oxana Pogoutse, Suprama Datta, Milton Saier, Mark Crovella, Sandor Vajda, Gabriel Moreno-Hagelsieb, John Parkinson, Daniel Segre, Mohan Babu, Dima Kozakov, Andrew Emili
  • University of Toronto
  • Stony Brook University
  • Boston University
  • University of Regina
  • Mohammed VI Polytechnic University
  • Ontario Institute for Cancer Research
  • University of California at San Diego
  • Wilfrid Laurier University
  • Oregon Health and Science University

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Knowledge of protein-metabolite interactions can enhance mechanistic understanding and chemical probing of biochemical processes, but the discovery of endogenous ligands remains challenging. Here, we combined rapid affinity purification with precision mass spectrometry and high-resolution molecular docking to precisely map the physical associations of 296 chemically diverse small-molecule metabolite ligands with 69 distinct essential enzymes and 45 transcription factors in the gram-negative bacterium Escherichia coli. We then conducted systematic metabolic pathway integration, pan-microbial evolutionary projections, and independent in-depth biophysical characterization experiments to define the functional significance of ligand interfaces. This effort revealed principles governing functional crosstalk on a network level, divergent patterns of binding pocket conservation, and scaffolds for designing selective chemical probes. This structurally resolved ligand interactome mapping pipeline can be scaled to illuminate the native small-molecule networks of complete cells and potentially entire multi-cellular communities.

Original languageEnglish
Pages (from-to)1441-1455.e15
JournalCell
Volume188
Issue number5
DOIs
StatePublished - Mar 6 2025

Keywords

  • LP/MS
  • chemical probe
  • dynamic network
  • enzymes
  • molecular docking
  • multi-modal interactome
  • precision structural modeling
  • protein-ligand binding pocket
  • protein-metabolite interactions
  • transcription factors

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