@article{PENG2025,
  author	= {Peng, Hui and Kotelnikov, Sergei and Egbert, Megan E. and Ofaim, Shany and Stevens, Grant C. and Phanse, Sadhna and Saccon, Tatiana and Ignatov, Mikhail and Dutta, Shubham and Istace, Zoe and Moutaoufik, Mohamed Taha and Aoki, Hiroyuki and Kewalramani, Neal and Sun, Jianxian and Gong, Yufeng and Padhorny, Dzmitry and Poda, Gennady and Alekseenko, Andrey and Porter, Kathryn A. and Jones, George and Rodionova, Irina and Guo, Hongbo and Pogoutse, Oxana and Datta, Suprama and Saier, Milton and Crovella, Mark and Vajda, Sandor and Moreno-Hagelsieb, Gabriel and Parkinson, John and Segre, Daniel and Babu, Mohan and Kozakov, Dima and Emili, Andrew},
  title		= {Ligand interaction landscape of transcription factors and essential enzymes in {E}. coli},
  journal	= {Cell},
  year		= {2025},
  ISSN		= {0092-8674},
  doi		= {https://doi.org/10.1016/j.cell.2025.01.003},
  URL		= {https://www.sciencedirect.com/science/article/pii/S0092867425000327},
  keywords	= {LP/MS, protein-metabolite interactions, protein-ligand binding pocket, molecular docking, precision structural modeling, enzymes, transcription factors, chemical probe, multi-modal interactome, dynamic network},
  abstract	= {Summary 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.},
}