Peng Hui, Kotelnikov Sergei, Egbert Megan E, Ofaim Shany, Stevens Grant C, Phanse Sadhna, Saccon Tatiana, Ignatov Mikhail, Dutta Shubham, Istace Zoe, Moutaoufik Mohamed Taha, Aoki Hiroyuki, Kewalramani Neal, Sun Jianxian, Gong Yufeng, Padhorny Dzmitry, Poda Gennady, Alekseenko Andrey, Porter Kathryn A, Jones George, Rodionova Irina, Guo Hongbo, Pogoutse Oxana, Datta Suprama, Saier Milton, Crovella Mark, Vajda Sandor, Moreno-Hagelsieb Gabriel, Parkinson John, Segre Daniel, Babu Mohan, Kozakov Dima, Emili Andrew
Department of Chemistry, University of Toronto, Toronto, ON M5S 3H6, Canada.
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA.
Cell. 2025 Mar 6;188(5):1441-1455.e15. doi: 10.1016/j.cell.2025.01.003. Epub 2025 Jan 24.
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.
了解蛋白质-代谢物相互作用可以增强对生化过程的机制理解和化学探测，但内源性配体的发现仍然具有挑战性。在这里，我们将快速亲和纯化与精密质谱和高分辨率分子对接相结合，以精确绘制296种化学性质不同的小分子代谢物配体与革兰氏阴性细菌大肠杆菌中69种不同的必需酶和45种转录因子的物理关联。然后，我们进行了系统的代谢途径整合、泛微生物进化预测和独立的深入生物物理表征实验，以确定配体界面的功能意义。这项工作揭示了在网络水平上控制功能串扰的原则、结合口袋保守性的不同模式以及设计选择性化学探针的支架。这种结构解析的配体相互作用组图谱绘制流程可以扩展，以阐明完整细胞乃至整个多细胞群落的天然小分子网络。
