@article{90256,
  keywords = {computational biology, Escherichia coli, Models, Biological, Homeostasis, Metabolic Networks and Pathways, Escherichia coli Proteins, Pyrimidines, Arginine, Enzymes},
  author = {Michele Castellana and Maxwell Wilson and Yifan Xu and Preeti Joshi and Ileana Cristea and Joshua Rabinowitz and Zemer Gitai and Ned Wingreen},
  title = {Enzyme clustering accelerates processing of intermediates through metabolic channeling.},
  abstract = { We present a quantitative model to demonstrate that coclustering multiple enzymes into compact agglomerates accelerates the processing of intermediates, yielding the same efficiency benefits as direct channeling, a well-known mechanism in which enzymes are funneled between enzyme active sites through a physical tunnel. The model predicts the separation and size of coclusters that maximize metabolic efficiency, and this prediction is in agreement with previously reported spacings between coclusters in mammalian cells. For direct validation, we study a metabolic branch point in Escherichia coli and experimentally confirm the model prediction that enzyme agglomerates can accelerate the processing of a shared intermediate by one branch, and thus regulate steady-state flux division. Our studies establish a quantitative framework to understand coclustering-mediated metabolic channeling and its application to both efficiency improvement and metabolic regulation. },
  year = {2014},
  journal = {Nat Biotechnol},
  volume = {32},
  pages = {1011-8},
  month = {10/2014},
  issn = {1546-1696},
  doi = {10.1038/nbt.3018},
  language = {eng},
}