Mapping allosteric communications within individual proteins

Jian Wang, Abha Jain, Leanna R. McDonald, Craig Gambogi, Andrew L. Lee, Nikolay V. Dokholyan

Research output: Contribution to journalArticlepeer-review

54 Scopus citations


Allostery in proteins influences various biological processes such as regulation of gene transcription and activities of enzymes and cell signaling. Computational approaches for analysis of allosteric coupling provide inexpensive opportunities to predict mutations and to design small-molecule agents to control protein function and cellular activity. We develop a computationally efficient network-based method, Ohm, to identify and characterize allosteric communication networks within proteins. Unlike previously developed simulation-based approaches, Ohm relies solely on the structure of the protein of interest. We use Ohm to map allosteric networks in a dataset composed of 20 proteins experimentally identified to be allosterically regulated. Further, the Ohm allostery prediction for the protein CheY correlates well with NMR CHESCA studies. Our webserver,, automatically determines allosteric network architecture and identifies critical coupled residues within this network.

Original languageEnglish (US)
Article number3862
JournalNature communications
Issue number1
StatePublished - Dec 1 2020

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)


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