Abstract
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, Ohm.dokhlab.org, automatically determines allosteric network architecture and identifies critical coupled residues within this network.
Highlights
Allostery in proteins influences various biological processes such as regulation of gene transcription and activities of enzymes and cell signaling
Since Nabuhiro Gō introduced his model of protein folding[1], whereby attractive amino acid interactions are assigned based on whether these residues are in proximity in the native state of the protein, it has been accepted that the native structure of a protein is determined to a significant extent by its folding pathway
A perturbation propagation algorithm is the foundation for allosteric network analysis in Ohm; this algorithm predicts allosteric sites, pathways, critical residues, and inter-residue correlations
Summary
Allostery in proteins influences various biological processes such as regulation of gene transcription and activities of enzymes and cell signaling. We posited that dynamic couplings in atomic motions are related to protein structure and sought to predict allosteric coupling based solely on established protein structures with the goal of building maps of dynamic coupling in proteins without the use of expensive computational or experimental approaches. Both experimental and computational methods have been proposed to identify putative allosteric sites and to study how perturbations at the allosteric site affect the active site[6,22,23,24,25,26,27,28]. They introduced perturbation-response scanning (PRS)[39,40] to calculate the effectiveness and sensitivity of residues in propagating allosteric signals
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