Prediction of allosteric sites and mediating interactions through bond-to-bond propensities

B. R. C. Amor, M. T. Schaub, S. N. Yaliraki () and M. Barahona ()
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B. R. C. Amor: Imperial College London
M. T. Schaub: Imperial College London
S. N. Yaliraki: Imperial College London
M. Barahona: Institute of Chemical Biology, Imperial College London

Nature Communications, 2016, vol. 7, issue 1, 1-13

Abstract: Abstract Allostery is a fundamental mechanism of biological regulation, in which binding of a molecule at a distant location affects the active site of a protein. Allosteric sites provide targets to fine-tune protein activity, yet we lack computational methodologies to predict them. Here we present an efficient graph-theoretical framework to reveal allosteric interactions (atoms and communication pathways strongly coupled to the active site) without a priori information of their location. Using an atomistic graph with energy-weighted covalent and weak bonds, we define a bond-to-bond propensity quantifying the non-local effect of instantaneous bond fluctuations propagating through the protein. Significant interactions are then identified using quantile regression. We exemplify our method with three biologically important proteins: caspase-1, CheY, and h-Ras, correctly predicting key allosteric interactions, whose significance is additionally confirmed against a reference set of 100 proteins. The almost-linear scaling of our method renders it suitable for high-throughput searches for candidate allosteric sites.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12477

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DOI: 10.1038/ncomms12477

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