@article{Amor:2016:10.1038/ncomms12477,
author = {Amor, BRC and Schaub, MT and Yaliraki, S and Barahona, M},
doi = {10.1038/ncomms12477},
journal = {Nature Communications},
pages = {1--13},
title = {Prediction of allosteric sites and mediating interactions through bond-to-bond propensities},
url = {http://dx.doi.org/10.1038/ncomms12477},
volume = {7},
year = {2016}
}

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TY  - JOUR
AB  - 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.
AU  - Amor,BRC
AU  - Schaub,MT
AU  - Yaliraki,S
AU  - Barahona,M
DO  - 10.1038/ncomms12477
EP  - 13
PY  - 2016///
SN  - 2041-1723
SP  - 1
TI  - Prediction of allosteric sites and mediating interactions through bond-to-bond propensities
T2  - Nature Communications
UR  - http://dx.doi.org/10.1038/ncomms12477
UR  - https://www.nature.com/articles/ncomms12477
UR  - http://hdl.handle.net/10044/1/33811
VL  - 7
ER  - 

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