Allostery is the phenomenon in which a ligand binding at one site affects other 
sites in the same macromolecule. Allostery has important roles in many 
biological processes. Theoretically, all nonfibrous proteins are potentially 
allosteric. However, few allosteric proteins have been validated, and the 
identification of novel allosteric sites remains a challenge. The motion of 
residues and subunits underlies protein function; therefore, we hypothesized 
that the motions of allosteric and orthosteric sites are correlated. We utilized 
a data set of 24 known allosteric sites from 23 monomer proteins to calculate 
the correlations between potential ligand-binding sites and corresponding 
orthosteric sites using a Gaussian network model (GNM). Most of the known 
allosteric site motions showed high correlations with corresponding orthosteric 
site motions, whereas other surface cavities did not. These high correlations 
were robust when using different structural data for the same protein, such as 
structures for the apo state and the orthosteric effector-binding state, whereas 
the contributions of different frequency modes to motion correlations depend on 
the given protein. The high correlations between allosteric and orthosteric site 
motions were also observed in oligomeric allosteric proteins. We applied motion 
correlation analysis to predict potential allosteric sites in the 23 monomer 
proteins, and some of these predictions were in good agreement with published 
experimental data. We also performed motion correlation analysis to identify a 
novel allosteric site in 15-lipoxygenase (an enzyme in the arachidonic acid 
metabolic network) using recently reported activating compounds. Our analysis 
correctly identified this novel allosteric site along with two other sites that 
are currently under experimental investigation. Our study demonstrates that the 
motions of allosteric sites are highly correlated with the motions of 
orthosteric sites. Our correlation analysis method provides new tools for 
predicting potential allosteric sites.