Allostery is a fundamental mechanism of regulation in biology. The residues at the end points of long-range allosteric perturbations are commonly identified by the comparative analyses of structures and dynamics in apo and effector-bound states. However, the networks of interactions mediating the propagation of allosteric signals between the end points often remain elusive. Here we show that the covariance analysis of NMR chemical shift changes caused by a set of covalently modified analogs of the allosteric effector (i.e., agonists and antagonists) reveals extended networks of coupled residues. Unexpectedly, such networks reach not only sites subject to effector-dependent structural variations, but also regions that are controlled by dynamically driven allostery. In these regions the allosteric signal is propagated mainly by dynamic rather than structural modulations, which result in subtle but highly correlated chemical shift variations. The proposed chemical shift covariance analysis (CHESCA) identifies interresidue correlations based on the combination of agglomerative clustering (AC) and singular value decomposition (SVD). AC results in dendrograms that define functional clusters of coupled residues, while SVD generates score plots that provide a residue-specific dissection of the contributions to binding and allostery. The CHESCA approach was validated by applying it to the cAMP-binding domain of the exchange protein directly activated by cAMP (EPAC) and the CHESCA results are in full agreement with independent mutational data on EPAC activation. Overall, CHESCA is a generally applicable method that utilizes a selected chemical library of effector analogs to quantitatively decode the binding and allosteric information content embedded in chemical shift changes. L ong-range allosteric perturbations are propagated not only by structural changes but also by effector-dependent modulations in dynamics (1-23). The end points of these long-range allosteric signal propagations are effectively characterized by the comparative analysis of the structural and dynamic profiles of apo and effector-bound states (2, 7). However, what remains experimentally challenging is often defining the networks of residues that mediate the cross-talk between distal sites. Such clusters of coupled residues are particularly elusive in allosteric processes with a significant dynamically driven component (11-17), as in this case the allosteric signal propagation relies on subtle, but critical, conformational and side-chain packing rearrangements that often fall below the resolution of common X-ray or NMR structure determination methods (2, 7, 24).Here we introduce a general experimental method to map allosteric networks based on the covariance analysis of NMR chemical shifts. The chemical shift covariance analysis (CHESCA) is based on two simple but general notions. The first assumption is that the subtle but functionally relevant structural changes that underlie the allosteric modulations of dynamics are effectively probed by accurately ...