For mapping energetic interactions in proteins, we developed a technique that uses evolutionary sequence data for a protein family to measure statistical interactions between amino acid positions. For the PDZ domain family, this analysis predicted a set of energetically coupled positions for a binding site residue that includes unexpected long-range interactions. Mutational studies confirm these predictions, demonstrating that the statistical energy function is a good indicator of thermodynamic coupling in proteins. Sets of interacting residues form connected pathways through the protein fold that may be the basis for efficient energy conduction within proteins. This work represents the starting point in our laboratory of the statistical coevolution strategy for analyzing amino acid interactions in proteins.