Protein dynamics play an essential role in function regulation. In recent years, many experimental and theoretical studies have shown that changes in protein fluctuations in the backbone and side chains fulfill a pivotal role associated with amino acid mutations, chemical modifications, and ligand binding. The dynamic correlations between protein side chains have not been sufficiently studied, and no reliable analysis method has been available so far. Therefore, we developed a method to evaluate the dynamic correlation between protein side chains using mutual information and molecular dynamics simulations. To eliminate the structural superposition errors dealing with conventional analysis methods, and to accurately extract the intrinsic fluctuation properties of the side chains, we employed distance principal component analysis (distPCA). The motion of the side chain was then projected onto the eigenvector space obtained by distPCA, and the mutual information between the projected motions was calculated. The proposed method was then applied to a small protein "eglin c" and the mutants. The results show that even a single mutation significantly changed the dynamic correlations and also suggest that the dynamic change is deeply related to the stability. Those results indicate that our developed method could be useful for analyzing the molecular mechanism of allosteric communication in proteins.