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Many computational tools have been developed to study amino acid co-evolution in proteins. Most of them, such as McLachlan-based substitution correlation and Mutual Information (MI), only focus on co-evolution of two amino acid residues. On the other hand, co-evolution information of multiple residues is useful to study protein structures and functions. Therefore, there is an urgent requirement for methods to identify multiple co-evolved residues. The n-dimensional Mutual Information (n DMI) method is introduced to identify co-evolution of multiple residues. This algorithm gains the co-evolution information of multiple residues from analysis of a matrix of MI values. The method was applied to G proteins. Results show that n DMI method is effective in identification of multiple co-evolved amino acids. Moreover, n DMI performs better in discovering functional important residues than methods focusing on pairwise co-evolved residues.

Using n-dimensional Mutual Information to Measure Protein Multiple Residues Coevolution