The identification of mutations that confer unique properties to a pathogen, such as host range, is of fundamental importance in the fight against disease. This paper describes a novel method for identifying amino acid sites that distinguish specific sets of protein sequences, by comparative analysis of matched alignments. The use of mutual information to identify distinctive residues responsible for functional variants makes this approach highly suitable for analyzing large sets of sequences. To support mutual information analysis, we developed the AVANA software, which utilizes sequence annotations to select sets for comparison, according to user-specified criteria. The method presented was applied to an analysis of influenza A PB2 protein sequences, with the objective of identifying the components of adaptation to human-to-human transmission, and reconstructing the mutation history of these components.