Recent advances in sequencing techniques have yielded enormous amounts of protein sequence data from various species. This large dataset allows sequence comparison between paralogous and orthologous proteins to identify motifs or functional positions that account for the differences of functional subgroups (specificity positions). Algorithms such as SDPpred and the two-entropies analysis (TEA) have been developed to detect such specificity positions from a multiple sequence alignment (MSA) grouped into classes according to certain biological functions. Other algorithms such as TreeDet compute a classification and then predict specificity positions associated with it. However, there are still many unresolved questions: Was the optimal subdivision of a protein family achieved? Do the definitions at different levels of the phylogenetic tree affect the prediction of specificity positions? Can the whole phylogenetic tree be used instead of only one level in it to predict specificity positions?