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Homologous enzymes evolved from a common ancestor to retain a general function but diverge in more specific features and can be divided into subfamilies with different specificity, enantioselectivity, stability, etc. While conserved positions define properties that are common for the entire family (for example, have a direct role in enzyme catalytic machinery) they do not explain functional diversity. New bioinformatic analysis method has been developed to identify subfamily-specific positions (SSPs) – conserved only within protein subfamilies, but different between subfamilies – that seem to play important role in functional discrimination. A novel scoring function is suggested to consider structural information as well as physicochemical and residue conservation in protein subfamilies. Random shuffling is performed to rank results by significance and Bernoulli statistics is applied to calculate P-values. Algorithm does not require pre-defined subfamily classification and can propose it automatically by graph-based clustering. Web-base interface to the program is available at http://biokinet.belozersky.msu.ru/zebra. Bioinformatic analysis was used to study how lipase and amidase catalytic activities are implemented into the alpha-beta hydrolase fold. Comparative analysis of α/β-hydrolases with lipase and protease activities was performed and subfamily-specific positions were identified. These hotspots were used to introduce amidase activity into Candida antarctica lipase B (CALB). Molecular modeling was implemented to evaluate influence of selected residues on binding and catalytic conversion of amide substrate by corresponding library of mutants. In silico screening was applied to select reactive enzyme-substrate complexes that satisfy knowledge-based criteria of amidase catalytic activity. Selected CALB variants were produced and showed significant improvement of experimentally measured amidase activity (Suplatov et.al., 2012). Based on these results, we suggest that bioinformatic analysis of subfamily-specific positions can be used as a systematic tool to study structure-function relationship in enzymes. Selection of subfamily-specific positions as hotspots for directed evolution and rational design is suggested as a new protein engineering strategy.