Ancestral sequence reconstruction represents a powerful approach for empirical testing of structure-function relationship of diverse proteins. This paleomolecular technique allows resurrection of ancient enzymes based on sequences predicted by a phylogenetic analysis. Starting from an alignment of modern sequences, the phylogenetic tree is inferred and statistical methods are used to predict the most likely ancestral sequences at the internal nodes of the tree. Genes that encode the inferred ancestral sequences can then be synthesized, expressed in cultured cells and experimentally characterized [1-2]. In this study, the sequences of representative members of haloalkane dehalogenase subfamily II were selected as targets for prediction of recent common ancestor of haloalkane dehalogenase DbjA [3-5] and DbeA , ancDbjA-DbeA-node1, and additional ancestors corresponding to the deeper nodes of the branch leading towards the present-day enzymes, ancDbjA-DbeA-node2, ancDbjA-DbeA-node3, ancDbjA-DbeA-node4 and ancDbjA-DbeA-node5. The genes encoding predicted sequences were synthesized; the ancient proteins were overexpressed in Escherichia coli BL21(DE3), purified to homogeneity by metallo-affinity chromatography and biochemically characterized. All resurrected enzymes were correctly folded and revealed enhanced thermodynamic stability up to 20 °C compared to the modern enzymes. Moreover, the ancestral enzymes exhibited different oligomeric states compared to descendant haloalkane dehalogenases. Steady-state kinetics revealed high catalytic efficiency of constructed enzymes towards 1,2-dibromoethane. The substrate specificity of the ancestors was determined spectrophotometrically towards a set of thirty different halogenated substrates and compared with substrate specificity profiles of the corresponding descendant enzymes. Multivariate statistical analysis of collected data uncovered significant differences in substrate specificity profiles of ancestral and modern enzymes. On-going crystallisation and structural analysis of selected ancestral enzymes will provide insight to unique properties of ancestral enzymes.