Catalytic mechanism of ancestral L-lysine oxidase assigned by sequence data mining.

A large number of protein sequences are registered in public databases such as PubMed. Functionally uncharacterized enzymes are included in these databases, some of which likely have potential for industrial applications. However, assignment of the enzymes remained difficult tasks for now. In this study, we assigned a total of 28 original sequences to uncharacterized enzymes in the FAD-dependent oxidase family expressed in some species of bacteria including Chryseobacterium, Flavobacterium, and Pedobactor. Progenitor sequence of the assigned 28 sequences was generated by ancestral sequence reconstruction, and the generated sequence exhibited L-lysine oxidase activity; thus, we named the enzyme AncLLysO. Crystal structures of ligand-free and ligand-bound forms of AncLLysO were determined, indicating that the enzyme recognizes L-Lys by hydrogen bond formation with R76 and E383. The binding of L-Lys to AncLLysO induced dynamic structural change at a plug loop formed by residues 251 to 254. Biochemical assays of AncLLysO variants revealed the functional importance of these substrate recognition residues and the plug loop. R76A and E383D variants were also observed to lose their activity, and the k/K value of G251P and Y253A mutations were approximately 800- to 1800-fold lower than that of AncLLysO, despite the indirect interaction of the substrates with the mutated residues. Taken together, our data demonstrate that combinational approaches to sequence classification from database and ancestral sequence reconstruction may be effective not only to find new enzymes using databases of unknown sequences but also to elucidate their functions.