Alteration of metal ions improves the activity and thermostability of aminoacylase from hyperthermophilic archaeon Pyrococcus horikoshii

Abstract

Recombinant L-aminoacylase (PhoACY) from a hyperthermophilic archeon, Pyrococcus horikoshii, is a zinc-containing metalloenzyme. When the zinc was substituted by Mn(2+) or Ni(2+), its specific activity was significantly increased with acetyl-L-methionine as a substrate. The thermostability of PhoACY was improved when it was incubated with 1 mM Zn(2+), Mn(2+) or Ni(2+). The enzyme with external Zn(2+) addition had no significant loss of the activity when held at 90 degrees C for up to 12 h and moreover had more than a 10-fold longer half-life even at 100 degrees C, compared to the enzyme without Zn(2+) addition. A thermostable structure of the enzyme associated with zinc binding is described based on differential scanning calorimetry.

Current scenario on computer-aided metalloenzymes designing

“…Recapitulation of active sites of native enzymes [28] Isochorismate pyruvate lyase QM/MM methods [29] Chorismate mutase Computing empirical valence bonds [30] Proteinase K Machine learning algorithms [32] b-Glycosidases Amino acid replacements [33] L-Aminoacylase Alternation of metal ions [34] Co-dependent b-methylaspartate mutase Molecular-evolution directed approach [11] Cs-dependent formyltetrahydrofolate ligase Molecular-evolution directed approach [12] List of enzymes computationally designed ever, the increasing interest in applying enzymes in industrial processes has spurred the search for biocatalysts with new or improved properties. The use of biotransformation in industry will raise as it has been claimed that a doubling of the number of industrially established biocatalytic processes every decade is probable.…”

“…Unfortunately the resulting models were significantly less effective than the corresponding natural enzymes [31] and the reasons for rather limited success are not completely clear [30]. A few successful experimental enzyme designs have been made for proteinase K invariant by machine learning algorithms [32], b-glycosidases by amino acid replacements [34], L-aminoacylase by alternation of metal ions [34] in the recent years. Using evolutionary conservation of catalytic domain, cobalt-dependent b-methylaspartate mutase [11] and cesium-dependent formyltetrahydrofolate ligase [12] constructs from the sequences of archaea [35] have been already designed, and the designing strategy is schematically represented in Figure. Chellapandi has comprehensively reviewed the enzyme engineering and designing algorithms and associated computational programs in conceptual trends, which will ensure a competitive edge in developing improved enzymes [36].…”