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Efficient resolution of profen ethyl ester racemates by engineered Yarrowia lipolytica Lip2p lipase

Abstract : Enzyme-catalyzed enantiomer discrimination is still a great challenge for the development of industrial pharmaceutical processes. For the resolution of ibuprofen, naproxen and ketoprofen racemates, three major anti-inflammatory drugs, only lipases from Candida rugosa present a high selectivity if solvent and surfactant use is discarded. However, their catalytic activities are too low. In the present work, we demonstrate that the lipase Lip2p from the yeast Yarrowia lipolytica has a higher catalytic activity than C rugosa lipases to hydrolyze the ethyl esters of ibuprofen, naproxen and ketoprofen, but its selectivity is not sufficient [E= 52 (S); 11 (S) and 1.5 (R) respectively]. The enantioselectivity was further improved by site-directed mutagenesis, targeted at the substrate binding site and guided by molecular modelling studies. By investigating the binding modes of the (R)-and (S)-enantiomers in the active site, two amino acid residues located in the hydrophobic substrate binding site of the lipase, namely residues 232 and 235, were identified as crucial for enantiomer discrimination and enzyme activity. The (S) enantioselectivity of Lip2p towards ethyl ibuprofen esters was rendered infinite (E >> 300) by replacing V232 by an A or C residue. Substitution of V235 by C, M, S, or T amino acids led to a great increase in the (S)-enantioselectivity (E >> 300) towards naproxen ethyl ester. Finally, the variant V232F enabled the efficient kinetic resolution of ethyl ketoprofen ester enantiomers [(R)-enantiopreference; E >> 300]. In addition to the increase in selectivity, a remarkable increase in velocity by 2.6, 2.7 and 2.5 times, respectively, was found for ibuprofen, naproxen and ketoprofen ethyl esters.
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Doriane Gerard, Marc Gueroult, Leticia Casas, Jean-Stéphane Condoret, Isabelle Andre, et al.. Efficient resolution of profen ethyl ester racemates by engineered Yarrowia lipolytica Lip2p lipase. Tetrahedron: Asymmetry, Elsevier, 2017, 28 (3), pp.433-441. ⟨10.1016/j.tetasy.2017.01.014⟩. ⟨hal-01603797⟩

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