TY - JOUR
T1 - A refined picture of the native Amine Dehydrogenase family revealed by extensive biodiversity screening
AU - Grogan, Gideon James
AU - Elisee, Eddy
AU - Ducrot, Laurine
AU - Meheust, Raphael
AU - Bastard, Karine
AU - Fossey-Jouenne, Aurelie
AU - Pelletier, Eric
AU - Petit, Jean-Louis
AU - Stam, Mark
AU - de Berardinis, Veronique
AU - Zaparucha, Anne
AU - Vallenet, David
AU - Vergne-Vaxelaire, Carine
N1 - © The Author(s) 2024
PY - 2024/6/10
Y1 - 2024/6/10
N2 - Native amine dehydrogenases offer sustainable access to chiral amines, so the search for scaffolds capable of converting more diverse carbonyl compounds is required to reach the full potential of this alternative to conventional synthetic reductive aminations. Here we report a multidisciplinary strategy combining bioinformatics, chemoinformatics and biocatalysis to extensively screen billions of sequences in silico and to efficiently find native amine dehydrogenases features using computational approaches. In this way, we achieve a comprehensive overview of the initial native amine dehydrogenase family, extending it from 2,011 to 17,959 sequences, and identify native amine dehydrogenases with non-reported substrate spectra, including hindered carbonyls and ethyl ketones, and accepting methylamine and cyclopropylamine as amine donor. We also present preliminary model-based structural information to inform the design of potential (R)-selective amine dehydrogenases, as native amine dehydrogenases are mostly (S)-selective. This integrated strategy paves the way for expanding the resource of other enzyme families and in highlighting enzymes with original features.INTRODUCTION
AB - Native amine dehydrogenases offer sustainable access to chiral amines, so the search for scaffolds capable of converting more diverse carbonyl compounds is required to reach the full potential of this alternative to conventional synthetic reductive aminations. Here we report a multidisciplinary strategy combining bioinformatics, chemoinformatics and biocatalysis to extensively screen billions of sequences in silico and to efficiently find native amine dehydrogenases features using computational approaches. In this way, we achieve a comprehensive overview of the initial native amine dehydrogenase family, extending it from 2,011 to 17,959 sequences, and identify native amine dehydrogenases with non-reported substrate spectra, including hindered carbonyls and ethyl ketones, and accepting methylamine and cyclopropylamine as amine donor. We also present preliminary model-based structural information to inform the design of potential (R)-selective amine dehydrogenases, as native amine dehydrogenases are mostly (S)-selective. This integrated strategy paves the way for expanding the resource of other enzyme families and in highlighting enzymes with original features.INTRODUCTION
U2 - 10.1038/s41467-024-49009-2
DO - 10.1038/s41467-024-49009-2
M3 - Article
SN - 2041-1723
VL - 15
JO - Nature Communications
JF - Nature Communications
M1 - 4933
ER -