Discovery of Novel R-Selective Aminotransferase Motifs through Computational Screening

Abstract

Transaminases, enzymes facilitating amino group transfers, are divided into four subfamilies: D-alanine transaminase (DATA), L-selective Branched chain aminotransferase (BCAT), 4-amino-4-deoxychorismate lyase (ADCL), and R-selective aminotransferase (RATA). RATA enzymes are particularly valuable in biocatalysis for synthesizing chiral amines and resolving racemic mixtures, yet their identification in sequence databases is challenging due to the lack of robust motif-based screening methods. By constructing a transaminase sequence dataset and categorizing them into subfamilies, we re-screened conserved motifs and explored novel ones. Phylogenetic clustering and structural localization of these motifs on Alphafold-predicted protein models validated their importance. For ADCL, BCAT, DATA, and RATA datasets, we discovered 5, 7, 10, and 2 novel motifs, respectively. Additionally, unique residue patterns were identified, underscoring their structural significance. This motif-based computational approach promises to unveil novel RATA enzymes for biocatalytic applications.