The Bamberger rearrangement is a key route to functionalized aminophenols that are widely used in pharmaceutical synthesis. Hydroxylaminobenzene mutase (HabM) catalyzes a Bamberger-type isomerization in the biosynthesis of the Pranlukast intermediate 3-amino-2-hydroxyacetophenone (3AHAP), but its low catalytic efficiency and unknown structure have limited rational improvement. Here, we combine AI-assisted phylogenetic mining, structural elucidation, protein engineering, and metabolic coordination to enhance 3AHAP biosynthesis. Deep learning-guided screening identified the NRBh-HabMEo pair as the most effective combination, substantially outperforming previously reported systems. Using an integrated dry-wet strategy involving homology template search, spectroscopy, mutagenesis, Size-Exclusion-Chromatography analysis, and AlphaFold3-assisted modeling, we reveal that HabMEo is a Fe-dependent tetramer. Rational mutagenesis supported by molecular dynamics simulations yielded a synergistic triple mutant with improved pocket dynamics, optimized Fe-substrate positioning, and markedly enhanced catalytic efficiency. To alleviate reductive limitations, NAD kinase was introduced to strengthen NADPH cycling; however, increased upstream flux led to intermediate accumulation and by-product formation. This was overcome by implementing a RIAD/RIDD-based scaffold to spatially organize NR, HabM, GDH, and NADK, thereby promoting intermediate channeling and suppressing over-reduction. Overall, this study elucidates the structure of HabM and established a successful paradigm for optimizing complex multi-enzyme cascades for sustainable production of high-value biopharmaceutical intermediates.
Tang et al. (Wed,) studied this question.