Genome mining integrating semi-rational protein engineering and nanoreactor design: roadmap for a robust biocatalyst for industrial resolution of Vince lactam.

Abstract

Biomanufacturing of chemicals using biocatalysts is an attractive strategy for the production of valuable pharmaceuticals since it is usually more economical and has a much-reduced environmental impact. However, there are often challenges such as their thermal instability that should be overcome before a newly discovered enzyme is eventually translated into industrial processes. In this work, we describe a roadmap for the development of a robust catalyst for industrial resolution of Vince lactam, a key intermediate for the synthesis of carbocyclic-nucleoside-related pharmaceuticals. By a genome mining strategy, a new (+)-γ-lactamase (MiteL) from Microbacterium testaceum was successfully discovered and biochemically characterized. In vitro studies showed that the enzyme exhibited high activity but poor enantioselectivity (E = 6.3 ± 0.2) toward racemic Vince lactam, and thus, it is not suitable for industrial applications. Based on structural modeling and docking studies, a semi-rational engineering strategy combined with an efficient screening method was then applied to improve the enantioselectivity of MiteL. Several mutants with significant shifting stereoselectivity toward (-)-γ-lactam were obtained by site-saturation mutagenesis. Synergy effects led to the final mutant F14D/Q114R/M117L, which enabled efficient acquisition of (-)-γ-lactam with a high E value (> 200). The mutant was biochemically characterized, and the docking studies suggested a plausible mechanism for its improved selectivity. Finally, a sunflower-like nanoreactor was successfully constructed to improve the mutant's robustness via protein supramolecular self-assembly. Thus, the synergism between semi-rational protein engineering and self-assembling immobilization enabled construction of a nanoreactor with superior properties, which can be used for resolution of Vince lactam in large scale.