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<p><i>N</i>-acetylserotonin <i>O</i>-methyltransferase (ASMT) is a key rate-limiting enzyme in microbial melatonin biosynthesis, and its low catalytic efficiency hinders high-yield production. To enhance its catalytic performance, virtual saturation mutagenesis scans were conducted on all residues located within the binding substrate 6 Å in this study, and then the mutant library was screened based on computational tools. Rosetta Cartesian_ddg was subsequently used to evaluate the effects of mutations on protein folding stability, allowing the exclusion of structurally destabilizing variants. Next, the binding free energy changes of enzyme-substrate complexes were calculated using the MM-GBSA method to identify mutations with the potential to improve substrate affinity. Through this strategy, a high-activity mutant, M105W/Y108W, was identified, exhibiting a 6.1-fold increase in catalytic efficiency (<i>k</i><sub><i>cat</i></sub>/<i>K</i><sub><i>ₘ</i></sub>) compared to the wild type (WT). Molecular dynamics simulations and structural analysis revealed that the improved activity resulted from enhanced structural stability, optimized microenvironment within the binding pocket, and strengthened key interactions. When introduced into <i>Escherichia coli</i> co-expressing serotonin <i>N</i>-acetyltransferase (SNAT), and following optimization of expression elements and fermentation conditions, this engineered strain achieved a melatonin production of 742.13&#xa0;mg/L in shake-flask fermentation, representing the highest level reported at this scale. This study not only obtained a highly efficient engineered ASMT variant, but also proposed a broadly applicable strategy for the rational remodeling of enzyme substrate-binding pockets.</p>

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Engineering the substrate-binding pocket of N-acetylserotonin O-methyltransferase for efficient melatonin biosynthesis

  • 期刊论文

  • 发表日期：

    2026年4月13日

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  • Lirong Chen,
  • Wenzhao Xu,
  • Ling Gao,
  • Xiaole Xia

摘要

N-acetylserotonin O-methyltransferase (ASMT) is a key rate-limiting enzyme in microbial melatonin biosynthesis, and its low catalytic efficiency hinders high-yield production. To enhance its catalytic performance, virtual saturation mutagenesis scans were conducted on all residues located within the binding substrate 6 Å in this study, and then the mutant library was screened based on computational tools. Rosetta Cartesian_ddg was subsequently used to evaluate the effects of mutations on protein folding stability, allowing the exclusion of structurally destabilizing variants. Next, the binding free energy changes of enzyme-substrate complexes were calculated using the MM-GBSA method to identify mutations with the potential to improve substrate affinity. Through this strategy, a high-activity mutant, M105W/Y108W, was identified, exhibiting a 6.1-fold increase in catalytic efficiency (kcat/Kₘ) compared to the wild type (WT). Molecular dynamics simulations and structural analysis revealed that the improved activity resulted from enhanced structural stability, optimized microenvironment within the binding pocket, and strengthened key interactions. When introduced into Escherichia coli co-expressing serotonin N-acetyltransferase (SNAT), and following optimization of expression elements and fermentation conditions, this engineered strain achieved a melatonin production of 742.13 mg/L in shake-flask fermentation, representing the highest level reported at this scale. This study not only obtained a highly efficient engineered ASMT variant, but also proposed a broadly applicable strategy for the rational remodeling of enzyme substrate-binding pockets.