Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.
Life Sciences Institute, University of Michigan, Ann Arbor, Michigan 48109, United States.
J Am Chem Soc. 2024 Nov 6;146(44):30194-30203. doi: 10.1021/jacs.4c08761. Epub 2024 Oct 23.
Biocatalysis can be powerful in organic synthesis but is often limited by enzymes' substrate scope and selectivity. Developing a biocatalytic step involves identifying an initial enzyme for the target reaction followed by optimization through rational design, directed evolution, or both. These steps are time consuming, resource-intensive, and require expertise beyond typical organic chemistry. Thus, an effective strategy for streamlining the process from enzyme identification to implementation is essential to expanding biocatalysis. Here, we present a strategy combining bioinformatics-guided enzyme mining and ancestral sequence reconstruction (ASR) to resurrect enzymes for biocatalytic synthesis. Specifically, we achieve an enantioselective synthesis of azaphilone natural products using two ancestral enzymes: a flavin-dependent monooxygenase (FDMO) for stereodivergent oxidative dearomatization and a substrate-selective acyltransferase (AT) for the acylation of the enzymatically installed hydroxyl group. This cascade, stereocomplementary to established chemoenzymatic routes, expands access to enantiomeric linear tricyclic azaphilones. By leveraging the co-occurrence and coevolution of FDMO and AT in azaphilone biosynthetic pathways, we identified an AT candidate, CazE, and addressed its low solubility and stability through ASR, obtaining a more soluble, stable, promiscuous, and reactive ancestral AT (AncAT). Sequence analysis revealed AncAT as a chimeric composition of its descendants with enhanced reactivity likely due to ancestral promiscuity. Flexible receptor docking and molecular dynamics simulations showed that the most reactive AncAT promotes a reactive geometry between substrates. We anticipate that our bioinformatics-guided, ASR-based approach can be broadly applied in target-oriented synthesis, reducing the time required to develop biocatalytic steps and efficiently access superior biocatalysts.
生物催化在有机合成中具有强大的作用，但通常受到酶的底物范围和选择性的限制。开发生物催化步骤涉及识别初始酶以进行目标反应，然后通过合理设计、定向进化或两者结合进行优化。这些步骤既耗时又耗资源，并且需要超出典型有机化学范围的专业知识。因此，从酶鉴定到实施简化该过程的有效策略对于扩大生物催化至关重要。在这里，我们提出了一种结合生物信息学指导的酶挖掘和祖先序列重建（ASR）的策略，用于复活用于生物催化合成的酶。具体来说，我们使用两种祖先酶实现了氮杂菲酮天然产物的对映选择性合成：黄素依赖性单加氧酶（FDMO）用于立体发散的氧化去芳构化，以及对酶安装的羟基进行酰化的底物选择性酰基转移酶（AT）。这种级联反应与现有的化学酶法路线互补，扩大了对映体线性三环氮杂菲酮的获得途径。通过利用 FDMO 和 AT 在氮杂菲酮生物合成途径中的共同出现和共同进化，我们鉴定了一个 AT 候选物 CazE，并通过 ASR 解决了其低溶解度和稳定性问题，获得了更具可溶性、稳定性、混杂性和反应性的祖先 AT（AncAT）。序列分析表明 AncAT 是其后代的嵌合体组成，其反应性增强可能是由于祖先的混杂性。灵活的受体对接和分子动力学模拟表明，反应性最强的 AncAT 促进了底物之间的反应性几何形状。我们预计，我们的基于生物信息学指导、ASR 为基础的方法可以广泛应用于定向合成，从而减少开发生物催化步骤所需的时间，并有效地获得优越的生物催化剂。
