High throughput biosynthesis of ribosomally synthesized and post-translationally modified peptide natural products

生物系统产生的化学品或自然产品对人类健康产生了巨大影响。 例如，过去监管机构批准的所有小分子药物中有近三分之一几乎 四十年来一直是天然产物或天然产物的衍生物，包括70%以上的抗生素和 40%的抗癌药物[1]。虽然在数十万种分子中发现了非常有用的分子， 到目前为止，已被表征的天然产物，过去十年的基因组测序工作， 有一半的人发现，我们只描述了一小部分生物合成途径的产物， 存在于自然界中。这些途径的产物有可能极大地影响诊断， 治疗疾病，至关重要的是，我们开发新的方法，以加快识别和 新天然产物和天然产物样化合物的表征。 为了满足这一关键需求，我的团队专注于核糖体合成和后修饰 肽（RiPP）类天然产物[2]，以及参与其生物合成的酶。中独一无二 在天然产物生物合成途径中，RiPP生物合成酶的底物是基因编码的 前体肽底物的这一特征允许进行深度突变分析，而不仅仅是酶， 也包括它们的基质。我们将开发一个高通量检测底物的平台 基于酵母或细菌表面展示、荧光 激活细胞分选和下一代测序。利用该平台和编码底物的基因库 变体，我们将研究这些酶的底物范围，以及该范围如何与酶的序列相关。 酶的天然底物。此外，我们将对酶进行深入的突变分析， 对底物识别和选择性的贡献。这些研究将为我们提供更深入的了解 这些酶是如何运作的。有了这种更深入的了解，我们将能够利用这些酶作为工具 以产生大量的天然产物样化合物库，这些化合物可以被筛选以鉴定那些具有有用活性的化合物。 生物活性比目前的天然产物发现方法更有效。

Chemicals produced by living systems, or natural products, have had a tremendous impact on human health. For example, nearly one third of all small molecule drugs approved by a regulatory agency over the past nearly four decades have been natural products or derivatives of natural products, including over 70% of antibiotics and 40% of anticancer drugs [1]. While very useful molecules have been identified among the hundreds of thousands of natural products that have been characterized to date, genome sequencing efforts over the past decade and a half have revealed that we have only characterized the products of a small fraction of the biosynthetic pathways that exist in nature. The products of these pathways have the potential to greatly impact the diagnosis and treatment of disease, and it is critical that we develop new approaches to accelerate the identification and characterization of new natural products and natural product-like compounds. Towards this critical need, my group focuses on the ribosomally synthesized and post-translationally modified peptide (RiPP) class of natural products [2], and the enzymes involved in their biosynthesis. Unique among natural product biosynthetic pathways, the substrate of the RiPP biosynthetic enzymes is a genetically encoded precursor peptide. This feature of the substrates allows for deep mutational analysis, not just of the enzymes, but of their substrates as well. We will develop a platform for high throughput examination of the substrate selectivity and activity of RiPP biosynthetic enzymes based on yeast or bacterial surface display, fluorescence activated cell sorting, and next generation sequencing. Using this platform and gene libraries encoding substrate variants we will study the substrate scope of these enzymes, and how that scope relates to the sequence of the native substrate of the enzymes. Additionally, we will perform deep mutational analysis of the enzymes to identify contributions to substrate recognition and selectivity. These studies will provide us with a deeper understanding of how these enzymes function. With this deeper understanding, we will be able to use these enzymes as tools to generate large libraries of natural product-like compounds that can be screened to identify those with useful biological activities more efficiently than current natural product discovery approaches.