Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States.
Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States.
J Am Chem Soc. 2024 Mar 27;146(12):8016-8030. doi: 10.1021/jacs.3c11306. Epub 2024 Mar 12.
There have been significant advances in the flexibility and power of cell-free translation systems. The increasing ability to incorporate noncanonical amino acids and complement translation with recombinant enzymes has enabled cell-free production of peptide-based natural products (NPs) and NP-like molecules. We anticipate that many more such compounds and analogs might be accessed in this way. To assess the peptide NP space that is directly accessible to current cell-free technologies, we developed a peptide parsing algorithm that breaks down peptide NPs into building blocks based on ribosomal translation logic. Using the resultant data set, we broadly analyze the biophysical properties of these privileged compounds and perform a retrobiosynthetic analysis to predict which peptide NPs could be directly synthesized in augmented cell-free translation reactions. We then tested these predictions by preparing a library of highly modified peptide NPs. Two macrocyclases, PatG and PCY1, were used to effect the head-to-tail macrocyclization of candidate NPs. This retrobiosynthetic analysis identified a collection of high-priority building blocks that are enriched throughout peptide NPs, yet they had not previously been tested in cell-free translation. To expand the cell-free toolbox into this space, we established, optimized, and characterized the flexizyme-enabled ribosomal incorporation of piperazic acids. Overall, these results demonstrate the feasibility of cell-free translation for peptide NP total synthesis while expanding the limits of the technology. This work provides a novel computational tool for exploration of peptide NP chemical space, that could be expanded in the future to allow design of ribosomal biosynthetic pathways for NPs and NP-like molecules.
无细胞翻译系统的灵活性和功能得到了显著提高。越来越能够掺入非规范氨基酸并与重组酶互补翻译,使得基于肽的天然产物 (NP) 和 NP 样分子的无细胞生产成为可能。我们预计,通过这种方式可以获得更多的此类化合物和类似物。为了评估当前无细胞技术直接可及的肽 NP 空间,我们开发了一种肽解析算法,该算法根据核糖体翻译逻辑将肽 NP 分解为构建块。使用所得数据集,我们广泛分析了这些特权化合物的物理化学性质,并进行了回溯生物合成分析,以预测哪些肽 NP 可以在增强的无细胞翻译反应中直接合成。然后,我们通过制备高度修饰的肽 NP 文库来测试这些预测。使用两种环化酶,PatG 和 PCY1,来实现候选 NP 的头到尾环化。这种回溯生物合成分析确定了一组高优先级的构建块,这些构建块在肽 NP 中丰富存在,但以前从未在无细胞翻译中进行过测试。为了将无细胞工具箱扩展到这个空间,我们建立、优化和表征了可灵活酶促核糖体掺入哌嗪酸。总的来说,这些结果证明了无细胞翻译用于肽 NP 全合成的可行性,同时扩展了该技术的限制。这项工作为探索肽 NP 化学空间提供了一种新的计算工具,未来可以扩展该工具以允许设计用于 NP 和 NP 样分子的核糖体生物合成途径。