Laboratory of Genetically Encoded Small Molecules , The Rockefeller University , New York , New York 10065 , United States.
J Am Chem Soc. 2019 Oct 9;141(40):15737-15741. doi: 10.1021/jacs.9b07317. Epub 2019 Sep 27.
Bioinformatic analysis of sequenced bacterial genomes has uncovered an increasing number of natural product biosynthetic gene clusters (BGCs) to which no known bacterial metabolite can be ascribed. One emerging method we have investigated for studying these BGCs is the synthetic-Bioinformatic Natural Product (syn-BNP) approach. The syn-BNP approach replaces transcription, translation, and enzymatic biosynthesis of natural products with bioinformatic algorithms to predict the output of a BGC and chemical synthesis to produce the predicted structure. Here we report on expanding the syn-BNP approach to the design and synthesis of cyclic peptides inspired by nonribosomal peptide synthetase BGCs associated with the human microbiota. While no syn-BNPs we tested inhibited the growth of bacteria or yeast, five were found to be active in the human cell-based MTT metabolic activity assay. Interestingly, active peptides were mostly inspired by BGCs found in the genomes of opportunistic pathogens that are often more commonly associated with environments outside the human microbiome. The cyclic syn-BNP studies presented here provide further evidence of its potential for identifying bioactive small molecules directly from the instructions encoded in the primary sequences of natural product BGCs.
对测序细菌基因组的生物信息学分析揭示了越来越多的天然产物生物合成基因簇(BGCs),这些 BGCs 没有已知的细菌代谢产物可以归属。我们研究这些 BGCs 的一种新兴方法是合成生物信息学天然产物(syn-BNP)方法。syn-BNP 方法用生物信息学算法替代天然产物的转录、翻译和酶促生物合成,以预测 BGC 的产物,并进行化学合成以产生预测的结构。在这里,我们报告了将 syn-BNP 方法扩展到受人类微生物群相关非核糖体肽合成酶 BGC 启发的环状肽的设计和合成。虽然我们测试的 syn-BNPs 没有抑制细菌或酵母的生长,但有 5 种在基于人细胞的 MTT 代谢活性测定中表现出活性。有趣的是,活性肽主要受到机会性病原体基因组中 BGC 的启发,这些病原体通常与人类微生物组以外的环境更为相关。这里介绍的环状 syn-BNP 研究进一步证明了它从天然产物 BGC 的原始序列编码的指令中直接识别生物活性小分子的潜力。