Accessing and Expanding Natural Products Chemical Diversity by Big-data Analysis and Biosynthetic Investigation

通过大数据分析和生物合成研究获取和扩大天然产物化学多样性

• 批准号: 10714466
• 负责人: Jie Li
• 金额: $ 31.59万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10714466
• 关键词: Address; Anabolism; Big Data; Biomedical Engineering; Chemicals; Collaborations; Competence; Data Analyses; Data Correlations; Engineering; Environment; Enzymatic Biochemistry; FDA approved; Family; Fatty Acids; Firmicutes; Flavoproteins; Fostering; Foundations; Future; Gene Cluster; Genetic; Genome; Goals; Hydroxylation; In Vitro; Informatics; Investigation; Libraries; Mediating; Methods; Microbial Genetics; Mining; Mission; National Institute of General Medical Sciences; Natural Product Drug; Natural Products; Nature; Orphan; Pathway Analysis; Pathway interactions; Peptide Hydrolases; Peptides; Pharmaceutical Preparations; Postdoctoral Fellow; Proteins; Public Health; Research; Source; Sulfur; Terpenes; Time; Training; bioactive natural products; drug discovery; microbial; novel; novel therapeutics; programs; screening; small molecule; structural biology; undergraduate student

PROJECT SUMMARY/ABSTRACT Natural products (NPs) have historically been a critical source of bioactive molecules, with NPs and their derivatives making up over 50% of FDA-approved small molecule drugs. In recent years, NP-based drug discovery is facing a fundamental barrier in identifying new drugs due to repeated rediscovery of the same or similar compounds, representing limited chemical diversity. Fortunately, since NPs have been evolving over billions of years in trillions of vastly diverse environments, there is an abundance of new bioactive NPs encoded in nature which may be useful as drugs. However, their accessibility is a problem: only less than 10% of NP biosynthetic gene clusters (BGCs) have been connected to existing NPs, leaving the vast majority of BGCs untapped as to what NPs they may produce. The overall goal of this research program is to leverage big-data informatic analysis and biosynthetic investigation to access and convert the tremendous genetic potential of these “orphan BGCs”, BGCs with unknown products, into chemical reality, connecting them to their products and in turn supplying structurally diverse pools of NPs for drug discovery screening. To this end, we propose two research directions: (1) Utilizing our established big-data correlational networking analysis, we have identified hidden proteases missing from the BGCs of almost all class III lanthipeptides. We previously used this method to discover two new families of class III lanthipeptides from Firmicutes for the first time. We will leverage these hidden proteases to further unlock the inherent chemical diversity of lanthipeptides and generate two libraries of natural and non-natural peptides through in vitro enzymatic synthesis and targeted biosynthetic engineering for drug discovery screening. (2) Mining the untapped microbial genetic potential, with an initial emphasis on sulfur- containing NPs and unprecedented biosynthetic pathway hybridization, we have prioritized two promising orphan BGCs with highly unique enzymology and connected them to their native products. The first features a novel S- hydroxylating flavoprotein, potentially involved in the formation of a new sulfur-containing functionality. The second has an unprecedented terpenoid-fatty acid-non-ribosomal peptide hybridization mediated by unusual cross-pathway enzymatic combinations. We will further investigate the new biosynthesis harbored by these BGCs to produce new NPs, inform future genome mining of similar pathways, and enable pathway engineering to further increase NPs chemical diversity. Our significant progress in both research directions supports the feasibility of this proposal as well as our competence to establish a successful and sustainable independent program in this field. We have fostered several key collaborations in bioactivity screening and protein structural biology that further strengthen our research program. In addition, this program will provide opportunities to train undergraduates, graduates, and postdoctoral fellows. Overall, this program is expected to discover new biosynthesis, expand NPs chemical diversity, and facilitate informatics-based NPs discovery and bioengineering to provide promising new drug leads.

项目概要/摘要 天然产物 (NP) 历来是生物活性分子的重要来源，NP 及其衍生物 近年来，NP类药物占FDA批准的小分子药物的50%以上。 由于重复地重新发现相同或相同的药物，发现在识别新药方面面临着根本障碍 幸运的是，由于纳米颗粒已经不断进化，因此它们具有相似的化合物。 数十亿年来，在数万亿个极其多样化的环境中，编码了大量新的生物活性纳米颗粒 在自然界中可能可用作药物，但它们的可及性是一个问题：只有不到 10% 的 NP。 生物合成基因簇（BGC）已与现有的 NP 连接，留下绝大多数 BGC 尚未开发它们可能产生什么纳米粒子 该研究计划的总体目标是利用大数据。 信息分析和生物合成研究，以获取和转化巨大的遗传潜力 这些“孤儿 BGC”（具有未知产品的 BGC）进入化学现实，将它们与其产品连接起来， 反过来，为药物发现筛选提供结构多样化的纳米颗粒库为此，我们提出了两种方案。 研究方向：（1）利用我们建立的大数据关联网络分析，我们确定了 几乎所有 III 类羊毛肽的 BGC 中都缺少隐藏的蛋白酶 我们之前使用过这种方法。 我们将首次从厚壁菌门中发现两个新的 III 类羊毛脂肽家族。 隐藏的蛋白酶进一步解开羊毛硫肽固有的化学多样性并生成两个库 通过体外酶促合成和靶向生物合成工程生产天然和非天然肽 (2) 挖掘未开发的微生物遗传潜力，最初重点是硫- 含有纳米粒子和前所未有的生物合成途径杂交，我们优先考虑了两个有前途的孤儿 BGC 具有高度独特的酶学，并将其与其天然产物连接起来。第一个具有新颖的 S-。 羟基化黄素蛋白，可能参与新的含硫功能的形成。 第二个具有前所未有的萜类脂肪酸非核糖体肽杂交，由不寻常的介导 我们将进一步研究这些跨途径酶组合。 BGC 可产生新的 NP，为未来类似途径的基因组挖掘提供信息，并实现途径工程 进一步增加纳米粒子化学多样性，我们在这两个研究方向上取得的重大进展支持了 该提案的可行性以及我们建立成功且可持续的独立性的能力 我们在该领域开展了多项关键合作，包括生物活性筛选和蛋白质结构。 生物学，进一步加强我们的研究计划此外，该计划还将提供培训机会。 总的来说，这个项目预计会发现新的东西。 生物合成，扩大纳米颗粒化学多样性，促进基于信息学的纳米颗粒发现和生物工程 提供有前景的新药先导物。