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.

项目摘要/摘要 天然产物（NPs）在历史上一直是生物活性分子的关键来源，NPs和它们的生物活性分子是天然产物。 衍生物占FDA批准的小分子药物的50%以上。近年来，NP药物 由于重复重新发现相同或相似的药物， 类似的化合物，代表有限的化学多样性。幸运的是，由于NP已经在不断发展， 数十亿年来，在数万亿个极其不同的环境中，编码了大量新的生物活性纳米颗粒， 在自然界中可以用作药物。然而，他们的可访问性是一个问题：只有不到10%的NP 生物合成基因簇（BGC）已经连接到现有的NP，使绝大多数BGC 他们可以生产什么样的NP。这项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，将它们与其产品联系起来， 进而为药物发现筛选提供结构多样的NP库。为此，我们建议两个 研究方向：（1）利用我们建立的大数据相关网络分析，我们确定了 几乎所有III类羊毛硫肽的BGC中缺失的隐藏蛋白酶。我们以前用这种方法 首次从厚壁菌门中发现两个新的III类羊毛硫肽家族。我们将利用这些 隐藏的蛋白酶，以进一步解锁羊毛硫肽的固有化学多样性，并产生两个文库， 通过体外酶促合成和靶向生物合成工程， 药物发现筛选(2)挖掘未开发的微生物遗传潜力，最初的重点是硫- 包含NP和前所未有的生物合成途径杂交，我们优先考虑两个有前途的孤儿 BGC具有高度独特的酶学，并将其与当地产品联系起来。第一个故事是一部小说S- 羟基化黄素蛋白，可能参与形成新的含硫官能团。的 第二种是前所未有的萜类-脂肪酸-非核糖体肽杂交， 交叉途径酶组合。我们将进一步研究新的生物合成窝藏这些 BGC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 以进一步增加NP的化学多样性。我们在这两个研究方向上的重大进展支持了 这一建议的可行性以及我们建立一个成功的和可持续的独立的能力， 该领域的方案。我们已经在生物活性筛选和蛋白质结构方面建立了几个关键的合作关系。 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， 本科生、研究生和博士后研究员。总体而言，该计划预计将发现新的 生物合成，扩大NPs化学多样性，促进基于信息学的NPs发现和生物工程 提供有前景的新药线索