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 自然产物（NP）历史上一直是生物活性分子的关键来源，NP及其 占FDA批准的小分子药物的50％以上的衍生物。近年来，基于NP的药物 由于反复重新发现相同或 类似的化合物，代表有限的化学多样性。幸运的是，由于NP一直在不断发展 数十亿年来，在多种多样的环境中，有大量的新生物活性NPS编码 在自然界中，这可能是有用的。但是，它们的可访问性是一个问题：仅少于NP的10％ 生物合成基因簇（BGC）已连接到现有的NP，留下了绝大多数BGC 尚未开发它们可能产生的NP。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投资，以获取和转化 这些“孤儿BGC”，具有未知产品的BGC，将它们连接到他们的产品和 反过来，为药物发现筛查提供结构上的NPS池。为此，我们提出了两个 研究方向：（1）利用我们既定的大数据相关网络分析，我们已经确定了 几乎所有III级灯笼肽的BGC缺少的隐藏蛋白酶。我们以前使用过这种方法 首次从Firmicutes中发现了两个新的型型灯笼肽的新家庭。我们将利用这些 隐藏的蛋白酶，以进一步解锁植物肽的遗传化学多样性，并产生两个库 天然和非天然肽通过体外酶促合成和针对性的生物合成工程 药物发现筛查。 （2）挖掘未开发的微生物遗传潜力，最初重点是 包含NP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 具有高度独特酶学的BGC并将其连接到本机产品。第一个具有新颖的S- 羟基羟基黄蛋蛋白，可能与新的含硫的功能的形成有关。这 第二 跨道路酶促组合。我们将进一步研究这些新的生物合成 BGC生产新的NP，为未来的基因组开采提供类似途径的挖掘，并启用途径工程 进一步增加NPS化学多样性。我们在两个研究方向上的重大进展都支持 该提案的可行性以及我们建立成功和可持续独立的能力 该领域的程序。我们在生物活性筛查和蛋白质结构方面培养了几个关键的合作 生物学进一步加强我们的研究计划。此外，该计划将提供培训的机会 本科生，毕业生和博士后研究员。总体而言，该计划有望发现新的 生物合成，扩展NPS化学多样性，并促进基于信息的NPS发现和生物工程 提供诺言新药。