An LCMS-guided bioanalytical approach for rational natural product library design and optimization

LCMS 引导的生物分析方法，用于合理的天然产物库设计和优化

• 批准号: 10697396
• 负责人: Robert Henry Cichewicz
• 金额: $ 7.06万
• 依托单位: UNIVERSITY OF OKLAHOMA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-05 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10697396
• 关键词: Acceleration; Accounting; Address; Affect; Alternaria; American; Biological; Breathing; Chemicals; Coculture Techniques; Collection; Complex; Data; Disease; Diversity Library; Ensure; Environment; Epidemic; Generations; Habits; Individual; Lead; Libraries; Liquid Chromatography; Methodology; Methods; Natural Products; Nature; Oklahoma; Persons; Pharmaceutical Preparations; Pharmacologic Substance; Poverty; Production; Public Health; Randomized; Rare Diseases; Reporting; Risk; Running; Sampling; Signal Transduction; Soil; Source; Stress; System; Testing; Trichoderma; Universities; Validation; Work; citizen science; clinical translation; cost; design; drug development; drug discovery; drug resource; emerging pathogen; evidence base; fungus; high throughput screening; liquid chromatography mass spectrometry; metabolomics; microbial; novel; novel strategies; programs; quorum sensing; rational design; scaffold; single molecule; small molecule; small molecule libraries; success; tandem mass spectrometry

Project Summary/Abstract Natural products are a mainstay of drug discovery, accounting for up to 50% of approved drugs either as direct natural molecules or as inspiration for synthetic molecules. High-throughput screening of compound libraries is a common starting point for drug development campaigns. The quality of these libraries is therefore a key determinant of high-throughput screening campaign success. Natural product compound library design is particularly challenging given redundancies in natural product production between isolates and greater costs of compound production and isolation. Evidence-based and scientifically rigorous methods to optimize natural product library design are therefore urgently required. In MPIs’ previous work, they demonstrated using the example of the fungus Alternaria that liquid chromatography-tandem mass spectrometry (LC- MS/MS)-based analysis of fungal extracts could reveal the minimal number of extracts to include in a chemical library, to achieve saturation of chemical diversity. Strikingly, this number could be as small as 39 isolate extracts, depending on the Alternaria clade. It is now necessary to demonstrate the broader utility of this bioanalytical approach, to the significant biological problem of high-throughput screening natural product chemical library design. In addition, the high-throughput nature of our approach enables the systematic and unbiased assessment of different natural product diversification approaches on elicited chemical diversity. Our proposal builds on MPI’s extensive expertise in metabolomics and small molecule characterization and natural product analysis. In addition, it is enabled by the MPI’s access to the large collection of fungal isolates from the University of Oklahoma Citizen Science Soil Collection Program. This collection currently totals >78,000 isolates from 893 fungal genera. Our central hypothesis is that our untargeted metabolomics method can be applied to generate specific rules of natural product library design and provide evidence to prove or disprove current dogma governing natural product library design. We will focus on three common library design approaches, in three independent aims. Aim 1 will focus on using our approach to demonstrate that comparable chemical diversity can be obtained from focused, rationally-designed natural product libraries, compared to random serendipitous discovery. Aim 2 will systematically assess the impact of co-culture on elicited chemical diversity, comparing sympatric vs allopatric co-culture systems. Aim 3 will systematically quantify the impact of environment-mimicking culture conditions such as soil or bacterial-derived signals, on elicited chemical diversity. Overall, our results will lead to validation of a new approach for rational natural product library design, with major implications for drug development.

项目概要/摘要 天然产物是药物发现的支柱，占批准药物的 50% 直接天然分子或作为合成分子的灵感。化合物的高通量筛选 图书馆是药物开发活动的共同起点。因此，这些库的质量是 高通量筛选活动成功的关键决定因素。天然产物化合物库设计是 鉴于分离株之间天然产物生产的冗余和更高的成本，这一问题尤其具有挑战性 化合物的生产和分离。基于证据和科学严谨的优化方法 因此迫切需要天然产物库的设计。在 MPI 之前的工作中，他们证明了 以真菌链格孢属 (Alternaria) 为例，液相色谱-串联质谱法 (LC- 基于 MS/MS）的真菌提取物分析可以揭示化学品中包含的最小提取物数量 库，以实现化学多样性的饱和。引人注目的是，这个数字可能小至 39 个分离株 提取物，取决于链格孢属分支。现在有必要证明这一点的更广泛的用途 生物分析方法，解决高通量筛选天然产物的重大生物学问题 化学库设计。此外，我们方法的高通量性质使得系统性和 对不同天然产品多样化方法对引发的化学多样性进行公正的评估。我们的 该提案建立在 MPI 在代谢组学和小分子表征以及天然产物方面的广泛专业知识的基础上 产品分析。此外，它是通过 MPI 获取大量真菌分离物来实现的。 俄克拉荷马大学公民科学土壤收集计划。该收藏目前总计 >78,000 从 893 个真菌属中分离出来。我们的中心假设是我们的非靶向代谢组学方法可以 应用于生成天然产物库设计的具体规则并提供证据证明或 反驳当前管理天然产品库设计的教条。我们将重点关注三个常用库 设计方法，三个独立的目标。目标 1 将侧重于使用我们的方法来证明 可以从集中、合理设计的天然产物库中获得可比较的化学多样性， 与随机的偶然发现相比。目标 2 将系统地评估共培养对 通过比较同域与异域共培养系统，引发了化学多样性。目标 3 将系统地 量化模拟环境培养条件（例如土壤或细菌衍生信号）对 引发化学多样性。总的来说，我们的结果将验证一种理性自然的新方法 产品库设计，对药物开发具有重大影响。