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: 10418425
• 负责人: Robert Henry Cichewicz
• 金额: $ 35.89万
• 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 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10418425
• 关键词: 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; base; 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.

项目摘要/摘要 天然产品是药物发现的主要主体，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 图书馆是药物开发运动的普遍起点。因此，这些图书馆的质量是 高通量筛选活动成功的关键决定者。天然产品复合库设计是 鉴于分离株之间自然产品生产的冗余和更高的成本，特别具有挑战性 复合生产和隔离。基于循证和科学严格的方法来优化 因此，迫切需要天然产品库设计。在MPI的先前工作中，他们证明了 以液态色谱串联质谱法（LC-）的真菌为例 基于MS/MS）对真菌提取物的分析可能会揭示最少的提取物数量 图书馆，以实现化学多样性的安全性。令人惊讶的是，这个数字可能小至39个分离株 提取物，具体取决于替代进化枝。现在有必要证明更广泛的效用 生物分析方法，用于高通量筛查天然产品的重大生物学问题 化学库设计。此外，我们方法的高通量性质使系统和 对引起的化学多样性的不同天然产品多元化方法的无偏评估。我们的 提案以MPI在代谢组学和小分子表征和自然方面的广泛专业知识为基础 产品分析。此外，通过MPI访问从The 俄克拉荷马大学公民科学土壤收集计划。该系列目前总计> 78,000 来自893个真菌属的分离物。我们的核心假设是我们不靶向的代谢组学方法可以 应用于生成自然产品库设计的特定规则，并提供证据证明或 反驳当前管理自然产品图书馆设计的教条。我们将专注于三个普通图书馆 设计方法，三个独立目标。 AIM 1将专注于使用我们的方法证明 可比较的化学多样性可以从专注的，理性设计的天然产物库中获得 与随机的偶然发现相比。 AIM 2将系统地评估共文化对 引起化学多样性，比较同胞与同种异体共培养系统。 AIM 3将系统地 量化模拟环境培养条件（例如土壤或细菌信号）对 引起化学多样性。总体而言，我们的结果将导致验证一种新方法的理性自然方法 产品库设计，对药物开发产生了重大影响。