Computation-assisted discovery of bioactive minor cannabinoids from hemp

计算辅助从大麻中发现生物活性次要大麻素

• 批准号: 10791213
• 负责人: Jan Frederik Stevens
• 金额: $ 40.84万
• 依托单位: OREGON STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-25 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10791213
• 关键词: Acceleration; Agreement; Anti-Inflammatory Agents; Area; Artificial Intelligence; Attenuated; Authorization documentation; Biological; Biological Assay; Biological Sciences; Botanical dietary supplements; Botanicals; Cannabidiol; Cannabinoids; Cannabis; Cell Culture Techniques; Cells; Chronic; Collaborations; Consumption; Crystallization; Development; Endocannabinoids; Facility Designs; Feasibility Studies; Female; Flavonoids; Fractionation; Goals; Hemp; Human; Humulus; Individual; Industrialization; Industry; Inflammation; Inflammatory Bowel Diseases; Investments; Knowledge; Laboratories; Leadership; Libraries; Literature; Machine Learning; Marketing; Mass Spectrum Analysis; Measurement; Minor; Modeling; Mothers; Natural Products; Nociception; Nutraceutical; Oregon; PTGS2 gene; Pain; Pain management; Pathologic; Phytochemical; Plant Resins; Plants; Positioning Attribute; Pre-Clinical Model; Production; Property; Recombinants; Reporting; Research; Resources; Role; Signal Pathway; Source; System; TRPV1 gene; Terpenes; Testing; Tetrahydrocannabinol; Therapeutic; Time; Universities; Waste Products; Work; authority; bioactive natural products; chronic pain; chronic pain management; chronic pain patient; clinically relevant; cyclooxygenase 1; distilled alcoholic beverage; endovanilloid; high throughput screening; human disease; human model; inflorescence; innovation; manufacture; manufacturing facility; medical food; natural product derivative; novel; overexpression; pain relief; pain sensation; pain signal; pharmacologic; prenylation; release of sequestered calcium ion into cytoplasm; repository; response; screening services

This project aims to conduct mechanistic research of potential therapeutic benefits of minor cannabinoids in hemp. We propose to integrate Artificial Intelligence in our workflow to accelerate the discovery of bioactive minor cannabinoids. We focus on chronic pain as our therapeutic benefit of non-psychoactive cannabinoids. A large body of literature suggests that terpenophenolics from hemp may have potential in the treatment of pain and other conditions that are driven by low-grade chronic inflammation. The conventional, classic approach to identify potential therapeutics derived from natural products (NPs) is laborious and time-consuming bioassay-guided fractionation. Our AI-assisted approach for the discovery of bioactive NPs accelerates the discovery pipeline, as our feasibility studies show. We expect that we will succeed in identifying bioactive cannabinoids that have previously not been studied in clinically relevant bioassays. Our Specific Aims are: Specific Aim 1: To predict and validate the effects of individual cannabinoids in CBD-depleted hemp extracts in cell culture models relevant to nociception. Columbia Basin Bioscience operates an industrial scale CBD manufacturing facility which makes use of recrystallization of CBD from cannabinoid-enriched hemp extracts. We will use the supernatants of various recrystallization stages (“mother liquors”) as our source of minor cannabinoids in our computation-assisted discovery of bioactives. We will perform calcium flux assays using HEK-293 cells stably over-expressing recombinant human TRPV1 as a cell culture model relevant to nociception. We will also test for FAAH/COX-2 inhibitory activity as dual acting compounds targeting the endocannabinoid and endovanilloid systems are emerging as a novel treatment option for chronic pain management. We will validate the most potent predictors of activity by testing individual, pure cannabinoids in the same assays. We will also determine the bioactivity of 17 minor cannabinoids from our repository of cannabinoid standards, which may or may not include predictors of bioactivity from our discovery pipeline. Specific Aim 2: To predict and validate synergistic/interactive effects between bioactive cannabinoids. Our AI-discovery pipeline has the ability to detect synergistic, additive, or antagonistic effects based on measurements of absolute concentrations of NPs in crude fractions containing bioactive cannabinoids for which we will establish concentration-effect curves. We will quantify the pharmacological interactions among a subset of authentic cannabinoids including 17 minor cannabinoids from our repository of standards which show bioactivity in our assays or which have been reported to attenuate TRPV1-related pain signaling. We expect that the proposed AI-assisted discovery approach will generate cannabinoid candidates that attenuate nociceptive TRPV1-FAAH/COX-1 signaling pathways for further mechanistic testing in preclinical models of pain sensation. The development of minor cannabinoids as pain mitigators from waste products of the CBD-industry will benefit not only chronic pain patients but also a sustainable agro-industry.

本项目旨在对大麻中少量大麻素的潜在治疗益处进行机制研究。我们建议将人工智能整合到我们的工作流程中，以加快发现具有生物活性的微小大麻类化合物。我们专注于慢性疼痛，将其作为非精神活性大麻类药物的治疗益处。大量文献表明，大麻中的萜类酚类化合物可能在治疗疼痛和其他由低级别慢性炎症驱动的疾病方面具有潜力。从天然产物(NPs)中鉴定潜在治疗药物的传统经典方法是费时费力的生物测定引导分级。正如我们的可行性研究显示的那样，我们的人工智能辅助发现生物活性NPs的方法加速了发现管道。我们期望我们能够成功地鉴定出以前没有在临床相关生物检测中进行过研究的生物活性大麻素。我们的具体目标是： 具体目标1：在与伤害相关的细胞培养模型中，预测和验证CBD耗竭的大麻提取物中个别大麻素的作用。哥伦比亚盆地生物科学公司经营着一家工业规模的CBD制造设施，该设施利用从富含大麻的大麻提取物中重结晶CBD。我们将使用不同重结晶阶段的上清液(“母液”)作为我们在计算机辅助发现生物活性中的次要大麻类化合物的来源。我们将使用稳定高表达重组人TRPV1的HEK-293细胞作为与伤害性感受相关的细胞培养模型进行钙离子通量分析。我们还将测试FAAH/COX-2抑制活性，因为针对内源性大麻素和内源性香草素系统的双重作用化合物正在成为一种新的慢性疼痛治疗选择。我们将通过在相同的检测中测试单独的纯大麻类化合物来验证最有效的活性预测因素。我们还将从我们的大麻素标准库中确定17种轻微的大麻类化合物的生物活性，其中可能包括也可能不包括我们的发现流程中的生物活性预测因子。 具体目标2：预测和验证生物活性大麻素之间的协同/相互作用效应。我们的人工智能发现管道能够根据对含有生物活性大麻素的粗馏分中NPs的绝对浓度的测量，检测协同、添加或拮抗效应，我们将为其建立浓度-效应曲线。我们将量化正宗大麻素的子集之间的药理相互作用，包括来自我们的标准库的17种轻微的大麻素，这些标准在我们的检测中显示了生物活性，或者据报道它们可以减弱TRPV1相关的疼痛信号。我们期望所提出的人工智能辅助发现方法将产生大麻类候选化合物，以减弱伤害性TRPV1-FAAH/COX-1信号通路，以便在临床前痛觉模型中进行进一步的机械测试。从CBD工业的废物中开发少量大麻素作为止痛剂，不仅有利于慢性疼痛患者，而且有利于可持续的农用工业。