Computation-assisted discovery of bioactive minor cannabinoids from hemp

本项目旨在对大麻中微量大麻素的潜在治疗作用进行机理研究。我们建议将人工智能整合到我们的工作流程中，以加速生物活性小大麻素的发现。我们关注慢性疼痛作为非精神活性大麻素的治疗益处。大量文献表明，大麻中的萜酚类物质可能具有治疗疼痛和其他由低度慢性炎症引起的疾病的潜力。从天然产物（NPs）中识别潜在治疗药物的传统、经典方法是费力且耗时的生物测定引导分离。正如我们的可行性研究所表明的那样，我们的人工智能辅助方法可以加速发现生物活性NPs的过程。我们期望我们将成功地识别以前未在临床相关生物测定中研究过的生物活性大麻素。我们的具体目标是：

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.