ABSTRACT Oxidative stress and inflammation (OSI) occurs naturally during many biological processes including digestion, metabolism, and exercise. While small, transient amounts of OSI are considered normal, unregulated, or chronic OSI can damage the vascular-circulatory system, which can result in chronic illnesses such as cardiovascular disease (CVD), atherosclerosis, and cancer. Antioxidant phytochemicals have the capacity to mitigate OSI through radical scavenging activity or the induction of endogenous mechanisms, but to achieve optimal reductions in OSI, the timing of antioxidant effects must occur during the onset of OSI – a concept known as ‘bio-matching.’ Additionally, the bioavailability and antioxidant capacity of active phytochemicals should be accounted for during pharmacokinetic assessments to guide bio-matching. Herein two quantitative structure–activity relationship (QSAR) predictive models are presented: the intestinal absorption prediction (IBP) model for predicting compound bioavailability (r2 = 0.93), and the phytochemical relative antioxidant potential prediction (PRAPP) model for predicting antioxidant capacity (r2 = 0.89). Application of these models to a characterized hemp meal phytochemical profile, along with established models for predicting Tmax and T½, generated a composite antioxidant fingerprint, which predicted a peak in antioxidant activity 36 min after ingestion in liquid form. Accordingly, hemp meal-based protein powders (a common exercise supplement) should be consumed 26 min prior to completion of exercise to achieve bio-matching with the onset of exercise-induced OSI 10 min after exercise. The IBP and PRAPP models presented herein could be useful tools in understanding phytochemical complex antioxidant pharmacodynamics and in optimizing the consumption of hemp meal and other functional foods to achieve bio-matching of composite antioxidant activity with OSI profiles. Abbreviations 4-HPP: 4-hydroxyphenylpyruvic acid; ABTS: 2,2ʹ-azinobis(3-ethyl-benzothiazoline-6-sulfonate); DPPH: 1,1-diphenyl-2-picrylhydrazyl; FRAP: Ferric reducing antioxidant power; HPLC: high-pressure liquid chromatography; IAP: inhalation absorption prediction; IBP: intestinal bioavailability prediction; Log P: lipophilicity descriptor; MW: molecular weight; Nrot: number of rotatable bonds; OSI: oxidative stress and inflammation; PCAP: phytochemical absorption prediction; PDC: plasma drug concentration; PRAPP: phytochemical relative antioxidant potential prediction; QSAR: quantitative structure–activity relationship; ROS: reactive oxygen species; T½: elimination half-life; TEAC: Trolox equivalent antioxidant capacity; Tmax: time of maximal plasma concentration; TPSA: topological polar surface area; V: molecular volume.

中文翻译：

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开发肠道生物利用度预测 (IBP) 和植物化学相对抗氧化潜力预测 (PRAPP) 模型，以优化大麻（大麻）的功能性食品价值

摘要氧化应激和炎症 (OSI) 在许多生物过程中自然发生，包括消化、代谢和运动。虽然少量、短暂的 OSI 被认为是正常的、不受管制的或慢性的 OSI 会损害血管循环系统，这可能导致慢性疾病，如心血管疾病 (CVD)、动脉粥样硬化和癌症。抗氧化植物化学物质有能力通过自由基清除活动或内源性机制的诱导减轻 OSI，但要实现 OSI 的最佳降低，抗氧化作用的时间必须发生在 OSI 发作期间——这一概念被称为“生物匹配”。此外，在药代动力学评估期间应考虑活性植物化学物质的生物利用度和抗氧化能力，以指导生物匹配。本文提出了两种定量构效关系 (QSAR) 预测模型：用于预测化合物生物利用度的肠道吸收预测 (IBP) 模型 (r2 = 0.93)，以及用于预测抗氧化能力的植物化学相对抗氧化潜力预测 (PRAPP) 模型 (r2 = 0.89）。将这些模型应用于具有特征的大麻粉植物化学特征，以及用于预测 Tmax 和 T1/2 的已建立模型，生成了复合抗氧化指纹，其预测了以液体形式摄入后 36 分钟的抗氧化活性峰值。因此，应在完成运动前 26 分钟食用基于大麻粉的蛋白粉（一种常见的运动补充剂），以实现与运动后 10 分钟运动诱发的 OSI 发作的生物匹配。本文提出的 IBP 和 PRAPP 模型可能是了解植物化学复合抗氧化药效学和优化大麻粉和其他功能性食品的消费以实现复合抗氧化活性与 OSI 谱的生物匹配的有用工具。缩写 4-HPP：4-羟基苯基丙酮酸；ABTS：2,2ʹ-azinobis(3-ethyl-benzothiazoline-6-sulfonate)；DPPH：1,1-二苯基-2-苦基肼；FRAP：铁还原抗氧化能力；HPLC：高压液相色谱；IAP：吸入吸收预测；IBP：肠道生物利用度预测；Log P：亲脂性描述符；MW：分子量；Nrot：可旋转债券的数量；OSI：氧化应激和炎症；PCAP：植物化学吸收预测；PDC：血浆药物浓度；普拉普：植物化学相对抗氧化潜力预测；QSAR：定量构效关系；ROS：活性氧；T½：消除半衰期；TEAC：Trolox 等效抗氧化能力；Tmax：最大血浆浓度时间；TPSA：拓扑极性表面积；V：分子体积。