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A novel combinatorial approach integrating experimental and computational analysis of antioxidant activity:
Ayeshum Rasool1, Chinanu Chidi1, Sophie Rigaut1
1Chemistry and Biochemistry, University of St. Thomas, Houston, TX, United States of America.
Insights
This study evaluated antioxidant activity in normal and high-triglyceride serum using computational models and the FRAP assay. Results show how serum environments affect antioxidant potency, offering insights for cardiovascular disease interventions.
Area of Science:
- Biochemistry
- Computational Chemistry
- Cardiovascular Science
Background:
- Cardiovascular disease (CVD) is a leading global health issue, with oxidative stress driving its progression through lipid peroxidation and inflammation.
- Antioxidants combat oxidative stress by inhibiting free radical damage, crucial for preventing conditions like atherosclerosis.
- Understanding how serum environments influence antioxidant efficacy is vital for developing targeted interventions.
Purpose of the Study:
- To assess the antioxidant activity of L-ascorbic acid (vitamin C) and catechin in normal and hypertriglyceridemic serum.
- To investigate the impact of hydrophobic serum environments on antioxidant efficacy using computational models.
- To explore a combinatorial approach combining experimental assays and computational simulations for antioxidant evaluation.
Main Methods:
- Optimized the Ferric Reducing Ability of Plasma (FRAP) assay at a microscale to measure antioxidant activity.
- Utilized computational models (Gaussian software) to simulate hydrophilic and hydrophobic serum environments.
- Calculated free energy changes and bond dissociation energy (BDE) via the hydrogen atom transfer (HAT) mechanism.
Main Results:
- Experimental and computational findings demonstrated varying antioxidant activities based on serum composition.
- Hypertriglyceridemic serum, with its increased lipid content, influenced the efficacy of tested antioxidants.
- Computational models accurately predicted antioxidant behavior in different simulated serum environments, aligning with experimental data.
Conclusions:
- A novel combinatorial approach effectively assesses antioxidant activity in diverse serum conditions, including hypertriglyceridemic states.
- Findings provide valuable insights into how serum lipid profiles modulate antioxidant function.
- This research holds potential for informing clinical strategies aimed at managing cardiovascular disease through antioxidant therapies.
Abstract:
Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality globally, with oxidative stress playing a pivotal role in its progression. Free radicals produced via oxidative stress contribute to lipid peroxidation, leading to subsequent inflammatory responses, which then result in atherosclerosis. Antioxidants inhibit these harmful effects through their reducing ability, thereby preventing oxidative damage. In this study, we introduce computational models simulating hydrophilic and hydrophobic serum environments. We optimized the Ferric Reducing Ability of Plasma (FRAP) assay at a microscale level to evaluate the antioxidant activity of L-ascorbic acid (vitamin C) and catechin, a phytochemical found in green tea, in normal and hypertriglyceridemic serum. Hypertriglyceridemic serum, characterized by increased hydrophobic lipid content, provides a model to examine the impact of serum triglycerides on antioxidant activity. Additionally, we employed computational models using the Gaussian software to simulate the hydrogen atom transfer (HAT) mechanism, calculating free energy changes and bond dissociation energy (BDE) to assess the antioxidant potency of the studied compounds in both hydrophilic and hydrophobic environments. The computational results align with the experimental finding offering a unique combinatorial approach to assess antioxidant activity in both normal and hypertriglyceridemic serum, with potential implications for clinical interventions.
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