Attenuation of Aging-Related Oxidative Stress Pathways by Phytonutrients: A Computational Systems Biology Analysis.

Aging results from gradual accumulation of damage to the cellular functions caused by biochemical processes such as oxidative stress, inflammation-driven prolonged cellular senescence state, immune system malfunction, psychological stress, and epigenetic changes due to exposure to environmental toxins. Plant-derived bioactive molecules have been shown to ameliorate the damage from oxidative stress. This research seeks to uncover the mechanisms of action of how phytochemicals from fruit/berry/vegetable (FBV) juice powder mitigate oxidative stress. The study uses a computational systems biology approach to (1) identify biomolecular pathways of oxidative stress; (2) identify phytochemicals from FBV juice powder and their specific action on oxidative stress mechanisms; and (3) quantitatively estimate the effects of FBV juice powder bioactive compounds on oxidative stress. The compounds in FBV affected two oxidative stress molecular pathways: (1) reactive oxygen species (ROS) production and (2) antioxidant enzyme production. Six bioactive compounds including cyanidin, delphinidin, ellagic acid, kaempherol, malvidin, and rutin in FBV significantly lowered production of ROS and increased the production of antioxidant enzymes such as catalase, heme oxygenase-1, superoxide dismutase, and glutathione peroxidase. FBV juice powder provides a combination of bioactive compounds that attenuate aging by affecting multiple pathways of oxidative stress.

Mechanistic Understanding of D-Glucaric Acid to Support Liver Detoxification Essential to Muscle Health Using a Computational Systems Biology Approach.

Liver and muscle health are intimately connected. Nutritional strategies that support liver detoxification are beneficial to muscle recovery. Computational-in silico-molecular systems' biology analysis of supplementation of calcium and potassium glucarate salts and their metabolite D-glucaric acid (GA) reveals their positive effect on mitigation of liver detoxification via four specific molecular pathways: (1) ROS production, (2) deconjugation, (3) apoptosis of hepatocytes, and (4) ß-glucuronidase synthesis. GA improves liver detoxification by downregulating hepatocyte apoptosis, reducing glucuronide deconjugates levels, reducing ROS production, and inhibiting ß-Glucuronidase enzyme that reduces re-absorption of toxins in hepatocytes. Results from this in silico study provide an integrative molecular mechanistic systems explanation for the mitigation of liver toxicity by GA.

Attenuation of low-grade chronic inflammation by phytonutrients: A computational systems biology analysis.

BACKGROUND: Low-grade chronic inflammation (LGCI) is a strong and independent risk factor for many chronic diseases, like cardiovascular, musculoskeletal, metabolic, and neurological conditions. Dietary intervention studies have reported evidence for the role of plant-derived flavonoids in modulation of LGCI. This research explores the efficacy of Fruit/Berry/Vegetable (FBV) juice powder on LGCI. METHODS: The study employs computational systems biology: 1) to identify biomolecular mechanisms of LGCI; 2) to identify the bioactive compounds of FBV juice powder and their specific effects on mechanisms of LGCI; and, 3) to predict the quantitative effects of those bioactive compounds on LGCI. RESULTS: Four molecular pathways that are affected by the compounds of FBV include: 1) TNF-α production; 2) CCL2 production; 3) IL-1ß production; and 4) reactive oxygen species production. The bioactive compounds including luteolin, epicatechin, epigallocatechin gallate, lycopene, quercetin, vitamin A, vitamin C and vitamin E in FBV significantly lowered TNF-α production, CCL2 production, IL-1ß production, and reactive oxygen species production. CONCLUSION: FBV provides a combination of active ingredients that synergistically affect multiple modalities of low grade chronic inflammation to help improve blood circulation and energy levels, and lower muscle soreness.

Molecular Systems Architecture of Interactome in the Acute Myeloid Leukemia Microenvironment.

A molecular systems architecture is presented for acute myeloid leukemia (AML) to provide a framework for organizing the complexity of biomolecular interactions. AML is a multifactorial disease resulting from impaired differentiation and increased proliferation of hematopoietic precursor cells involving genetic mutations, signaling pathways related to the cancer cell genetics, and molecular interactions between the cancer cell and the tumor microenvironment, including endothelial cells, fibroblasts, myeloid-derived suppressor cells, bone marrow stromal cells, and immune cells (e.g., T-regs, T-helper 1 cells, T-helper 17 cells, T-effector cells, natural killer cells, and dendritic cells). This molecular systems architecture provides a layered understanding of intra- and inter-cellular interactions in the AML cancer cell and the cells in the stromal microenvironment. The molecular systems architecture may be utilized for target identification and the discovery of single and combination therapeutics and strategies to treat AML.

Bioactive compounds in green tea may improve transplant tolerance: A computational systems biology analysis.

BACKGROUND: Green tea (Camellia sinensis) has bioactive compounds that have been shown to possess nutritive effects on various biomolecular processes such as immunomodulation. This research explores the immunomodulatory effects of green tea in reducing transplant rejection. METHOD: The study employs computational systems biology: 1) to identify biomolecular mechanisms of immunomodulation in transplant rejection; 2) to identify the bioactive compounds of green tea and their specific effects on mechanisms of immunomodulation in transplant rejection; and, 3) to predict the quantitative effects of those bioactive compounds on immunomodulation in transplant rejection. RESULTS: Three bioactive compounds of green tea - epicatechin (EC), gallic acid (GA), and epigallocatechin gallate (EGCG), were identified for their potential effects on immunomodulation of transplant rejection. Of the three, EGCG was the only one determined to enhance anti-inflammatory activity by: 1) upregulating synthesis of HO-1 that is known to promote Treg and Th2 phenotypes associated with enabling transplant tolerance; and, 2) downregulating pro-inflammatory cytokines IL-2, IL-17, IFN-γ, TNF-α, NO, IL-6, and IL-1ß that are known to promote Th1 and Th17 phenotypes associated with transplant rejection. CONCLUSIONS: To the best of our knowledge, this study provides the first molecular mechanistic understanding the clinical nutritive value of green tea, specifically the bioactive compound EGCG, in enabling transplant tolerance.

Multi-Criteria Decision Analysis Model for Assessing the Risk from Multi-Ingredient Dietary Supplements (MIDS).

Military personnel use dietary supplements (DS) for performance enhancement, bodybuilding, weight loss, and to maintain health. Adverse events, including cardiovascular (CV) effects, have been reported in military personnel taking supplements. Previous research determined that ingestion of multi-ingredient dietary supplements (MIDS), can lead to signals of safety concerns. Therefore, to assess the safety of MIDS, the Department of Defense via a contractor explored the development of a model-based risk assessment tool. We present a strategy and preliminary novel multi-criteria decision analysis (MCDA)-based tool for assessing the risk of adverse CV effects from MIDS. The tool integrates toxicology and other relevant data available on MIDS; likelihood of exposure, and biologic plausibility that could contribute to specific aspects of risk.Inputs for the model are values of four measures assigned based on the available evidence supplemented with the opinion of experts in toxicology, modeling, risk assessment etc. Measures were weighted based on the experts' assessment of measures' relative importance. Finally, all data for the four measures were integrated to provide a risk potential of 0 (low risk) to 100 (high risk) that defines the relative risk of a MIDS to cause adverse reactions.We conclude that the best available evidence must be supplemented with the opinion of experts in medicine, toxicology and pharmacology. Model-based approaches are useful to inform risk assessment in the absence of data. This MCDA model provides a foundation for refinement and validation of accuracy of the model predictions as new evidence becomes available.

CytoSolve: A Scalable Computational Method for Dynamic Integration of Multiple Molecular Pathway Models.

A grand challenge of computational systems biology is to create a molecular pathway model of the whole cell. Current approaches involve merging smaller molecular pathway models' source codes to create a large monolithic model (computer program) that runs on a single computer. Such a larger model is difficult, if not impossible, to maintain given ongoing updates to the source codes of the smaller models. This paper describes a new system called CytoSolve that dynamically integrates computations of smaller models that can run in parallel across different machines without the need to merge the source codes of the individual models. This approach is demonstrated on the classic Epidermal Growth Factor Receptor (EGFR) model of Kholodenko. The EGFR model is split into four smaller models and each smaller model is distributed on a different machine. Results from four smaller models are dynamically integrated to generate identical results to the monolithic EGFR model running on a single machine. The overhead for parallel and dynamic computation is approximately twice that of a monolithic model running on a single machine. The CytoSolve approach provides a scalable method since smaller models may reside on any computer worldwide, where the source code of each model can be independently maintained and updated.

Multiscale mathematical modeling to support drug development.

It is widely recognized that major improvements are required in the methods currently being used to develop new therapeutic drugs. The time from initial target identification to commercialization can be 10-14 years and incur a cost in the hundreds of millions of dollars. Even after substantial investment, only 30-40% of the candidate compounds entering clinical trials are successful. We propose that multiscale mathematical pathway modeling can be used to decrease time required to bring candidate drugs to clinical trial and increase the probability that they will be successful in humans. The requirements for multiple time scales and spatial scales are discussed, and new computational paradigms are identified to address the increased complexity of modeling.