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See detailDCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling.
Kishk, Ali UL; Pires Pacheco, Maria Irene UL; Sauter, Thomas UL

in iScience (2021), 24(11), 103331

The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no approved effective antiviral drug. Flux balance analysis (FBA) is an efficient method to analyze metabolic networks ... [more ▼]

The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no approved effective antiviral drug. Flux balance analysis (FBA) is an efficient method to analyze metabolic networks. Here, FBA was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the virus replication within the host tissue. Making use of expression datasets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then, host-specific essential genes and gene pairs were determined through in silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, ferroptosis, and pyrimidine metabolism. By in silico screening of Food and Drug Administration (FDA)-approved drugs on the putative disease-specific essential genes and gene pairs, 85 drugs and 52 drug combinations were predicted as promising candidates for COVID-19 (https://github.com/sysbiolux/DCcov). [less ▲]

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See detailImportance of the biomass formulation for cancer metabolic modeling and drug prediction.
Moscardo Garcia, Maria UL; Pires Pacheco, Maria Irene UL; Bintener, Tamara Jean Rita UL et al

in iScience (2021), 24(10), 103110

Genome-scale metabolic reconstructions include all known biochemical reactions occurring in a cell. A typical application is the prediction of potential drug targets for cancer treatment. The precision of ... [more ▼]

Genome-scale metabolic reconstructions include all known biochemical reactions occurring in a cell. A typical application is the prediction of potential drug targets for cancer treatment. The precision of these predictions relies on the definition of the objective function. Generally, the biomass reaction is used to illustrate the growth capacity of a cancer cell. Today, seven human biomass reactions can be identified in published metabolic models. The impact of these differences on the metabolic model predictions has not been explored in detail. We explored this impact on cancer metabolic model predictions and showed that the metabolite composition and the associated coefficients had a large impact on the growth rate prediction accuracy, whereas gene essentiality predictions were mainly affected by the metabolite composition. Our results demonstrate the importance of defining a consensus biomass reaction compatible with most human models, which would contribute to ensuring the reproducibility and consistency of the results. [less ▲]

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See detailBusiness Models and Profitability of Energy Storage
Baumgarte, Felix; Glenk, Gunther; Rieger, Alexander UL

in iScience (2020), 23(10),

Rapid growth of intermittent renewable power generation makes the identification of investment opportunities in energy storage and the establishment of their profitability indispensable. Here we first ... [more ▼]

Rapid growth of intermittent renewable power generation makes the identification of investment opportunities in energy storage and the establishment of their profitability indispensable. Here we first present a conceptual framework to characterize business models of energy storage and systematically differentiate investment opportunities. We then use the framework to examine which storage technologies can perform the identified business models and review the recent literature regarding the profitability of individual combinations of business models and technologies. Our analysis shows that a set of commercially available technologies can serve all identified business models. We also find that certain combinations appear to have approached a tipping point toward profitability. Yet, this conclusion only holds for combinations examined most recently or stacking several business models. Many technologically feasible combinations have been neglected, indicating a need for further research to provide a detailed and conclusive understanding about the profitability of energy storage. [less ▲]

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See detailHuman Dopaminergic Neurons Lacking PINK1 Exhibit Disrupted Dopamine Metabolism Related to Vitamin B6 Co-Factors.
Bus, Christine; Zizmare, Laimdota; Feldkaemper, Marita et al

in iScience (2020), 23(12), 101797

PINK1 loss-of-function mutations cause early onset Parkinson disease. PINK1-Parkin mediated mitophagy has been well studied, but the relevance of the endogenous process in the brain is debated. Here, the ... [more ▼]

PINK1 loss-of-function mutations cause early onset Parkinson disease. PINK1-Parkin mediated mitophagy has been well studied, but the relevance of the endogenous process in the brain is debated. Here, the absence of PINK1 in human dopaminergic neurons inhibits ionophore-induced mitophagy and reduces mitochondrial membrane potential. Compensatory, mitochondrial renewal maintains mitochondrial morphology and protects the respiratory chain. This is paralleled by metabolic changes, including inhibition of the TCA cycle enzyme mAconitase, accumulation of NAD(+), and metabolite depletion. Loss of PINK1 disrupts dopamine metabolism by critically affecting its synthesis and uptake. The mechanism involves steering of key amino acids toward energy production rather than neurotransmitter metabolism and involves cofactors related to the vitamin B6 salvage pathway identified using unbiased multi-omics approaches. We propose that reduction of mitochondrial membrane potential that cannot be controlled by PINK1 signaling initiates metabolic compensation that has neurometabolic consequences relevant to Parkinson disease. [less ▲]

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