Robustness analysis of the detailed kinetic model of an ErbB signaling network by using dynamic sensitivity

Masunaga, Hiroyuki; Sugimoto, Yurie; Magi, Shigeyuki; Itasaki, Ryunosuke; Okada‐Hatakeyama, Mariko; Kurata, Hiroyuki

doi:10.1371/journal.pone.0178250

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…To investigate the robustness of the model, the relative change of metabolite concentrations with respect to a change in a kinetic constant were evaluated. Sensitivity analysis explores some mechanisms by which a system of interest generates robustness and remarkable changes (Masunaga et al, 2017). The dynamic sensitivity of target parameter y with respect to a change in specific constant parameter p is given by:…”

Section: Dynamic Sensitivity Analysismentioning

confidence: 99%

Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes

Kurata

2021

iScience

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Summary A virtual metabolic human model is a valuable complement to experimental biology and clinical studies, because in vivo research involves serious ethical and technical problems. I have proposed a multi-organ and multi-scale kinetic model that formulates the reactions of enzymes and transporters with the regulation of hormonal actions at postprandial and postabsorptive states. The computational model consists of 202 ordinary differential equations for metabolites with 217 reaction rates and 1,140 kinetic parameter constants. It is the most comprehensive, largest, and highly predictive model of the whole-body metabolism. Use of the model revealed the mechanisms by which individual disorders, such as steatosis, β cell dysfunction, and insulin resistance, were combined to cause diabetes. The model predicted a glycerol kinase inhibitor to be an effective medicine for type 2 diabetes, which not only decreased hepatic triglyceride but also reduced plasma glucose. The model also enabled us to rationally design combination therapy.

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Section: Dynamic Sensitivity Analysismentioning

confidence: 99%

Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes

Kurata

2021

iScience

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“…To investigate the robustness of the model, the relative change of metabolite concentrations with respect to a change in a kinetic constant were evaluated. Sensitivity analysis explores some mechanisms by which a system of interest generates robustness and remarkable changes (43). The dynamic sensitivity of target parameter y with respect to a change in specific constant parameter p is given by:…”

Section: Dynamic Sensitivity Analysismentioning

confidence: 99%

Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes

Kurata

2020

Preprint

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A virtual metabolic human model is a valuable complement to experimental biology and clinical studies, because in vivo research involves serious ethical and technical issues. A whole-body dynamic model is required not only to reproduce a variety of physiological and metabolic functions, but also to analyze pathology and design drugs. I first proposed a virtual metabolic human model, a multi-organ and multi-scale kinetic model of the whole-body metabolism that formulates the reactions of enzymes and transporters with the regulation of enzyme activities and hormonal actions under prandial and rest conditions. To accurately simulate metabolic changes and robustness, the model incorporates nucleotide cofactors that are critically responsible for global feedback regulations to adapt to metabolic changes. The model predicted a two-phase hepatic fatty acid production that consists of the synthesis of malonyl-CoA and the NADPH-dependent synthesis of fatty acid. The model performed pathological analysis of type 2 diabetes. I divided type 2 diabetes into specific disorders of steatosis, β cell dysfunction and insulin resistance for each organ, and analyzed the effect of the individual disorders on the dynamics of plasma glucose (hyperglycemia) and hepatic TG (steatosis). The model suggested that a chronic or irreversible change in hepatic TG accumulation plays a critical role in disease progression. The model predicted a glycerol kinase inhibitor to be a new medicine for type 2 diabetes, because it not only decreased hepatic TG but also reduced plasma glucose, unexpectedly. The model also enabled us to rationally design combination therapy.

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“…В отсутствие лигандов ERBB-ре-цепторы не обладают киназной активностью. Следует отметить, что ERBB2 и ERBB3 не являются автономно дей-ствующими РТК, но образуют функционально активные гетеродимеры [10].…”

Section: основные клеточные сигнальные пути вовлеченные в патогенез unclassified

Molecular Basis of Modern Targeted Therapy for Squamous Cell Carcinoma of the Tongue and Oral Mucosa With Monoclonal Antibodies

Льянова¹,

Владимирова²,

Франциянц³

et al. 2017

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Robustness analysis of the detailed kinetic model of an ErbB signaling network by using dynamic sensitivity

Cited by 4 publications

References 24 publications

Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes

Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes

Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes

Molecular Basis of Modern Targeted Therapy for Squamous Cell Carcinoma of the Tongue and Oral Mucosa With Monoclonal Antibodies

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