{"title":"超越迈克尔斯-门顿混沌的异相速率控制","authors":"Tjeerd V. olde Scheper","doi":"arxiv-2401.04786","DOIUrl":null,"url":null,"abstract":"The method developed by Michaelis and Menten was foundational in the\ndevelopment of our understanding of biochemical reaction kinetics. Extended\nmodels of metabolism encapsulated by reaction rate theory, stochastic reaction\nmodels, and dynamic flux estimation, amongst others, address aspects of this\nfundamental idea. The limitations of these approaches are well understood, and\nefforts to overcome those issues so far have been plentiful but with limited\nsuccess. The known issues can be summarised as the sole dependent relation with\nsubstrate concentration, the encapsulation of rate in a single relevant scalar,\nand the subsequent lack of functional control that results from this\nassumption. The Rate Control of Chaos (RCC) is a nonlinear control method that\nhas been shown to be effective in controlling the dynamic state of biological\noscillators based on the concept of rate limitation of the exponential growth\nin chaotic systems. Extending RCC with allosteric properties allows robust\ncontrol of the enzymatic process, and replicates the Michaelis-Menten kinetics.\nThe emergent dynamics is robust to perturbations and noise but susceptible to\nregulatory adjustments. This control method adapts the control parameters\ndynamically in the presence of a ligand, and permits introduction of energy\nrelations into the control function. The dynamic nature of the control\neliminates the steady-state requirements and allows the modelling of\nlarge-scale dynamic behaviour, potentially addressing issues in metabolic\ndisorder and failure of metabolic control.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"9 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Beyond Michaelis-Menten: Allosteric Rate Control of Chaos\",\"authors\":\"Tjeerd V. olde Scheper\",\"doi\":\"arxiv-2401.04786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The method developed by Michaelis and Menten was foundational in the\\ndevelopment of our understanding of biochemical reaction kinetics. Extended\\nmodels of metabolism encapsulated by reaction rate theory, stochastic reaction\\nmodels, and dynamic flux estimation, amongst others, address aspects of this\\nfundamental idea. The limitations of these approaches are well understood, and\\nefforts to overcome those issues so far have been plentiful but with limited\\nsuccess. The known issues can be summarised as the sole dependent relation with\\nsubstrate concentration, the encapsulation of rate in a single relevant scalar,\\nand the subsequent lack of functional control that results from this\\nassumption. The Rate Control of Chaos (RCC) is a nonlinear control method that\\nhas been shown to be effective in controlling the dynamic state of biological\\noscillators based on the concept of rate limitation of the exponential growth\\nin chaotic systems. Extending RCC with allosteric properties allows robust\\ncontrol of the enzymatic process, and replicates the Michaelis-Menten kinetics.\\nThe emergent dynamics is robust to perturbations and noise but susceptible to\\nregulatory adjustments. This control method adapts the control parameters\\ndynamically in the presence of a ligand, and permits introduction of energy\\nrelations into the control function. The dynamic nature of the control\\neliminates the steady-state requirements and allows the modelling of\\nlarge-scale dynamic behaviour, potentially addressing issues in metabolic\\ndisorder and failure of metabolic control.\",\"PeriodicalId\":501170,\"journal\":{\"name\":\"arXiv - QuanBio - Subcellular Processes\",\"volume\":\"9 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuanBio - Subcellular Processes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2401.04786\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Subcellular Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2401.04786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Beyond Michaelis-Menten: Allosteric Rate Control of Chaos
The method developed by Michaelis and Menten was foundational in the
development of our understanding of biochemical reaction kinetics. Extended
models of metabolism encapsulated by reaction rate theory, stochastic reaction
models, and dynamic flux estimation, amongst others, address aspects of this
fundamental idea. The limitations of these approaches are well understood, and
efforts to overcome those issues so far have been plentiful but with limited
success. The known issues can be summarised as the sole dependent relation with
substrate concentration, the encapsulation of rate in a single relevant scalar,
and the subsequent lack of functional control that results from this
assumption. The Rate Control of Chaos (RCC) is a nonlinear control method that
has been shown to be effective in controlling the dynamic state of biological
oscillators based on the concept of rate limitation of the exponential growth
in chaotic systems. Extending RCC with allosteric properties allows robust
control of the enzymatic process, and replicates the Michaelis-Menten kinetics.
The emergent dynamics is robust to perturbations and noise but susceptible to
regulatory adjustments. This control method adapts the control parameters
dynamically in the presence of a ligand, and permits introduction of energy
relations into the control function. The dynamic nature of the control
eliminates the steady-state requirements and allows the modelling of
large-scale dynamic behaviour, potentially addressing issues in metabolic
disorder and failure of metabolic control.