{"id":8236,"date":"2023-08-10T17:27:38","date_gmt":"2023-08-10T08:27:38","guid":{"rendered":"https:\/\/www.ibs.re.kr\/bimag\/?post_type=tribe_events&p=8236"},"modified":"2023-08-31T13:08:32","modified_gmt":"2023-08-31T04:08:32","slug":"2023-09-01-jc","status":"publish","type":"tribe_events","link":"https:\/\/www.ibs.re.kr\/bimag\/event\/2023-09-01-jc\/","title":{"rendered":"Hyeongjun Jang, Generalized Michaelis\u2013Menten rate law with time-varying molecular concentrations"},"content":{"rendered":"
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We will discuss about \u201cGeneralized Michaelis\u2013Menten rate law with time-varying molecular concentrations\u201d, Lim, Roktaek, et al.,bioRxiv (2022): 2022-01<\/p>\n

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Abstract<\/p>\n

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The Michaelis\u2013Menten (MM) rate law has been the dominant paradigm of modeling biochemical rate processes for over a century with applications in biochemistry, biophysics, cell biology, and chemical engineering. The MM rate law and its remedied form stand on the assumption that the concentration of the complex of interacting molecules, at each moment, approaches an equilibrium much faster than the molecular concentrations change. Yet, this assumption is not always justified. Here, we relax this quasi-steady state requirement and propose the generalized MM rate law for the interactions of molecules with active concentration changes over time. Our approach for time-varying molecular concentrations, termed the effective time-delay scheme (ETS), is based on rigorously estimated time-delay effects in molecular complex formation. With particularly marked improvements in protein\u2013 protein and protein\u2013DNA interaction modeling, the ETS provides an analytical framework to interpret and predict rich transient or rhythmic dynamics (such as autogenously-regulated cellular adaptation and circadian protein turnover), which goes beyond the quasi-steady state assumption.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n

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