Kang, H.-W. ; KhudaBukhsh, W. R. ; Koeppl, H. ; Rempala, G. A. (2019)
Quasi-steady-state approximations derived from the stochastic model of enzyme kinetics.
In: Bulletin of Mathematical Biology, 81
doi: 10.1007/s11538-019-00574-4
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
The paper outlines a general approach to deriving quasi-steady-state approximations (QSSAs) of the stochastic reaction networks describing the Michaelis–Menten enzyme kinetics. In particular, it explains how different sets of assumptions about chemical species abundance and reaction rates lead to the standard QSSA, the total QSSA, and the reverse QSSA. These three QSSAs have been widely studied in the literature in deterministic ordinary differential equation settings, and several sets of conditions for their validity have been proposed. With the help of the multiscaling techniques introduced in Ball et al. (Ann Appl Probab 16(4):1925–1961, 2006), Kang and Kurtz (Ann Appl Probab 23(2):529–583, 2013), it is seen that the conditions for deterministic QSSAs largely agree (with some exceptions) with the ones for stochastic QSSAs in the large-volume limits. The paper also illustrates how the stochastic QSSA approach may be extended to more complex stochastic kinetic networks like, for instance, the enzyme–substrate–inhibitor system.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2019 |
| Autor(en): | Kang, H.-W. ; KhudaBukhsh, W. R. ; Koeppl, H. ; Rempala, G. A. |
| Art des Eintrags: | Bibliographie |
| Titel: | Quasi-steady-state approximations derived from the stochastic model of enzyme kinetics |
| Sprache: | Englisch |
| Publikationsjahr: | 12 Februar 2019 |
| Verlag: | Springer |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Bulletin of Mathematical Biology |
| Jahrgang/Volume einer Zeitschrift: | 81 |
| DOI: | 10.1007/s11538-019-00574-4 |
| URL / URN: | https://link.springer.com/article/10.1007/s11538-019-00574-4... |
| Kurzbeschreibung (Abstract): | The paper outlines a general approach to deriving quasi-steady-state approximations (QSSAs) of the stochastic reaction networks describing the Michaelis–Menten enzyme kinetics. In particular, it explains how different sets of assumptions about chemical species abundance and reaction rates lead to the standard QSSA, the total QSSA, and the reverse QSSA. These three QSSAs have been widely studied in the literature in deterministic ordinary differential equation settings, and several sets of conditions for their validity have been proposed. With the help of the multiscaling techniques introduced in Ball et al. (Ann Appl Probab 16(4):1925–1961, 2006), Kang and Kurtz (Ann Appl Probab 23(2):529–583, 2013), it is seen that the conditions for deterministic QSSAs largely agree (with some exceptions) with the ones for stochastic QSSAs in the large-volume limits. The paper also illustrates how the stochastic QSSA approach may be extended to more complex stochastic kinetic networks like, for instance, the enzyme–substrate–inhibitor system. |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Bioinspirierte Kommunikationssysteme 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik |
| Hinterlegungsdatum: | 26 Feb 2019 09:25 |
| Letzte Änderung: | 02 Dez 2021 11:10 |
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