Production-passage-time approximation: A new approximation method to accelerate the simulation process of enzymatic reactions

Hiroyuki Kuwahara*, Chris Myers

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


Given the substantial computational requirements of stochastic simulation, approximation is essential for efficient analysis of any realistic biochemical system. This paper introduces a new approximation method to reduce the computational cost of stochastic simulations of an enzymatic reaction scheme which in biochemical systems often includes rapidly changing fast reactions with enzyme and enzyme-substrate complex molecules present in very small counts. Our new method removes the substrate dissociation reaction by approximating the passage time of the formation of each enzyme-substrate complex molecule which is destined to a production reaction. This approach skips the firings of unimportant yet expensive reaction events, resulting in a substantial acceleration in the stochastic simulations of enzymatic reactions. Additionally, since all the parameters used in our new approach can be derived by the Michaelis-Menten parameters which can actually be measured from experimental data, applications of this approximation can be practical even without having full knowledge of the underlying enzymatic reaction. Furthermore, since our approach does not require a customized simulation procedure for enzymatic reactions, it allows biochemical systems that include such reactions to still take advantage of standard stochastic simulation tools. Here, we apply this new method to various enzymatic reaction systems, resulting in a speedup of orders of magnitude in temporal behavior analysis without any significant loss in accuracy.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 11th Annual International Conference, RECOMB 2007, Proceedings
PublisherSpringer Verlag
Number of pages15
ISBN (Print)3540716807, 9783540716808
StatePublished - Jan 1 2007
Event11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007 - Oakland, CA, United States
Duration: Apr 21 2007Apr 25 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4453 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007
CountryUnited States
CityOakland, CA

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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