2007
DOI: 10.1073/pnas.0611519104
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Extending the absorbing boundary method to fit dwell-time distributions of molecular motors with complex kinetic pathways

Abstract: Dwell-time distributions, waiting-time distributions, and distributions of pause durations are widely reported for molecular motors based on single-molecule biophysical experiments. These distributions provide important information concerning the functional mechanisms of enzymes and their underlying kinetic and mechanical processes. We have extended the absorbing boundary method to simulate dwell-time distributions of complex kinetic schemes, which include cyclic, branching, and reverse transitions typically o… Show more

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Cited by 25 publications
(30 citation statements)
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“…On the other hand, it has been claimed [6] that difference of two exponentials fit the experimentally measured f (t) very well. We reconcile these two observations by identifying the parameter regime where our theoretically derived f (t) is, indeed, well approximated by difference of two exponentials [7,8,9,10,11]. Moreover, we show that t −1 , inverse of the mean dwell time, satisfies a Michaelis-Menten-like equation [12].…”
Section: Introductionsupporting
confidence: 72%
“…On the other hand, it has been claimed [6] that difference of two exponentials fit the experimentally measured f (t) very well. We reconcile these two observations by identifying the parameter regime where our theoretically derived f (t) is, indeed, well approximated by difference of two exponentials [7,8,9,10,11]. Moreover, we show that t −1 , inverse of the mean dwell time, satisfies a Michaelis-Menten-like equation [12].…”
Section: Introductionsupporting
confidence: 72%
“…Recently, a new absorbing boundary method has been proposed for understanding dynamics of molecular motors. 23 Although the method is powerful, it requires some knowledge of the network topology and it is not efficient in obtaining average values such as mean times. 23 In this article, we develop a new method to predict structural and dynamic information of the underlying chemical and biological networks by analyzing distributions of events without assuming any specific model.…”
Section: Introductionmentioning
confidence: 99%
“…We obtain the lifetime pdf for our system through solution of a master equation for the probabilities of being in any of the underlying biochemical states (open complex, closed complex, or dissociated). This is a standard and straightforward method for obtaining wait-time probabilities for Markov processes with discrete states; Liao et al 16 applied a similar analysis to molecular motor dwell time records. In brief, the procedure is as follows:…”
Section: Dwell-time Distribution Analysismentioning
confidence: 99%