NDLI: Maximum Likelihood Estimation of Molecular Motor Kinetics from Staircase Dwell-Time Sequences

Content Provider	PubMed Central
Author	Milescu, Lorin S. Yildiz, Ahmet Selvin, Paul R. Sachs, Frederick
Copyright Year	2006
Abstract	Molecular motors, such as kinesin, myosin, or dynein, convert chemical energy into mechanical energy by hydrolyzing ATP. The mechanical energy is used for moving in discrete steps along the cytoskeleton and carrying a molecular load. High resolution single molecule recordings of motor steps appear as a stochastic sequence of dwells, resembling a staircase. Staircase data can also be obtained from other molecular machines such as F1-ATPase, RNA polymerase, or topoisomerase. We developed a maximum likelihood algorithm that estimates the rate constants between different conformational states of the protein, including motor steps. We model the motor with a periodic Markov model that reflects the repetitive chemistry of the motor step. We estimated the kinetics from the idealized dwell-sequence by numerical maximization of the likelihood function for discrete-time Markov models. This approach eliminates the need for missed event correction. The algorithm can fit kinetic models of arbitrary complexity, such as uniform or alternating step chemistry, reversible or irreversible kinetics, ATP concentration and mechanical force-dependent rates, etc. The method allows global fitting across stationary and nonstationary experimental conditions, and user-defined a priori constraints on rate constants. The algorithm was tested with simulated data, and implemented in the free QuB software.
Related Links	http://dx.doi.org/10.1529/biophysj.105.079541
Ending Page	1168
Page Count	13
Starting Page	1156
File Format	PDF
ISSN	00063495
e-ISSN	15420086
Journal	Biophysical Journal
Issue Number	4
Volume Number	91
Language	English
Publisher	Biophysical Society
Publisher Date	2006-08-01
Access Restriction	Open
Rights Holder	Biophysical Society
Subject Keyword	Biophysics Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Biophysics

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