View source for Dynamic disorder in single enzyme kinetics: effects of conformational fluctuations

Enzymes are dynamic entities: their conformations as well as catalytic activity fluctuate over 
time. A number of recent single-molecule experiments have shown that the catalytic activity of 
single enzymes can change with time, producing measurable kinetic effects, including time- 
dependent rate constants (a phenomenon known as dynamic disorder) and nonexponential 
waiting time distributions between successive turnover events. These effects are believed to be 
largely the result of slow conformational fluctuations between different states of the enzyme with 
distinct reactivities.  A model of barrier crossing dynamics governed by fractional Gaussian noise 
and the generalized Langevin equation used to study the reaction kinetics of single enzymes 
subject to conformational fluctuations will be discussed. The direct application of Kramers's 
flux-over-population method to this model yields analytic expressions for the distribution of 
waiting times for barrier crossing. These expressions are found to reproduce the observed trends 
in recent experiments. 
 
Xie et. al have recently experimentally demonstrated that the Michelis Menten(MM) behavior 
of the average number of catalytic turnovers per unit time (for beta-galactosidase) still holds 
even in the presence of slow protein conformational fluctuations. The role of conformational 
dynamics on the dynamics of coupled enzymatic reactions (network) will be discussed. Our goal 
is to examine the limits in which such detailed dynamics can be simplified to a conventional rate- 
equation formalism by integration over conformational degrees of freedom, derive the relation 
between microscopic and macroscopic parameters and to investigate the validity of detailed 
balance conditions. Finally we investigate the influence of conformational fluctuations on 
networks nonlinear dynamics when conventional rate-equation formalism fails.