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On distributions of barrier crossing times as observed in single-molecule studies of biomolecules

Alexander M. Berezhkovskii, Dmitrii E. Makarov

2021Biophysical Reports18 citationsDOIOpen Access PDF

Abstract

Single-molecule experiments that monitor time evolution of molecular observables in real time have expanded beyond measuring transition rates toward measuring distributions of times of various molecular events. Of particular interest is the first-passage time for making a transition from one molecular configuration (a) to another (b) and conditional first-passage times such as the transition path time, which is the first-passage time from a to b conditional upon not leaving the transition region intervening between a and b. Another experimentally accessible (but not yet studied experimentally) observable is the conditional exit time, i.e., the time to leave the transition region through a specified boundary. The distributions of such times contain a wealth of mechanistic information about the transitions in question. Here, we use the first and the second (and, if desired, higher) moments of these distributions to characterize their relative width for the model in which the experimental observable undergoes Brownian motion in a potential of mean force. We show that although the distributions of transition path times are always narrower than exponential (in that the ratio of the standard deviation to the distribution’s mean is always less than 1), distributions of first-passage times and of conditional exit times can be either narrow or broad, in some cases displaying long power-law tails. The conditional exit time studied here provides a generalization of the transition path time that also allows one to characterize the temporal scales of failed barrier crossing attempts.

Topics & Concepts

ObservableStatistical physicsFirst-hitting-time modelPath (computing)Conditional probability distributionPhysicsDistribution (mathematics)Boundary (topology)Brownian motionConditional probabilityGeneralizationProbability distributionExponential functionPower lawMathematicsStatisticsQuantum mechanicsMathematical analysisComputer scienceProgramming languageAdvanced Fluorescence Microscopy TechniquesAdvanced Thermodynamics and Statistical MechanicsSpectroscopy and Quantum Chemical Studies