  Extracting the intrinsic kinetic information of biological molecule from its
single-molecule kinetic data is of considerable biophysical interest. In this
work, we theoretically investigate the feasibility of inferring single RNA's
intrinsic kinetic parameters from the time series obtained by forced
folding/unfolding experiment done in the light tweezer, where the molecule is
flanked by long double-stranded DNA/RNA handles and tethered between two big
beads. We first construct a coarse-grain physical model of the experimental
system. The model has captured the major physical factors: the Brownian motion
of the bead, the molecular structural transition, and the elasticity of the
handles and RNA. Then based on an analytic solution of the model, a Bayesian
method using Monte Carlo Markov Chain is proposed to infer the intrinsic
kinetic parameters of the RNA from the noisy time series of the distance or
force. Because the force fluctuation induced by the Brownian motion of the bead
and the structural transition can significantly modulate the transition rates
of the RNA, we prove that, this statistic method is more accurate and efficient
than the conventional histogram fitting method in inferring the molecule's
intrinsic parameters.
