jp6b05625_si_001.pdf (1.78 MB)
Predicting Molecular Crowding Effects in Ion–RNA Interactions
journal contribution
posted on 2016-08-04, 00:00 authored by Tao Yu, Yuhong Zhu, Zhaojian He, Shi-Jie ChenWe develop a new statistical mechanical
model to predict the molecular
crowding effects in ion–RNA interactions. By considering discrete
distributions of the crowders, the model can treat the main crowder-induced
effects, such as the competition with ions for RNA binding, changes
of electrostatic interaction due to crowder-induced changes in the
dielectric environment, and changes in the nonpolar hydration state
of the crowder–RNA system. To enhance the computational efficiency,
we sample the crowder distribution using a hybrid approach: For crowders
in the close vicinity of RNA surface, we sample their discrete distributions;
for crowders in the bulk solvent away from the RNA surface, we use
a continuous mean-field distribution for the crowders. Moreover, using
the tightly bound ion (TBI) model, we account for ion fluctuation
and correlation effects in the calculation for ion–RNA interactions.
Applications of the model to a variety of simple RNA structures such
as RNA helices show a crowder-induced increase in free energy and
decrease in ion binding. Such crowding effects tend to contribute
to the destabilization of RNA structure. Further analysis indicates
that these effects are associated with the crowder–ion competition
in RNA binding and the effective decrease in the dielectric constant.
This simple ion effect model may serve as a useful framework for modeling
more realistic crowders with larger, more complex RNA structures.