  We demonstrate the use of multiscale polymer modelling to quantitatively
predict DNA linear dichroism (LD) in shear flow. LD is the difference in
absorption of light polarised along two perpendicular axes, and has long been
applied to study biopolymer structure and drug-biopolymer interactions. As LD
is orientation-dependent, the sample must be aligned in order to measure a
signal. Shear flow via a Couette cell can generate the required orientation,
however it is challenging to separate the LD due to changes in polymer
conformation from specific interactions, e.g. drug-biopolymer. In this study,
we have applied a combination of Brownian dynamics and equilibrium Monte Carlo
simulations to accurately predict polymer alignment, and hence flow LD, at
modest computational cost. As the optical and conformational contributions to
the LD can be explicitly separated, our findings allow for enhanced
quantitative interpretation of LD spectra through the use of an in-silico model
to capture conformational changes. Our model requires no fitting and only five
input parameters, the DNA contour length, persistence length, optical factor,
solvent quality, and relaxation time, all of which have been well characterized
in prior literature. The method is sufficiently general to apply to a wide
range of biopolymers beyond DNA, and our findings could help guide the search
for new pharmaceutical drug targets via flow LD.
