posted on 2023-11-21, 19:11authored byUtkarsh Kapoor, Young C. Kim, Jeetain Mittal
Recent advances in coarse-grained (CG) computational
models for
DNA have enabled molecular-level insights into the behavior of DNA
in complex multiscale systems. However, most existing CG DNA models
are not compatible with CG protein models, limiting their applications
for emerging topics such as protein–nucleic acid assemblies.
Here, we present a new computationally efficient CG DNA model. We
first use experimental data to establish the model’s ability
to predict various aspects of DNA behavior, including melting thermodynamics
and relevant local structural properties such as the major and minor
grooves. We then employ an all-atom hydropathy scale to define nonbonded
interactions between protein and DNA sites, to make our DNA model
compatible with an existing CG protein model (HPS-Urry), which is
extensively used to study protein phase separation, and show that
our new model reasonably reproduces the experimental binding affinity
for a prototypical protein–DNA system. To further demonstrate
the capabilities of this new model, we simulate a full nucleosome
with and without histone tails, on a microsecond time scale, generating
conformational ensembles and provide molecular insights into the role
of histone tails in influencing the liquid–liquid phase separation
(LLPS) of HP1α proteins. We find that histone tails interact
favorably with DNA, influencing the conformational ensemble of the
DNA and antagonizing the contacts between HP1α and DNA, thus
affecting the ability of DNA to promote LLPS of HP1α. These
findings shed light on the complex molecular framework that fine-tunes
the phase transition properties of heterochromatin proteins and contributes
to heterochromatin regulation and function. Overall, the CG DNA model
presented here is suitable to facilitate micrometer-scale studies
with sub-nm resolution in many biological and engineering applications
and can be used to investigate protein–DNA complexes, such
as nucleosomes, or LLPS of proteins with DNA, enabling a mechanistic
understanding of how molecular information may be propagated at the
genome level.