posted on 2024-01-19, 17:40authored byDebayan Chakraborty, Balaka Mondal, D. Thirumalai
DNA–protein
interactions are pervasive in a number of biophysical
processes ranging from transcription and gene expression to chromosome
folding. To describe the structural and dynamic properties underlying
these processes accurately, it is important to create transferable
computational models. Toward this end, we introduce Coarse-grained Force Field for Energy Estimation, COFFEE, a robust framework for simulating
DNA–protein complexes. To brew COFFEE, we integrated the energy
function in the self-organized polymer model with side-chains for
proteins and the three interaction site model for DNA in a modular
fashion, without recalibrating any of the parameters in the original
force-fields. A unique feature of COFFEE is that it describes sequence–specific
DNA–protein interactions using a statistical potential (SP)
derived from a data set of high-resolution crystal structures. The
only parameter in COFFEE is the strength (λDNAPRO) of the DNA–protein contact potential. For an optimal choice
of λDNAPRO, the crystallographic B-factors for DNA–protein complexes with varying sizes and
topologies are quantitatively reproduced. Without any further readjustments
to the force-field parameters, COFFEE predicts scattering profiles
that are in quantitative agreement with small-angle X-ray scattering
experiments, as well as chemical shifts that are consistent with NMR.
We also show that COFFEE accurately describes the salt-induced unraveling
of nucleosomes. Strikingly, our nucleosome simulations explain the
destabilization effect of ARG to LYS mutations, which do not alter
the balance of electrostatic interactions but affect chemical interactions
in subtle ways. The range of applications attests to the transferability
of COFFEE, and we anticipate that it would be a promising framework
for simulating DNA–protein complexes at the molecular length-scale.