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Conformational Ensembles from Experimental Data
and Computer Simulations
Poster Abstracts
62
29-POS
Board 29
Minimalist Coarse-grained Models for Double-stranded DNA Fragments: A Comparative
Survey
Mathieu Fossépré
.Mathieu Surin.
UMONS, Mons, Belgium.
Computational molecular modelling approaches such as Molecular Dynamics (MD) play an
increasingly important role for studying structure, dynamics, and function of biomolecular
systems and to complement experimental results [1]. Despite the constant development of
computer performances, the size of biomolecular systems and the phenomenological timescales
required to consider most biological phenomena are still out of reach. By merging a set of atoms
into one bead, coarse-grained (CG) models permit much faster simulations of large and complex
biomolecular systems on the microsecond timescale. Consequently, there was a renewed interest
in the use of coarse-grained (CG) models for biopolymers in the last decade, leading to a large
variety of CG DNA models with various spatial resolutions, mapping schemes, and interaction
potentials [2,3]. In this study, we compared a selection of generic CG models for DNA, as a
prerequisite to simulate DNA/polymer complexation. We focused our analysis on minimalist
DNA models, i.e., a class of CG models using a single or a few beads for each nucleotide. CG
models were applied on DNA sequences of various lengths, ranging from 17 to 100 base pairs,
on the microsecond timescale by using MD simulations techniques. The performance of CG
models is evaluated in terms of the dynamical and mechanical properties of DNA fragments and
on the range of applicability of these properties. Ultimately, this comparison between CG models
will be helpful to further develop models in order to understand the complexation and
aggregation mechanisms of DNA with conjugated polyelectrolytes [4].
[1] J.R. Perilla et al., Curr. Opin. Struct. Biol. 31 64 (2015)
[2] M.G. Saunders et al., Annu. Rev. Biophys. 42 73 (2013)
[3] P.D. Dans et al., Curr. Opin. Struct. Biol. 37 29 (2016)
[4] J. Rubio-Magnieto et al., Soft Matter 11 6460 (2015)