Conformational Ensembles from Experimental Data and Computer Simulations

Conformational Ensembles from Experimental Data and Computer Simulations

Poster Abstracts

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)

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