Exploring DNA dynamics within oligonucleosomes with coarse-grained simulations: SIRAH force field extension for protein-DNA complexes

Brandner, Astrid; Schüller, Andreas; Melo, Francisco S.; Pantano, Sergio

doi:10.1016/j.bbrc.2017.09.086

Cited by 30 publications

(24 citation statements)

References 47 publications

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“…Indeed, various coarse grained methods have been proposed, [16][17][18][19][20][21][22] e.g. for handling membrane proteins, 23 DNA, 24 water solutions, 25 lipid membranes, 21 and polymers. 26,27 The basic units of these CG models are typically spherical beads, which is quite reasonable for modelling alkyl chains, phosphates, and more generally biomolecules, like, e.g., in the popular MARTINI package.…”

Section: Introductionmentioning

confidence: 99%

MOLC. A reversible coarse grained approach using anisotropic beads for the modelling of organic functional materials

Ricci

Roscioni

Querciagrossa

et al. 2019

Phys. Chem. Chem. Phys.

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Section: Introductionmentioning

confidence: 99%

MOLC. A reversible coarse grained approach using anisotropic beads for the modelling of organic functional materials

Ricci

Roscioni

Querciagrossa

et al. 2019

Phys. Chem. Chem. Phys.

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“…Coarse-grained simulations of unrolling have been studied by Langowski and co-workers [70]. The SIRAH force field extension for protein-DNA complexes has been used to perform coarse-grained simulations of tetranucleosomes to study DNA dynamics within the context of this system [71]. Many coarse-grained models of DNA itself have been described previously [72].…”

Section: Nucleosomes Di-nucleosomes Tri-nucleosomes and Tetra-nuclmentioning

confidence: 99%

Large-scale simulations of nucleoprotein complexes: ribosomes, nucleosomes, chromatin, chromosomes and CRISPR

Sanbonmatsu

2019

Current Opinion in Structural Biology

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Recent advances in biotechnology, such as Hi-C, CRISPR/Cas9, and ribosome display, have place nucleoprotein complexes at center stage. Understanding the structural dynamics of these complexes aids in optimizing protocols and interpreting data for these new technologies. The integration of simulation and experiment has helped advance mechanistic understanding of these systems. Coarse-grained simulations, reduced-description models and explicit solvent molecular dynamics simulations yield useful complementary perspectives on nucleoprotein complex structural dynamics. When combined with Hi-C, cryo-EM, and single molecule measurements, these simulations integrate disparate forms of experimental data into a coherent mechanism. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…Recently, coarse-grained models are also being extended to study ribosome dynamics 25 and various protein-DNA transient complexes. [26][27][28] Motivated by these success stories of coarsegrained models, we speculated if coarse-grained models of proteins and small molecules can be put into play to substitute computationally expensive all-atom simulations for capturing protein-ligand recognition process on the fly. In this work, by building on popular MAR-TINI 6,29-31 coarse-grained frame-work, we report that while its vanilla implementation on protein-ligand system might fail to capture the binding event, judicious optimization of elastic network 32 in MARTINI protein model enable the simulation of the spontaneous binding process of ligand to the designated cavity at crystallographically identical pose.…”

Section: Introductionmentioning

confidence: 99%

Capturing Protein-Ligand Recognition Pathways in Coarse-grained Simulation

Dandekar

Mondal

2019

Preprint

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Protein-substrate recognition is highly dynamic and complex process in nature. A key approach in deciphering the mechanism underlying the recognition process is to capture the kinetic process of substrate in its act of binding to its designated protein cavity. Towards this end, microsecond long atomistic molecular dynamics (MD) simulation has recently emerged as a popular method of choice, due its ability to record these events at high spatial and temporal resolution. However, success in this approach comes at an exorbitant computational cost. Here we demonstrate that coarse grained models of protein, when systematically optimised to maintain its tertiary fold, can capture the complete process of spontaneous protein-ligand binding from bulk media to cavity, within orders of magnitude shorter wall clock time compared to that of all-atom MD simulations. The simulated and crystallographic binding pose are in excellent agreement. We find that the exhaustive sampling of ligand exploration in protein and solvent, harnessed by coarse-grained simulation at a frugal computational cost, in combination with Markov state modelling, leads to clearer mechanistic insights and discovery of novel recognition pathways. The result is successfully validated against three popular protein-ligand systems. Overall, the approach provides an affordable and 1 attractive alternative of all-atom simulation and promises a way-forward for replacing traditional docking based small molecule discovery by high-throughput coarse-grained simulation for searching potential binding site and allosteric sites. This also provides practical avenues for first-hand exploration of bio-molecular recognition processes in large-scale biological systems, otherwise inaccessible in all-atom simulations.

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Exploring DNA dynamics within oligonucleosomes with coarse-grained simulations: SIRAH force field extension for protein-DNA complexes

Cited by 30 publications

References 47 publications

MOLC. A reversible coarse grained approach using anisotropic beads for the modelling of organic functional materials

MOLC. A reversible coarse grained approach using anisotropic beads for the modelling of organic functional materials

Large-scale simulations of nucleoprotein complexes: ribosomes, nucleosomes, chromatin, chromosomes and CRISPR

Capturing Protein-Ligand Recognition Pathways in Coarse-grained Simulation

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