scholarly journals Supercoiling Enhances DNA Mobility by Reducing Threadings and Entanglements

2020 ◽  
Author(s):  
Jan Smrek ◽  
Davide Michieletto

DNA is increasingly employed for bio and nanotechnology thanks to its exquisite versatility and designability. Most of its use is limited to linearised and torsionally relaxed DNA but non-trivial architectures and torsionally constrained – or supercoiled – DNA plasmids are largely neglected; this is partly due to the limited understanding of how supercoiling affects the rheology of entangled DNA. To address this open question we perform large scale Molecular Dynamics (MD) simulations of entangled solutions of DNA plasmids modelled as twistable chains. We discover that, contrarily to what generally assumed in the literature, larger supercoiling increases the average size of plasmids in the entangled regime. At the same time, we discover that this is accompanied by an unexpected increase of diffusivity. We explain our findings as due to a decrease in inter-plasmids threadings and entanglements.

2014 ◽  
Vol 1700 ◽  
pp. 61-66
Author(s):  
Guttormur Arnar Ingvason ◽  
Virginie Rollin

ABSTRACTAdding single walled carbon nanotubes (SWCNT) to a polymer matrix can improve the delamination properties of the composite. Due to the complexity of polymer molecules and the curing process, few 3-D Molecular Dynamics (MD) simulations of a polymer-SWCNT composite have been run. Our model runs on the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), with a COMPASS (Condensed phase Optimized Molecular Potential for Atomistic Simulations Studies) potential. This potential includes non-bonded interactions, as well as bonds, angles and dihedrals to create a MD model for a SWCNT and EPON 862/DETDA (Diethyltoluenediamine) polymer matrix. Two simulations were performed in order to test the implementation of the COMPASS parameters. The first one was a tensile test on a SWCNT, leading to a Young’s modulus of 1.4 TPa at 300K. The second one was a pull-out test of a SWCNT from an originally uncured EPON 862/DETDA matrix.


Soft Matter ◽  
2018 ◽  
Vol 14 (15) ◽  
pp. 2796-2807 ◽  
Author(s):  
Andrea Catte ◽  
Mark R. Wilson ◽  
Martin Walker ◽  
Vasily S. Oganesyan

Antimicrobial action of a cationic peptide is modelled by large scale MD simulations.


Author(s):  
Juan J Galano-Frutos ◽  
Helena García-Cebollada ◽  
Javier Sancho

Abstract The increasing ease with which massive genetic information can be obtained from patients or healthy individuals has stimulated the development of interpretive bioinformatics tools as aids in clinical practice. Most such tools analyze evolutionary information and simple physical–chemical properties to predict whether replacement of one amino acid residue with another will be tolerated or cause disease. Those approaches achieve up to 80–85% accuracy as binary classifiers (neutral/pathogenic). As such accuracy is insufficient for medical decision to be based on, and it does not appear to be increasing, more precise methods, such as full-atom molecular dynamics (MD) simulations in explicit solvent, are also discussed. Then, to describe the goal of interpreting human genetic variations at large scale through MD simulations, we restrictively refer to all possible protein variants carrying single-amino-acid substitutions arising from single-nucleotide variations as the human variome. We calculate its size and develop a simple model that allows calculating the simulation time needed to have a 0.99 probability of observing unfolding events of any unstable variant. The knowledge of that time enables performing a binary classification of the variants (stable-potentially neutral/unstable-pathogenic). Our model indicates that the human variome cannot be simulated with present computing capabilities. However, if they continue to increase as per Moore’s law, it could be simulated (at 65°C) spending only 3 years in the task if we started in 2031. The simulation of individual protein variomes is achievable in short times starting at present. International coordination seems appropriate to embark upon massive MD simulations of protein variants.


MRS Advances ◽  
2017 ◽  
Vol 2 (29) ◽  
pp. 1571-1576
Author(s):  
Vinicius Splugues ◽  
Pedro Alves da Silva Autreto ◽  
Douglas S. Galvao

ABSTRACTThe advent of graphene created a revolution in materials science. Because of this there is a renewed interest in other carbon-based structures. Graphene is the ultimate (just one atom thick) membrane. It has been proposed that graphene can work as impermeable membrane to standard gases, such argon and helium. Graphene-like porous membranes, but presenting larger porosity and potential selectivity would have many technological applications. Biphenylene carbon (BPC), sometimes called graphenylene, is one of these structures. BPC is a porous two-dimensional (planar) allotrope carbon, with its pores resembling typical sieve cavities and/or some kind of zeolites. In this work, we have investigated the hydrogenation dynamics of BPC membranes under different conditions (hydrogenation plasma density, temperature, etc.). We have carried out an extensive study through fully atomistic molecular dynamics (MD) simulations using the reactive force field ReaxFF, as implemented in the well-known Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code. Our results show that the BPC hydrogenation processes exhibit very complex patterns and the formation of correlated domains (hydrogenated islands) observed in the case of graphene hydrogenation was also observed here. MD results also show that under hydrogenation BPC structure undergoes a change in its topology, the pores undergoing structural transformations and extensive hydrogenation can produce significant structural damages, with the formation of large defective areas and large structural holes, leading to structural collapse.


RSC Advances ◽  
2020 ◽  
Vol 10 (16) ◽  
pp. 9187-9192 ◽  
Author(s):  
Hui Feng ◽  
Jingwen Tang ◽  
Haotian Chen ◽  
Yuanyuan Tian ◽  
Qihong Fang ◽  
...  

Using large-scale molecular dynamics (MD) simulations, the effects of interface and layer number in the nanoindentation response of experimentally observed nanotwinned Cu/high entropy alloy (HEA) FeCoCrNi nanolaminate are studied.


2020 ◽  
Author(s):  
Jordi Juárez-Jiménez ◽  
Philip Tew ◽  
Michael o'connor ◽  
Salome Llabres ◽  
Rebecca Sage ◽  
...  

<p>Molecular dynamics (MD) simulations are increasingly used to elucidate relationships between protein structure, dynamics and their biological function. Currently it is extremely challenging to perform MD simulations of large-scale structural rearrangements in proteins that occur on millisecond timescales or beyond, as this requires very significant computational resources, or the use of cumbersome ‘collective variable’ enhanced sampling protocols. Here we describe a framework that combines ensemble MD simulations and virtual-reality visualization (eMD-VR) to enable users to interactively generate realistic descriptions of large amplitude, millisecond timescale protein conformational changes in proteins. Detailed tests demonstrate that eMD-VR substantially decreases the computational cost of folding simulations of a WW domain, without the need to define collective variables <i>a priori</i>. We further show that eMD-VR generated pathways can be combined with Markov State Models to describe the thermodynamics and kinetics of large-scale loop motions in the enzyme cyclophilin A. Our results suggest eMD-VR is a powerful tool for exploring protein energy landscapes in bioengineering efforts. </p>


2019 ◽  
Author(s):  
Junghoon Chae ◽  
Debsindhu Bhowmik ◽  
Heng Ma ◽  
Arvind Ramanathan ◽  
Chad Steed

AbstractMolecular Dynamics (MD) simulation have been emerging as an excellent candidate for understanding complex atomic and molecular scale mechanism of bio-molecules that control essential bio-physical phenomenon in a living organism. But this MD technique produces large-size and long-timescale data that are inherently high-dimensional and occupies many terabytes of data. Processing this immense amount of data in a meaningful way is becoming increasingly difficult. Therefore, specific dimensionality reduction algorithm using deep learning technique has been employed here to embed the high-dimensional data in a lower-dimension latent space that still preserves the inherent molecular characteristics i.e. retains biologically meaningful information. Subsequently, the results of the embedding models are visualized for model evaluation and analysis of the extracted underlying features. However, most of the existing visualizations for embeddings have limitations in evaluating the embedding models and understanding the complex simulation data. We propose an interactive visual analytics system for embeddings of MD simulations to not only evaluate and explain an embedding model but also analyze various characteristics of the simulations. Our system enables exploration and discovery of meaningful and semantic embedding results and supports the understanding and evaluation of results by the quantitatively described features of the MD simulations (even without specific labels).


2020 ◽  
Author(s):  
Jordi Juárez-Jiménez ◽  
Philip Tew ◽  
Michael o'connor ◽  
Salome Llabres ◽  
Rebecca Sage ◽  
...  

<p>Molecular dynamics (MD) simulations are increasingly used to elucidate relationships between protein structure, dynamics and their biological function. Currently it is extremely challenging to perform MD simulations of large-scale structural rearrangements in proteins that occur on millisecond timescales or beyond, as this requires very significant computational resources, or the use of cumbersome ‘collective variable’ enhanced sampling protocols. Here we describe a framework that combines ensemble MD simulations and virtual-reality visualization (eMD-VR) to enable users to interactively generate realistic descriptions of large amplitude, millisecond timescale protein conformational changes in proteins. Detailed tests demonstrate that eMD-VR substantially decreases the computational cost of folding simulations of a WW domain, without the need to define collective variables <i>a priori</i>. We further show that eMD-VR generated pathways can be combined with Markov State Models to describe the thermodynamics and kinetics of large-scale loop motions in the enzyme cyclophilin A. Our results suggest eMD-VR is a powerful tool for exploring protein energy landscapes in bioengineering efforts. </p>


Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2917-2917
Author(s):  
Tai-Sung Lee ◽  
Steven Potts ◽  
Hagop Kantarjian ◽  
Jorge Cortes ◽  
Francis Giles ◽  
...  

Abstract Molecular dynamics (MD) simulations on the complex of imatinib with the wild-type, T315I, and other 10 P-loop mutants of the tyrosine kinase Bcr-Abl have been performed to study the imatinib resistance mechanism at the atomic level. MD simulations show that large scale computational simulations could offer insight information that a static structure or simple homology modeling methods cannot provide for studying the Bcr-Abl imatinib resistance problem, especially in the case of conformational changes due to remote mutations. By utilizing the Molecular Mechanics/Poisson-Boltzmann surface area (MM-PBSA) techniques and analyzing the interactions between imatinib and individual residues, imatinib resistance mechanisms not previously thought have been revealed. Non-directly contacted P-loop mutations either unfavorably change the direct electrostatic interactions with imatinib, or cause the conformational changes influencing the contact energies between imatinib and other non-P-loop residues. We demonstrate that imatinib resistance of T315I mainly comes from the breakdown of the interactions between imatinib and E286 and M290, contradictory to previously suggested that the missing hydrogen bonding is the main contribution. We also demonstrate that except for the mutations of the direct contact residues, such as L248 and Y253, the unfavorable electrostatic interaction between P-loop and imatinib is the main reason for resistance for the P-loop mutations. Furthermore, in Y255H, protonation of the histidin is essential for rendering this mutation resistant to Gleevec. Our results demonstrate that MD is a powerful way to verify and predict clinical response or resistance to imatinib and other potential drugs.


Author(s):  
Yuan Dong ◽  
Jian Lin

The graphene-based nanomaterial has great potential as catalyst and supercapacitors. In this paper we study the pyrolysis of polymers in a nanosecond time scale with the reactive molecular dynamics (MD) simulations using ReaxFF potential. It is found that the confined heating will produce graphene-like nanostructures out of two kinds of polymers: polyimide and polyether ether ketone. The peak pressure achieves above 3GPa with a processing temperature of 3000K. It indicates that the local high temperature and pressure can convert polymer to graphene-based nanomaterials without metal catalyst, which may enable large scale production of high performance electrical devices and microreactors with laser scribing method.


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