151 research outputs found
A simple asynchronous replica-exchange implementation
We discuss the possibility of implementing asynchronous replica-exchange (or
parallel tempering) molecular dynamics. In our scheme, the exchange attempts
are driven by asynchronous messages sent by one of the computing nodes, so that
different replicas are allowed to perform a different number of time-steps
between subsequent attempts. The implementation is simple and based on the
message-passing interface (MPI). We illustrate the advantages of our scheme
with respect to the standard synchronous algorithm and we benchmark it for a
model Lennard-Jones liquid on an IBM-LS21 blade center cluster.Comment: Preprint of Proceeding for CSFI 200
Reactive Force Field for Proton Diffusion in BaZrO3 using an empirical valence bond approach
A new reactive force field to describe proton diffusion within the
solid-oxide fuel cell material BaZrO3 has been derived. Using a quantum
mechanical potential energy surface, the parameters of an interatomic potential
model to describe hydroxyl groups within both pure and yttrium-doped BaZrO3
have been determined. Reactivity is then incorporated through the use of the
empirical valence bond model. Molecular dynamics simulations (EVB-MD) have been
performed to explore the diffusion of hydrogen using a stochastic thermostat
and barostat whose equations are extended to the isostress-isothermal ensemble.
In the low concentration limit, the presence of yttrium is found not to
significantly influence the diffusivity of hydrogen, despite the proton having
a longer residence time at oxygen adjacent to the dopant. This lack of
influence is due to the fact that trapping occurs infrequently, even when the
proton diffuses through octahedra adjacent to the dopant. The activation energy
for diffusion is found to be 0.42 eV, in good agreement with experimental
values, though the prefactor is slightly underestimated.Comment: Corrected titl
Hamiltonian replica-exchange in GROMACS: a flexible implementation
A simple and general implementation of Hamiltonian replica exchange for the popular molecular-dynamics software GROMACS is presented. In this implementation, arbitrarily different Hamiltonians can be used for the different replicas without incurring in any significant performance penalty. The implementation was validated on a simple toy model - alanine dipeptide in water - and applied to study the rearrangement of an RNA tetraloop, where it was used to compare recently proposed force-field corrections
Unravelling Mg2+-RNA binding with atomistic molecular dynamics
Interaction with divalent cations is of paramount importance for RNA structural stability and function. We report here a detailed molecular dynamics study of all the possible binding sites for Mg2+ on an RNA duplex, including both direct (inner sphere) and indirect (outer sphere) binding. In order to tackle sampling issues, we develop a modified version of bias-exchange metadynamics, which allows us to simultaneously compute affinities with previously unreported statistical accuracy. Results correctly reproduce trends observed in crystallographic databases. Based on this, we simulate a carefully chosen set of models that allows us to quantify the effects of competition with monovalent cations, RNA flexibility, and RNA hybridization. Our simulations reproduce the decrease and increase of Mg2+ affinity due to ion competition and hybridization, respectively, and predict that RNA flexibility has a site-dependent effect. This suggests a nontrivial interplay between RNA conformational entropy and divalent cation binding
Refinement of molecular dynamics ensembles using experimental data and flexible forward models
A novel method combining maximum entropy principle, the Bayesian-inference of
ensembles approach, and the optimization of empirical forward models is
presented. Here we focus on the Karplus parameters for RNA systems, which
relate the dihedral angles of , , and the dihedrals in the sugar
ring to the corresponding -coupling signal between coupling protons.
Extensive molecular simulations are performed on a set of RNA tetramers and
hexamers and combined with available nucleic-magnetic-resonance data. Within
the new framework, the sampled structural dynamics can be reweighted to match
experimental data while the error arising from inaccuracies in the forward
models can be corrected simultaneously and consequently does not leak into the
reweighted ensemble. Carefully crafted cross-validation procedure and
regularization terms enable obtaining transferable Karplus parameters. Our
approach identifies the optimal regularization strength and new sets of Karplus
parameters balancing good agreement between simulations and experiments with
minimal changes to the original ensemble.Comment: Submitted to journal; added zenodo link; replaced fig. 3 with correct
on
Using the maximum entropy principle to combine simulations and solution experiments
Molecular dynamics (MD) simulations allow the investigation of the structural dynamics of biomolecular systems with unrivaled time and space resolution. However, in order to compensate for the inaccuracies of the utilized empirical force fields, it is becoming common to integrate MD simulations with experimental data obtained from ensemble measurements. We review here the approaches that can be used to combine MD and experiment under the guidance of the maximum entropy principle. We mostly focus on methods based on Lagrangian multipliers, either implemented as reweighting of existing simulations or through an on-the-fly optimization. We discuss how errors in the experimental data can be modeled and accounted for. Finally, we use simple model systems to illustrate the typical difficulties arising when applying these methods
Langevin equation with colored noise for constant-temperature molecular dynamics simulations
We discuss the use of a Langevin equation with a colored (correlated) noise
to perform constant-temperature molecular dynamics simulations. Since the
equations of motion are linear in nature, it is easy to predict the response of
a Hamiltonian system to such a thermostat and to tune at will the relaxation
time of modes of different frequency. This allows one to optimize the time
needed to thermalize the system and generate independent configurations. We
show how this frequency-dependent response can be exploited to control the
temperature of Car-Parrinello-like dynamics, keeping at low temperature the
electronic degrees of freedom, without affecting the adiabatic separation from
the vibrations of the ions
Molecular dynamics simulations of chemically modified ribonucleotides
Post-transcriptional modifications are crucial for RNA function, with roles
ranging from the stabilization of functional RNA structures to modulation of
RNA--protein interactions. Additionally, artificially modified RNAs have been
suggested as optimal oligonucleotides for therapeutic purposes. The impact of
chemical modifications on secondary structure has been rationalized for some of
the most common modifications. However, the characterization of how the
modifications affect the three-dimensional RNA structure and dynamics and its
capability to bind proteins is still highly challenging. Molecular dynamics
simulations, coupled with enhanced sampling methods and integration of
experimental data, provide a direct access to RNA structural dynamics. In the
context of RNA chemical modifications, alchemical simulations where a wild type
nucleotide is converted to a modified one are particularly common. In this
Chapter, we review recent molecular dynamics studies of modified
ribonucleotides. We discuss the technical aspects of the reviewed works,
including the employed force fields, enhanced sampling methods, and alchemical
methods, in a way that is accessible to experimentalists. Finally, we provide
our perspective on this quickly growing field of research. The goal of this
Chapter is to provide a guide for experimentalists to understand molecular
dynamics works and, at the same time, give to molecular dynamics experts a
solid review of published articles that will be a useful starting point for new
research.Comment: Submitted as a chapter for the book "RNA Structure and Function",
series "RNA Technologies", published by Springe
Optimal Langevin modelling of out-of-equilibrium molecular dynamics simulations
We introduce a scheme for deriving an optimally-parametrised Langevin
dynamics of few collective variables from data generated in molecular dynamics
simulations. The drift and the position-dependent diffusion profiles governing
the Langevin dynamics are expressed as explicit averages over the input
trajectories. The proposed strategy is applicable to cases when the input
trajectories are generated by subjecting the system to a external
time-dependent force (as opposed to canonically-equilibrated trajectories).
Secondly, it provides an explicit control on the statistical uncertainty of the
drift and diffusion profiles. These features lend to the possibility of
designing the external force driving the system so to maximize the accuracy of
the drift and diffusions profile throughout the phase space of interest.
Quantitative criteria are also provided to assess a posteriori the
satisfiability of the requisites for applying the method, namely the Markovian
character of the stochastic dynamics of the collective variables.Comment: To be published on Journal of Chemical Physic
Metadynamics with adaptive Gaussians
Metadynamics is an established sampling method aimed at reconstructing the
free-energy surface relative to a set of appropriately chosen collective
variables. In standard metadynamics the free-energy surface is filled by the
addition of Gaussian potentials of pre-assigned and typically diagonal
covariance. Asymptotically the free-energy surface is proportional to the bias
deposited. Here we consider the possibility of using Gaussians whose variance
is adjusted on the fly to the local properties of the free-energy surface. We
suggest two different prescriptions: one is based on the local diffusivity and
the other on the local geometrical properties. We further examine the problem
of extracting the free-energy surface when using adaptive Gaussians. We show
that the standard relation between the bias and the free energy does not hold.
In the limit of narrow Gaussians an explicit correction can be evaluated. In
the general case we propose to use instead a relation between bias and free
energy borrowed from umbrella sampling. This relation holds for all kinds of
incrementally deposited bias. We illustrate on the case of alanine dipeptide
the advantage of using adaptive Gaussians in conjunction with the new
free-energy estimator both in terms of accuracy and speed of convergence.Comment: Reprinted (adapted) with permission from J. Chem. Theory Comput.,
DOI: 10.1021/ct3002464. Copyright (2012) American Chemical Societ
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