Efficient Treatment of Fixed and Induced Dipolar Interactions

2000 ◽  
Vol 653 ◽  
Author(s):  
Celeste Sagui ◽  
Thoma Darden
Keyword(s):  
Molecular Dynamics ◽  
Md Simulations ◽  
Lagrangian Formalism ◽  
Dipolar Interactions ◽  
Time Step ◽  
Efficient Treatment ◽  
Particle Mesh Ewald ◽  
Fixed Charges ◽  
Self Consistency ◽  
Induced Dipoles

AbstractFixed and induced point dipoles have been implemented in the Ewald and Particle-Mesh Ewald (PME) formalisms. During molecular dynamics (MD) the induced dipoles can be propagated along with the atomic positions either by interation to self-consistency at each time step, or by a Car-Parrinello (CP) technique using an extended Lagrangian formalism. The use of PME for electrostatics of fixed charges and induced dipoles together with a CP treatment of dipole propagation in MD simulations leads to a cost overhead of only 33% above that of MD simulations using standard PME with fixed charges, allowing the study of polarizability in largemacromolecular systems.

scholarly journals Testing for Physical Validity in Molecular Simulations

2018 ◽  
Author(s):  
Pascal T. Merz ◽  
Michael R. Shirts
Keyword(s):  
Molecular Dynamics ◽  
Open Source ◽  
Lipid Bilayers ◽  
Software Package ◽  
Degrees Of Freedom ◽  
Molecular Simulations ◽  
Polymeric Materials ◽  
Md Simulations ◽  
Time Step ◽  
Software Packages

<p>Advances in recent years have made molecular dynamics (MD) and Monte Carlo (MC) simulations powerful tools in molecular-level research, allowing the prediction of experimental observables in the study of systems such as proteins, membranes, and polymeric materials. However, the quality of any prediction based on molecular dynamics results will strongly depend on the validity of underlying physical assumptions.</p> <p>Unphysical behavior of simulations can have significant influence on the results and reproducibility of these simulations, such as folding of proteins and DNA or properties of lipid bilayers determined by cutoff treatment, dynamics of peptides and polymers affected by the choice of thermostat, or liquid properties depending on the simulation time step. Motivated by such examples, we propose a two-fold approach to increase the robustness of molecular simulations. The first part of this approach involves tests which can be performed by the users of MD programs on their respective systems and setups. We present a number of tests of different complexity, ranging from simple post-processing analysis to more involved tests requiring additional simulations. These tests are shown to significantly increase the reliability of MD simulations by catching a number of common simulation errors violating physical assumptions, such as non-conservative integrators, deviations from the Boltzmann ensemble, and lack of ergodicity between degrees of freedom. To make the usage as easy as possible, we have developed an open-source and platform-independent Python library (https://physical-validation.readthedocs.io) implementing these tests.</p> <p>The second part of the approach involves testing for code correctness. While unphysical behavior can be due to poor or incompatible choices of parameters by the user, it can just as well originate in coding errors within the program. We therefore propose to include physical validation tests in the code-checking mechanism of MD software packages. We have implemented such a validation for the GROMACS software package, ensuring that every major releases passes a number of physical sanity checks performed on selected representative systems before shipping. It is, to our knowledge, the first major molecular mechanics software package to run such validation routinely. The tests are, as the rest of the package, open source software, and can be adapted for other software packages.</p>

scholarly journals Testing for Physical Validity in Molecular Simulations

2018 ◽  
Author(s):  
Pascal T. Merz ◽  
Michael R. Shirts
Keyword(s):  
Molecular Dynamics ◽  
Open Source ◽  
Lipid Bilayers ◽  
Software Package ◽  
Degrees Of Freedom ◽  
Molecular Simulations ◽  
Polymeric Materials ◽  
Md Simulations ◽  
Time Step ◽  
Software Packages

<p>Advances in recent years have made molecular dynamics (MD) and Monte Carlo (MC) simulations powerful tools in molecular-level research, allowing the prediction of experimental observables in the study of systems such as proteins, membranes, and polymeric materials. However, the quality of any prediction based on molecular dynamics results will strongly depend on the validity of underlying physical assumptions.</p> <p>Unphysical behavior of simulations can have significant influence on the results and reproducibility of these simulations, such as folding of proteins and DNA or properties of lipid bilayers determined by cutoff treatment, dynamics of peptides and polymers affected by the choice of thermostat, or liquid properties depending on the simulation time step. Motivated by such examples, we propose a two-fold approach to increase the robustness of molecular simulations. The first part of this approach involves tests which can be performed by the users of MD programs on their respective systems and setups. We present a number of tests of different complexity, ranging from simple post-processing analysis to more involved tests requiring additional simulations. These tests are shown to significantly increase the reliability of MD simulations by catching a number of common simulation errors violating physical assumptions, such as non-conservative integrators, deviations from the Boltzmann ensemble, and lack of ergodicity between degrees of freedom. To make the usage as easy as possible, we have developed an open-source and platform-independent Python library (https://physical-validation.readthedocs.io) implementing these tests.</p> <p>The second part of the approach involves testing for code correctness. While unphysical behavior can be due to poor or incompatible choices of parameters by the user, it can just as well originate in coding errors within the program. We therefore propose to include physical validation tests in the code-checking mechanism of MD software packages. We have implemented such a validation for the GROMACS software package, ensuring that every major releases passes a number of physical sanity checks performed on selected representative systems before shipping. It is, to our knowledge, the first major molecular mechanics software package to run such validation routinely. The tests are, as the rest of the package, open source software, and can be adapted for other software packages.</p>

scholarly journals Density artefacts at interfaces caused by multiple time-step effects in molecular dynamics simulations

F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 1745 ◽  
Author(s):  
Dominik Sidler ◽  
Marc Lehner ◽  
Simon Frasch ◽  
Michael Cristófol-Clough ◽  
Sereina Riniker
Keyword(s):  
Molecular Dynamics ◽  
Weak Coupling ◽  
Stochastic Dynamics ◽  
Md Simulations ◽  
Multiple Time ◽  
Time Step ◽  
Nonbonded Interactions ◽  
Multiple Time Step ◽  
Wide Range ◽  
Dynamics Simulations

Background: Molecular dynamics (MD) simulations have become an important tool to provide insight into molecular processes involving biomolecules such as proteins, DNA, carbohydrates and membranes. As these processes cover a wide range of time scales, multiple time-step integration methods are often employed to increase the speed of MD simulations. For example, in the twin-range (TR) scheme, the nonbonded forces within the long-range cutoff are split into a short-range contribution updated every time step (inner time step) and a less frequently updated mid-range contribution (outer time step). The presence of different time steps can, however, cause numerical artefacts. Methods: The effects of multiple time-step algorithms at interfaces between polar and apolar media are investigated with MD simulations. Such interfaces occur with biological membranes or proteins in solution. Results: In this work, it is shown that the TR splitting of the nonbonded forces leads to artificial density increases at interfaces for weak coupling and Nosé-Hoover (chain) thermostats. It is further shown that integration with an impulse-wise reversible reference system propagation algorithm (RESPA) only shifts the occurrence of density artefacts towards larger outer time steps. Using a single-range (SR) treatment of the nonbonded interactions or a stochastic dynamics thermostat, on the other hand, resolves the density issue for pairlist-update periods of up to 40 fs. Conclusion: TR schemes are not advisable to use in combination with weak coupling or Nosé-Hoover (chain) thermostats due to the occurrence of significant numerical artifacts at interfaces.

Advances in biomolecular simulations: methodology and recent applications

2003 ◽  
Vol 36 (3) ◽  
pp. 257-306 ◽  
Author(s):  
Jan Norberg ◽  
Lennart Nilsson
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Force Fields ◽  
Md Simulations ◽  
Conformational Space ◽  
Multiple Time ◽  
Time Step ◽  
Field Methods ◽  
Reaction Field ◽  
Dynamics Simulations

1. Introduction 2582. Set-up of MD simulations 2602.1 Constant-pressure dynamics 2602.2 Grand-canonical dynamics 2612.3 Boundary conditions 2613. Force fields 2623.1 Proteins 2623.2 Nucleic acids 2653.3 Carbohydrates 2663.4 Phospholipids 2663.5 Polarization 2674. Electrostatics 2674.1 Spherical truncation methods 2684.2 Ewald summation methods 2694.3 Fast multipole (FM) methods 2714.4 Reaction-field methods 2715. Implicit solvation models 2716. Speeding-up the simulation 2736.1 SHAKE and its relatives 2736.2 Multiple time-step algorithms 2746.3 Other algorithms 2757. Conformational space sampling 2757.1 Multiple copy simultaneous search (MCSS) and locally enhanced sampling (LES) 2757.2 Steered or targeted MD 2767.3 Self-guided MD 2767.4 Leaving the standard 3D Cartesian coordinate system: 4D MD and internal coordinate MD 2777.5 Temperature variations 2778. Thermodynamic calculations 2788.1 Lambda (λ) dynamics 2788.2 Extracting thermodynamic information from simulations 2798.3 Non-Boltzmann thermodynamic integration (NBTI) 2798.4 Other methods 2799. QM/MM calculations 28210. MD simulations of protein folding and unfolding 28310.1 High-temperature effects 28410.2 Co-solvent and polarization effects 28810.3 External force effects 28811. On the horizon 29112. Acknowledgements 29213. References 292Molecular dynamics simulations are widely used today to tackle problems in biochemistry and molecular biology. In the 25 years since the first simulation of a protein computers have become faster by many orders of magnitude, algorithms and force fields have been improved, and simulations can now be applied to very large systems, such as protein–nucleic acid complexes and multimeric proteins in aqueous solution. In this review we give a general background about molecular dynamics simulations, and then focus on some recent technical advances, with applications to biologically relevant problems.

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