HylleraasMD: A Domain Decomposition-Based Hybrid Particle-Field Software for Multi-Scale Simulations of Soft Matter

Abstract

We present HylleraasMD (HyMD), a comprehensive implementation of the recently proposed Hamiltonian formulation of hybrid particle-field molecular dynamics (hPF). The methodology is based on tunable, grid-independent length-scale of coarse graining, obtained by filtering particle densities in reciprocal space. This enables systematic convergence of energies and forces by grid refinement, also eliminating non-physical force aliasing. Separating the time integration of fast modes associated with internal molecular motion, from slow modes associated with their density fields, we implement the first time-reversible hPF simulations. HyMD comprises the optional use of explicit electrostatics, which, in this formalism, corresponds to the long-range potential in Particle-Mesh Ewald. We demonstrate the ability of HhPF to perform simulations in the microcanonical and canonical ensembles with a series of test cases, comprising lipid bilayers and vesicles, surfactant micelles, and polypeptide chains, comparing our results to established literature. An on-the-fly increase of the characteristic coarse graining length significantly speeds up dynamics, accelerating self-diffusion and leading to expedited aggregation. Exploiting this acceleration, we find that the time scales involved in the self-assembly of polymeric structures can lie in the tens to hundreds of picoseconds instead of the multi microsecond regime observed with comparable coarse-grained models.

Soft Matter under Pressure: Pushing Particle–Field Molecular Dynamics to the Isobaric Ensemble

“…We used an rRESPA multiple time step algorithm where the slowly evolving field forces are integrated at a lower frequency while the rapidly evolving bonded forces are integrated at a higher frequency. 39 In all HhPF-NPT runs reported in this paper, the two time steps used are Δ t 1 = 0.3 ps and Δ t 2 = 0.03 ps, respectively. More details can be found in ref ( 39 ).…”

“…The compressibility parameter was set to the isothermal compressibility of water (β = 4.6 × 10 –5 bar –1 ), and a coupling time constant τ P was chosen from a range of 0.1–1.0 ps such that the pressure coupling always remains stronger than the thermostat coupling. We used an rRESPA multiple time step algorithm where the slowly evolving field forces are integrated at a lower frequency while the rapidly evolving bonded forces are integrated at a higher frequency . In all HhPF-NPT runs reported in this paper, the two time steps used are Δ t 1 = 0.3 ps and Δ t 2 = 0.03 ps, respectively.…”

“…In all HhPF-NPT runs reported in this paper, the two time steps used are Δ t 1 = 0.3 ps and Δ t 2 = 0.03 ps, respectively. More details can be found in ref . Our HhPF approach was implemented into the HylleraasMD (HyMD) modeling package. − More on this and the implementation of the barostat can be found in SI: Pressure Implementation.…”

“…More details can be found in ref . Our HhPF approach was implemented into the HylleraasMD (HyMD) modeling package. − More on this and the implementation of the barostat can be found in SI: Pressure Implementation.…”

“…At this juncture, a natural next step is to use the constantpressure implementation on chemically similar moieties, like other lipids with unsaturated tails, to test the transferability of the ML interaction parameters, as well as on lipids with saturated and polyunsaturated tails with different polar heads like phosphocholine and phosphoethanolamine, 3 to build a library of HhPF parameters that can reproduce properties such as those shown in the case of pure DPPC in this work. Furthermore, by straightforwardly implementing electrostatic interactions using the Ewald summation, as has already been done in the previous release of HyMD, 39 from the NVT ensemble into the NPT ensemble, studies on charged systems like peripheral and integral proteins embedded into membrane bilayers 5 or membranes in ionic media can be conducted.…”