Machine learning-driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins.

RAS is a signaling protein associated with the cell membrane that is mutated in up to 30% of human cancers. RAS signaling has been proposed to be regulated by dynamic heterogeneity of the cell membrane. Investigating such a mechanism requires near-atomistic detail at macroscopic temporal and spatial scales, which is not possible with conventional computational or experimental techniques. We demonstrate here a multiscale simulation infrastructure that uses machine learning to create a scale-bridging ensemble of over 100,000 simulations of active wild-type KRAS on a complex, asymmetric membrane. Initialized and validated with experimental data (including a new structure of active wild-type KRAS), these simulations represent a substantial advance in the ability to characterize RAS-membrane biology. We report distinctive patterns of local lipid composition that correlate with interfacially promiscuous RAS multimerization. These lipid fingerprints are coupled to RAS dynamics, predicted to influence effector binding, and therefore may be a mechanism for regulating cell signaling cascades.

Molecular dynamics studies of electron-ion temperature equilibration in hydrogen plasmas within the coupled-mode regime.

We use classical molecular dynamics (MD) to study electron-ion temperature equilibration in two-component plasmas in regimes for which the presence of coupled collective modes has been predicted to substantively reduce the equilibration rate. Guided by previous kinetic theory work, we examine hydrogen plasmas at a density of n=10^{26}cm^{-3}, T_{i}=10^{5}K, and 10^{7}K

Magnetostructural Transition Kinetics in Shocked Iron.

A generalized Heisenberg model is implemented to study the effect of thermal magnetic disorder on kinetics of the Fe α-ε transition. The barrier to bulk martensitic displacement remains large in α-Fe shocked well past the phase line but is much reduced in the [001] α-ε boundary. The first result is consistent with observed overdriving to metastable α, while the second suggests structural instability, as implied by observation of a [001] shock transformation front without plastic relaxation. Reconciling both behaviors may require concurrent treatment of magnetic and structural order.

Density functional theory calculations of magnetocrystalline anisotropy energies for (Fe(1-x)Co(x))(2)B.

We present and discuss density functional theory calculations of magnetic properties of the family of ferromagnetic compounds, (Fe(1-x)Co(x))(2)B, focusing specifically on the magnetocrystalline anisotropy energy (MAE). Using periodic supercells of various sizes (up to 96 atoms), it is shown that the general qualitative features of the composition dependence of the MAE is in agreement with experimental findings, while our predicted magnitudes are larger than those of experiment. We find that the use of small supercells (6 and 12-atom) favors larger MAE values relative to a statistical sample of configurations constructed with 96-atom supercells. The effect of lattice relaxations is shown to be small. Calculations of the Curie temperature for this alloy are also presented.

Molecular dynamics simulations of classical stopping power.

Molecular dynamics can provide very accurate tests of classical kinetic theory; for example, unambiguous comparisons can be made for classical particles interacting via a repulsive 1/r potential. The plasma stopping power problem, of great interest in its own right, provides an especially stringent test of a velocity-dependent transport property. We have performed large-scale (~10(4)-10(6) particles) molecular dynamics simulations of charged-particle stopping in a classical electron gas that span the weak to moderately strong intratarget coupling regimes. Projectile-target coupling is varied with projectile charge and velocity. Comparisons are made with disparate kinetic theories (both Boltzmann and Lenard-Balescu classes) and fully convergent theories to establish regimes of validity. We extend these various stopping models to improve agreement with the MD data and provide a useful fit to our results.

Molecular dynamics simulations and generalized Lenard-Balescu calculations of electron-ion temperature equilibration in plasmas.

We study the problem of electron-ion temperature equilibration in plasmas. We consider pure H at various densities and temperatures and Ar-doped H at temperatures high enough so that the Ar is fully ionized. Two theoretical approaches are used: classical molecular dynamics (MD) with statistical two-body potentials and a generalized Lenard-Balescu (GLB) theory capable of treating multicomponent weakly coupled plasmas. The GLB is used in two modes: (1) with the quantum dielectric response in the random-phase approximation (RPA) together with the pure Coulomb interaction and (2) with the classical (ℏ→0) dielectric response (both with and without local-field corrections) together with the statistical potentials. We find that the MD results are described very well by classical GLB including the statistical potentials and without local-field corrections (RPA only); worse agreement is found when static local-field effects are included, in contradiction to the classical pure-Coulomb case with like charges. The results of the various approaches are all in excellent agreement with pure-Coulomb quantum GLB when the temperature is high enough. In addition, we show that classical calculations with statistical potentials derived from the exact quantum two-body density matrix produce results in far better agreement with pure-Coulomb quantum GLB than classical calculations performed with older existing statistical potentials.