Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Many biologically interesting phenomena occur on a time scale that is too long to be studied by atomistic simulations. These phenomena include the dynamics of large proteins and self-assembly of biological materials. Coarse-grained (CG) molecular modeling allows computer simulations to be run on length and time scales that are 2–3 orders of magnitude larger compared to atomistic simulations, providing a bridge between the atomistic and the mesoscopic scale. We developed a new CG model for proteins as an extension of the MARTINI force field. Here, we validate the model for its use in peptide-bilayer systems. In order to validate the model, we calculated the potential of mean force for each amino acid as a function of its distance from the center of a dioleoylphosphatidylcholine (DOPC) lipid bilayer. We then compared amino acid association constants, the partitioning of a series of model pentapeptides, the partitioning and orientation of WALP23 in DOPC lipid bilayers and a series of KALP peptides in dimyris...

The MARTINI Coarse-Grained Force Field: Extension to Proteins

On the Controllable Soft-Templating Approach to Mesoporous Silicates

This paper describes the parametrization of a new coarse grained (CG) model for lipid and surfactant systems. Reduction of the number of degrees of freedom together with the use of short range potentials makes it computationally very efficient. Compared to atomistic models a gain of 3-4 orders of magnitude can be achieved. Micrometer length scales or millisecond time scales are therefore within reach. To encourage applications, the model is kept very simple. Only a small number of coarse grained atom types are defined, which interact using a few discrete levels of interaction. Despite the computational speed and the simplistic nature of the model, it proves to be both versatile in its applications and accurate in its predictions. We show that densities of liquid alkanes from decane up to eicosane can be reproduced to within 5%, and the mutual solubilities of alkanes in water and water in alkanes can be reproduced within 0.5 kT of the experimental values. The CG model for dipalmitoylphosphatidylcholine (DPPC) is shown to aggregate spontaneously into a bilayer. Structural properties such as the area per headgroup and the phosphate-phosphate distance match the experimentally measured quantities closely. The same is true for elastic properties such as the bending modulus and the area compressibility, and dynamic properties such as the lipid lateral diffusion coefficient and the water permeation rate. The distribution of the individual lipid components along the bilayer normal is very similar to distributions obtained from atomistic simulations. Phospholipids with different headgroup (ethanolamine) or different tail lengths (lauroyl, stearoyl) or unsaturated tails (oleoyl) can also be modeled with the CG force field. The experimental area per headgroup can be reproduced for most lipids within 0.02 nm(2). Finally, the CG model is applied to nonbilayer phases. Dodecylphosphocholine (DPC) aggregates into small micelles that are structurally very similar to ones modeled atomistically, and DOPE forms an inverted hexagonal phase with structural parameters in agreement with experimental data.

/pdf/coarse-grained-model-for-semiquantitative-lipid-simulations-3235leilrn.pdf

Coarse grained model for semiquantitative lipid simulations

We develop a unified and generally applicable theory of solvation of small and large apolar species in water. In the former, hydrogen bonding of water is hindered yet persists near the solutes. In the latter, hydrogen bonding is depleted, leading to drying of extended apolar surfaces, large forces of attraction, and hysteresis on mesoscopic length scales. The crossover occurs on nanometer length scales, when the local concentration of apolar units is sufficiently high, or when an apolar surface is sufficiently large. Our theory for the crossover has implications concerning the stability of protein assemblies and protein folding.

/pdf/hydrophobicity-at-small-and-large-length-scales-2xbfc1gyl4.pdf

Hydrophobicity at Small and Large Length Scales

In a physically confined environment, interfacial interactions, symmetry breaking, structural frustration and confinement-induced entropy loss can play dominant roles in determining molecular organization. Here we present a systematic study of the confined assembly of silica-surfactant composite mesostructures within cylindrical nanochannels of varying diameters. Using exactly the same precursors and reaction conditions that form the two-dimensional hexagonal SBA-15 mesostructured thin film, unprecedented silica mesostructures with chiral mesopores such as single- and double-helical geometries spontaneously form inside individual alumina nanochannels. On tightening the degree of confinement, a transition is observed in the mesopore morphology from a coiled cylindrical to a spherical cage-like geometry. Self-consistent field calculations carried out to account for the observed mesostructures accord well with experiment. The mesostructures produced by confined syntheses are useful as templates for fabricating highly ordered mesostructured nanowires and nanowire arrays.

/pdf/composite-mesostructures-by-nano-confinement-12i4j0bzwe.pdf

Composite mesostructures by nano-confinement.

http://www.mrl.ucsb.edu/%7Ekatsov/pubs/pub024.pdf

Biological and synthetic membranes: What can be learned from a coarse-grained description?

We discuss the role coarse-grained models play in the investigation of the structure and thermodynamics of bilayer membranes, and we place them in the context of alternative approaches. Because they reduce the degrees of freedom and employ simple and soft effective potentials, coarse-grained models can provide rather direct insight into collective phenomena in membranes on large time and length scales. We present a summary of recent progress in this rapidly evolving field, and pay special attention to model development and computational techniques. Applications of coarse-grained models to changes of the membrane topology are illustrated with studies of membrane fusion utilizing simulations and self-consistent field theory.

http://www.mrl.ucsb.edu/~katsov/pubs/pub017.pdf

Field Theoretic Study of Bilayer Membrane Fusion. I. Hemifusion Mechanism

https://faculty.washington.edu/schick/Abstracts/mmfusion03.final.pdf

Kirill Katsov

Papers

Composite mesostructures by nano-confinement.

Biological and synthetic membranes: What can be learned from a coarse-grained description?

Biological and synthetic membranes: What can be learned from a coarse-grained description?

Field Theoretic Study of Bilayer Membrane Fusion. I. Hemifusion Mechanism

A new mechanism of model membrane fusion determined from Monte Carlo simulation.