I do classical molecular dynamics simulations for a living, and I feel the model using in this paper is pretty dramatically different than what would typically be described as classical dynamics. 2B atoms would be absolutely insane for any sort of simulation that resolves forces between atoms of even groups of atoms, especially in organic systems.
As far as I can tell from their model, molecules don't interact with each other ~at all~ through classical dynamics. Rather, they define concentrations of various molecules on a voxel grid, assign diffusion coffecients for molecules and define reaction rates between each pair of molecules. Within each voxel, concentrations are assumed constant and evolve through a stochastic Monte-Carlo type simulation. Diffusion is solved as a system of ODEs.
This is a cool large scale simulation using this method, but this is a far cry from an actual atomic-level simulation of a cell, even using the crude approximations of classical molecular dynamics. IMO it is kind of disingenuous for them to say 2B atoms simulation when atoms don't really exist in their model, but it's a press release so it should be expected.
Excuse formatting, one phone. Was gonna put more refs... But phone.
Yes, this is not the standard "force field" pairwise stuff you're used to when you heard "simulation" of biomolecular systems. I don't know if it's quite disingenuous, just not what we expect based on what the vast, vast majority of the field does! It does represent that many atoms. We shouldn't include atoms for the sake of having them, right? It should depend on what questions we're asking of the system.
I like seeing other (simulation or analytic) methods get attention. Lattice methods --(HP models[0], for hydrophobicity[1], lattice-boltzmann even. field theoretic (see polymer physics, melts, old theory[2], new theory, and even newer simulation[3]). Even the simplest shit like springs[4]!
It also represents even more electrons and even more quarks than that. I think it would be silly to characterize this system by the number of constituent quarks, but that's just me. To me, the important number is the number of degrees of freedom within the model. In a force-field model this scales linearly in with the number of atoms. In the model presented in the paper, this depends on voxel resolution and number of molecular species. Sadly, this is omitted in the press release.
Thanks for your links :) I work in inorganic materials but I really should understand more about models for more complex systems.
Do you know how they deal with DNA? Does it fit in a single voxel? (Probably no). Are strands of DNA and RNA treated in chunks in a chain of voxels? Does the simulation perform transcription?
I am not an expert on this type of model but after reading their methods section a little more thoroughly, this is my sense:
I don't believe there is any case where a molecule in one voxel knows about molecules in other voxels. DNA and RNA is coarse grained where a 'molecule' might represent a specific sequence of interest rather than a full chain. Transcription and translation are modeled, essentially by saying if the neccessary ingredients are present in a voxel (DNA/RNA sequences, enzymes, raw materials, etc) there is some chance of forming mRNA or a protein as a function of the molecular concentrations present in the voxel. DNA and RNA reactions are treated with somewhat different equations than the rest of the molecules, I think to handle the coarse graining.
This is all correct. These simulations actually can model molecular crowding by using a diffusive propensity proportional to the particles in the adjacent cells but I don’t think it was used here. I developed this methodology in grad school, but it didn’t go any where.
Thanks for confirming my take. This is a little out of my comfort zone.
Do you see a future for this simulation method with increased computing power, or do you think limitations of the method might still limit its applicability. Maybe this is naivete coming from atomistic perspective, but it seems to me that the inability to model reactions that aren't explicitly predefined would be a significant challenge.
Dna does not fit in a voxel. Transcription is modeled by particles fixed in space which produce transcripts at a constant rate. The mRNA is treated the same as the other discrete particles in the simulation, though they are likely a bit bigger than the voxel size.
As far as I can tell from their model, molecules don't interact with each other ~at all~ through classical dynamics. Rather, they define concentrations of various molecules on a voxel grid, assign diffusion coffecients for molecules and define reaction rates between each pair of molecules. Within each voxel, concentrations are assumed constant and evolve through a stochastic Monte-Carlo type simulation. Diffusion is solved as a system of ODEs.
This is a cool large scale simulation using this method, but this is a far cry from an actual atomic-level simulation of a cell, even using the crude approximations of classical molecular dynamics. IMO it is kind of disingenuous for them to say 2B atoms simulation when atoms don't really exist in their model, but it's a press release so it should be expected.