Shihu Wang

Coarse-Grained Molecular Dynamics Simulation of Self-Assembly and Surface Adsorption of Ionic Surfactants Using an Implicit Water Model

We perform coarse-grained molecular dynamics simulations for sodium dodecyl sulfate (SDS) surfactant using a modification of the Dry Martini force field (Arnarez et al. 2014) with implicit water. After inclusion of particle mesh Ewald (PME) electrostatics, an artificially high dielectric constant for water (ε(r) = 150), and reparameterization, we obtain structural and thermodynamic properties of SDS micelles that are close to those obtained from the standard Martini force field with explicit water, which in turn match those of atomistic simulations. The gains in computational efficiency obtained by removing explicit water allow direct simulations of the self-assembly of SDS in solution. We observe surfactant exchange among micelles and micelle fission and fusion and obtain realistic, equilibrated micelle size distributions at modest computational cost, as well as a transition to cylindrical micelles at high surfactant concentration or with added salt. We further apply this parametrized force field to study the adsorption of SDS onto hydrophobic surfaces and calculate the adsorption kinetics and equilibrium adsorption isotherm. The greatly increased speed of computation of surfactant self-assembly made possible by this Dry Martini method should allow future simulation of competitive adsorption of multiple surfactant species to surfaces, as well as simulation of micellar shape transitions.

Coarse-grained molecular dynamics simulation of tethered lipid assemblies

Using coarse-grained molecular dynamic simulations based on the MARTINI force field, we study the self-assembly of free dipalmitoylphosphatidylcholine (DPPC) lipids onto PEGylated lipids tethered to a solid substrate. We show that upon increasing lipid concentration, structural transitions occur from tethered spherical nanoparticles, to tethered cylinders and bicelles, to a tethered lipid bilayer with pores, to an unporated tethered lipid bilayer, and finally to a tethered lipid bilayer with liposomes on top of it. The simulation results compare well with structures inferred from experimental observations. In addition, we demonstrate the structural stability and local fluidity of the tethered lipid bilayer.

Proteins searching for their target on DNA by one-dimensional diffusion: overcoming the "speed-stability" paradox.

The sequence dependence of DNA-protein interactions that allows proteins to find the correct reaction site also slows down the 1D diffusion of the protein along the DNA molecule, leading to the so-called “speed-stability paradox,” wherein fast diffusion along the DNA molecule is seemingly incompatible with stable targeting of the reaction site. Here, we develop diffusion-reaction models that use discrete and continuous Gaussian random 1D diffusion landscapes with or without a high-energy cut-off, and two-state models with a transition to and from a “searching” mode in which the protein diffuses rapidly without recognizing the target. We show the conditions under which such considerations lead to a predicted speed-up of the targeting process, and under which the presence of a “searching” mode in a two-state model is nearly equivalent to the existence of a high-energy cut-off in a one-state model. We also determine the conditions under which the search is either diffusion-limited or reaction-limited, and develop quantitative expressions for the rate of successful targeting as a function of the site-specific reaction rate, the roughness of the DNA-protein interaction potential, and the presence of a “searching” mode. In general, we find that a rough landscape is compatible with a fast search if the highest energy barriers can be avoided by “hopping” or by the protein transitioning to a lower-energy “searching” mode. We validate these predictions with the results of Brownian dynamics, kinetic Metropolis, and kinetic Monte Carlo simulations of the diffusion and targeting process, and apply these concepts to the case of T7 RNA polymerase searching for its target site on T7 DNA.

Multiple relaxation modes in suspensions of colloidal particles bridged by telechelic polymers

We build a Brownian dynamics simulation model to study the linear rheology of latex particles interacting with telechelic polymers (for example, so-called “HEUR” polymers), with the latter modeled as Finitely Extensible Nonlinear Elastic (FENE) dumbbells with ends that stick to Brownian colloidal spheres. We identify from this model four relaxation modes, including (1) a single chain relaxation time, τ′FENE, which is closely related to τFENE, the relaxation time of a free chain predicted using the FENE model, but is around 1.4 times longer because of surface constraints on polymer configuration; (2) a loop translational-rotational relaxation time, τloop, produced by migration of the chain over the particle surface, allowing it to further relax its orientational conformation while still trapped on the particle surface; (3) a bridge formation/breakage relaxation time, τbridge; and (4) one or more colloidal particle cluster relaxation times. We show that τloop scales as the square of particle radius. τbridge...

Proteins Searching for their Target on DNA by One-Dimensional Diffusion: Overcoming the “Speed-Stability” Paradox

The sequence dependence of DNA-protein interactions that allows proteins to find the correct reaction site also slows down the 1D diffusion of the protein along the DNA molecule, leading to the so-called “speed-stability paradox,” wherein fast diffusion along the DNA molecule is seemingly incompatible with stable targeting of the reaction site. Here, we develop diffusion-reaction models that use discrete and continuous Gaussian random 1D diffusion landscapes with or without a high-energy cut-off, and two-state models with a transition to and from a “searching” mode in which the protein diffuses rapidly without recognizing the target. We show the conditions under which such considerations lead to a predicted speed-up of the targeting process, and under which the presence of a “searching” mode in a two-state model is nearly equivalent to the existence of a high-energy cut-off in a one-state model. We also determine the conditions under which the search is either diffusion-limited or reaction-limited, and develop quantitative expressions for the rate of successful targeting as a function of the site-specific reaction rate, the roughness of the DNA-protein interaction potential, and the presence of a “searching” mode. In general, we find that a rough landscape is compatible with a fast search if the highest energy barriers can be avoided by “hopping” or by the protein transitioning to a lower-energy “searching” mode. We validate these predictions with the results of Brownian dynamics, kinetic Metropolis, and kinetic Monte Carlo simulations of the diffusion and targeting process, and apply these concepts to the case of T7 RNA polymerase searching for its target site on T7 DNA.