Molecular dynamic simulation of Ca2+‐ATPase interacting with lipid bilayer membrane

In biomedical and drug delivery treatments, protein Ca2+-ATPase in the lipid bilayer ( plasma) membrane plays a key role by reducing multidrug resistance of the cancerous cells. The lipid bilayer membrane and the protein Ca2+-ATPase were simulated by utilising the Gromacs software and by applying the all-atom/united atom and coarse-grained models. The initial structure of Ca2+-ATPase was derived from X-ray diffraction and electron microscopy patterns and was placed in a simulated bilayer membrane of dipalmitoylphosphatidylcholine. The conformational changes were investigated by evaluating the root mean square deviation, root mean square fluctuation, order parameter, diffusion coefficients, partial density, thickness and area per lipid

Prediction of Thermophysical Properties for Binary Mixtures of Common Ionic Liquids with Water or Alcohol at Several Temperatures and Atmospheric Pressure by Means of Artificial Neural Network

In this work, thermophysical properties such as density, dynamic viscosity, excess molar volume, refractive index and speed of sound of binary mixtures of common ionic liquids (ILs) with water or alcohol are predicted by the artificial neural network (ANN) technique. In each ANN proposed models, the density and dynamic viscosity of pure components IL, water or alcohol (including methanol, ethanol, 1-propanol and 2-propanol) and pure IL and the temperature as well as mole fractions of water or alcohol of studied binary mixtures were given as the inputs and the desired properties were predicted as the outputs. The obtained results revealed that the selected input parameters were appropriate and the high statistical quality represented by various criteria and the low prediction errors indicated that the presented models can accurately predict the properties of IL + water/alcohol binary mixtures

Self-Accumulation of Uncharged Polyaromatic Surfactants at Crude Oil–Water Interface: A Mesoscopic DPD Study

The dissipative particle dynamics (DPD) technique was applied to study the behavior of several uncharged perylene bisimide-based polyaromatic surfactant (PAS) molecules, with the same polyaromatic core but with different terminal functional types (TP, C5Pe, PAP, and PCH) at the crude oil–water interface. We considered the SARA crude oil model with Persian Gulf oil field composition, which includes saturates, 59%; aromatics, 28.5%; resins, 9.7%; and asphaltenes, 2.8% at two temperatures 298 and 363 K. The DPD interaction parameters for the bead pairs needed in the DPD simulations were evaluated by using the well-known correlation equation, where the required Flory–Huggins interaction parameter in this equation was calculated by the blend methodology model. The results indicated that the C5Pe terminal functional type of PAS is absorbed more effectively on the water droplet interface in the crude oil system and can reduce the interfacial tension (IFT) to facilitate the oil–water separation. The results of this simulation can be used to choose proper demulsifier surfactant for application in various processes in the oil industry as well as enhanced oil recovery (EOR)