Can current force fields reproduce ring puckering in 2-O-sulfo-α-l-iduronic acid? A molecular dynamics simulation study

The monosaccharide 2-O-sulfo-α-l-iduronic acid (IdoA2S) is one of the major components of glycosaminoglycans. The ability of molecular mechanics force fields to reproduce ring-puckering conformational equilibrium is important for the successful prediction of the free energies of interaction of these carbohydrates with proteins. Here we report unconstrained molecular dynamics simulations of IdoA2S monosaccharide that were carried out to investigate the ability of commonly used force fields to reproduce its ring conformational flexibility in aqueous solution. In particular, the distribution of ring conformer populations of IdoA2S was determined. The GROMOS96 force field with the SPC/E water potential can predict successfully the dominant skew-boat to chair conformational transition of the IdoA2S monosaccharide in aqueous solution. On the other hand, the GLYCAM06 force field with the TIP3P water potential sampled transitional conformations between the boat and chair forms. Simulations using the GROMOS96 force field showed no pseudorotational equilibrium fluctuations and hence no inter-conversion between the boat and twist boat ring conformers. Calculations of theoretical proton NMR coupling constants showed that the GROMOS96 force field can predict the skew-boat to chair conformational ratio in good agreement with the experiment, whereas GLYCAM06 shows worse agreement. The omega rotamer distribution about the C5–C6 bond was predicted by both force fields to have torsions around 10°, 190°, and 360°.

Reproducibility of scratch assays is affected by the initial degree of confluence: Experiments, modelling and model selection

Scratch assays are difficult to reproduce. Here we identify a previously overlooked source of variability which could partially explain this difficulty. We analyse a suite of scratch assays in which we vary the initial degree of confluence (initial cell density). Our results indicate that the rate of re-colonisation is very sensitive to the initial density. To quantify the relative roles of cell migration and proliferation, we calibrate the solution of the Fisher–Kolmogorov model to cell density profiles to provide estimates of the cell diffusivity, D, and the cell proliferation rate, λ. This procedure indicates that the estimates of D and λ are very sensitive to the initial density. This dependence suggests that the Fisher–Kolmogorov model does not accurately represent the details of the collective cell spreading process, since this model assumes that D and λ are constants that ought to be independent of the initial density. Since higher initial cell density leads to enhanced spreading, we also calibrate the solution of the Porous–Fisher model to the data as this model assumes that the cell flux is an increasing function of the cell density. Estimates of D and λ associated with the Porous–Fisher model are less sensitive to the initial density, suggesting that the Porous–Fisher model provides a better description of the experiments.