Biomolecular Complexation on the "Wrong Side": A Case Study of the Influence of Salts and Sugars on the Interactions between Bovine Serum Albumin and Sodium Polystyrene Sulfonate.

In the protein purification, drug delivery, food industry, and biotechnological applications involving protein-polyelectrolyte complexation, proper selection of co-solutes and solution conditions plays a crucial role. The onset of (bio)macromolecular complexation occurs even on the so-called "wrong side" of the protein isoionic point where both the protein and the polyelectrolyte are net like-charged. To gain mechanistic insights into the modulatory role of salts (NaCl, NaBr, and NaI) and sugars (sucrose and sucralose) in protein-polyelectrolyte complexation under such conditions, interaction between bovine serum albumin (BSA) and sodium polystyrene sulfonate (NaPSS) at pH = 8.

Modulating Role of Co-Solutes in Complexation between Bovine Serum Albumin and Sodium Polystyrene Sulfonate.

The action of three types of co-solutes: (i) salts (NaCl, NaBr, NaI), (ii) polymer (polyethylene glycol; PEG-400, PEG-3000, PEG-20000), and (iii) sugars (sucrose, sucralose) on the complexation between bovine serum albumin (BSA) and sodium polystyrene sulfonate (NaPSS) was studied. Three critical pH parameters were extracted from the pH dependence of the solution’s turbidity: pHc corresponding to the formation of the soluble complexes, pHΦ corresponding to the formation of the insoluble complexes, and pHopt corresponding to the charge neutralization of the complexes. In the presence of salts, the formation of soluble and insoluble complexes as well as the charge neutralization of complexes was hindered, which is a consequence of the electrostatic screening of attractive interactions between BSA and NaPSS.

Machine learning assessment of the binding region as a tool for more efficient computational receptor-ligand docking.

We present a combined computational approach to protein-ligand binding, which consists of two steps: (1) a deep neural network is used to locate a binding region on a target protein, and (2) molecular docking of a ligand is performed within the specified region to obtain the best pose using Autodock Vina. Our in-house designed neural network was trained using the PepBDB dataset. Although the training dataset consisted of protein-peptide complexes, we show that the approach is not limited to peptides, but also works remarkably well for a large class of non-peptide ligands.

Mechanistic differences in the effects of sucrose and sucralose on the phase stability of lysozyme solutions.

The effect of two disaccharide analogues, sucrose and sucralose, on the phase stability of aqueous lysozyme solutions has been addressed from a mechanistic viewpoint by a combination of experiment and molecular dynamics (MD) simulations. The influence of the added low molecular weight salts (NaBr, NaI and NaNO) was considered as well. The cloud-point temperature measurements revealed a larger stabilizing effect of sucralose.

Hydrogen bonding between hydrides of the upper-right part of the periodic table.

One of the most important electrostatic interactions between molecules is most definitely the hydrogen bond. Understanding the basis of this interaction may offer us the insight needed to understand its effect on the macroscopic scale. Hydrogen bonding is for example the reason for anomalous properties in compounds like water and naturally life as we know it.

Obesity resistant mechanisms in the Lean polygenic mouse model as indicated by liver transcriptome and expression of selected genes in skeletal muscle.

Background: Divergently selected Lean and Fat mouse lines represent unique models for a polygenic form of resistance and susceptibility to obesity development. Previous research on these lines focused mainly on obesity-susceptible factors in the Fat line. This study aimed to examine the molecular basis of obesity-resistant mechanisms in the Lean line by analyzing various fat depots and organs, the liver transcriptome of selected metabolic pathways, plasma and lipid homeostasis and expression of selected skeletal muscle genes.

Divergent physical activity and novel alternative responses to high fat feeding in polygenic fat and lean mice.

We determined whether altered physical activity levels might underlie the contrasting adiposity of a divergently selected polygenic murine model of metabolic syndrome (Fat; F) and leanness (Lean; L) mice. We measured physical activity with a long term running wheel experiment and performed an additional high fat diet intervention. Further, we measured posture allocation by visual monitoring within the home cage as a non-exercise correlate of 'normal' physical activity.