A coarse-grained xDLVO model for colloidal protein-protein interactions.

Colloidal protein-protein interactions (PPIs) of attractive and repulsive nature modulate the solubility of proteins, their aggregation, precipitation and crystallization. Such interactions are very important for many biotechnological processes, but are complex and hard to control, therefore, difficult to be understood in terms of measurements alone. In diluted protein solutions, PPIs can be estimated from the osmotic second virial coefficient, B22, which has been calculated using different methods and levels of theory. The most popular approach is based on the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and its extended versions, i.e. xDLVO. Despite much efforts, these models are not fully quantitative and must be fitted to experiments, which limits their predictive value. Here, we report an extended xDLVO-CG model, which extends existing models by a coarse-grained representation of proteins and the inclusion of an additional ion-protein dispersion interaction term. We demonstrate for four proteins, i.e. lysozyme (LYZ), subtilisin (Subs), bovine serum albumin (BSA) and immunoglobulin (IgG1), that semi-quantitative agreement with experimental values without the need to fit to experimental B22 values. While most likely not the final step in the nearly hundred years of research in PPIs, xDLVO-CG is a step towards predictive PPIs calculations that are transferable to different proteins.

Binding patterns of homo-peptides on bare magnetic nanoparticles: insights into environmental dependence.

Magnetic nanoparticles (MNP) are intensively investigated for applications in nanomedicine, catalysis and biotechnology, where their interaction with peptides and proteins plays an important role. However, the characterisation of the interaction of individual amino acids with MNP remains challenging. Here, we classify the affinity of 20 amino acid homo-hexamers to unmodified iron oxide nanoparticles using peptide arrays in a variety of conditions as a basis to identify and rationally design selectively binding peptides. The choice of buffer system is shown to strongly influence the availability of peptide binding sites on the MNP surface. We find that under certain buffer conditions peptides of different charges can bind the MNP and that the relative strength of the interactions can be modulated by changing the buffer. We further present a model for the competition between the buffer and the MNP's electrostatically binding to the adsorption sites. Thereby, we demonstrate that the charge distribution on the surface can be used to correlate the binding of positively and negatively charged peptides to the MNP. This analysis enables us to engineer the binding of MNP on peptides and contribute to better understand the bio-nano interactions, a step towards the design of affinity tags for advanced biomaterials.

The effect of O-methylated flavonoids and other co-metabolites on the crystallization and purification of artemisinin.

Methoxylated flavonoids casticin, artemetin and retusin were identified as putative causative factors for low crystallization yields of artemisinin from extracts. Comparative profiling of biomass grown in different countries found elevated levels (∼60% higher) of artemetin in the East African biomass, which also demonstrates poor crystallization yields. The single compound and the combined doping experiments at 0, 25 and 50 µg mL⁻¹ doping levels showed that artemetin (50 µg mL⁻¹) caused a reduction in the amount of artemisinin crystallized by ca. 60%. A combination of the three flavonoids at 50 µg mL⁻¹ almost completely inhibited crystallization, reducing the yield by 98%. Treatment of extracts by adsorbents efficiently resolves the problem of low crystallization yield.