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.Magnetic nanoparticles (MNP) are widely used for the purification of nucleic acids and other biological molecules [1][2][3][4] . MNP are also employed in the immobilisation of enzymes 5,6 , for biomedical applications such as drug delivery and hyperthermia in cancer treatment and as contrast agents for magnetic resonance imaging 7,8 . Their superparamagnetic behaviour allows for their manipulation by an external magnetic field to easily accumulate MNP in a desired area 9 . In addition, MNP have also spiked interest in the field of catalytic reaction engineering 10 . For most applications, MNP have to be functionalised to allow for a selective binding of the target molecule. This is presently achieved by attaching metal-ion chelating molecules, e.g. nitrilotriacetic acid, to the MNP surface, which then bind His-tagged biomolecules 11,12 . Drawbacks of this method are the leakage of toxic metal ions and instability of the surface functionalisation 13,14 . Alternative surface modifications for protein adsorption on magnetic particles are glutathione, streptavidin, biotin or protein A, all of which lead to high costs running in the thousands of Euros per gram 15 . Use of bare superparamagnetic iron oxides thus offers decisive advantages for industrial applications mainly due to the easy, rapid and low-cost synthesis and the absence of degradable functional surface groups. We undertake here the first systematic study of peptide-MNP interactions of bare MNP to ultimately develop peptides that can be genetically engineered into proteins as tags and strongly bind to the nonfunctionalised MNP. The key to the design of high-affinity peptide tags lies in an in-depth understanding of surface-peptide recognition patterns 16 ....

A methodology for chemical routes development and evaluation on the basis of data-mining is presented.

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...

We present a hybrid modeling strategy for the prediction of octanol/water partition coefficients for alcohol ethoxylate surfactants of varying chain lengths. The strategy makes use of molecular dynamics (MD) simulations for the generation of molecular conformations in the presence of a solvent. A clustering of the conformations from the MD trajectories was carried out based on principal component analysis of their dihedral angles. Representative conformations thus selected were then used in the conductor-like screening model for realistic solvents (COSMO-RS). Each conformation has been assigned a weight using an equation derived on the basis of its probability of occurrence in the MD trajectory. Experimental partition coefficients were reproduced within conformation-independent accuracy of COSMO-RS despite the size and flexibility of the ethoxy chain otherwise posing a challenge on their solvation modeling.

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Tetrafluoropropene (R1234yf) is the most likely replacement for tetrafluoroethane (R134a), a widely used refrigerant, propellant, and solvent, characterized by a very high global warming potential. In this study, solvation properties of R1234yf were studied experimentally and computationally for solubility of artemisinin, a precursor to the important biopharmaceutical API, and extraction of artemisinin from biomass. R1234yf was shown to be a poorer solvent than R134a for artemisinin. COSMO-RS calculations of solvation in R1234yf suggest that the decrease in performance is likely due to entropic effects. However, R1234yf was effectively used in solid−liquid extraction of Artemisia annua. The new solvent has shown an increased selectivity to the target metabolite artemisinin. This should allow for design of more selective separation processes based on the new solvent molecule with a low global warming potential of 4 relative to CO 2 .

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