The subtle interplay of several different effects makes the interpretation and analysis of experimental spectra in terms of structural and dynamic characteristics a very challenging task. In this context, theoretical studies can be very helpful, and this is the reason behind the rapid evolution of computational spectroscopy from a highly specialized research field toward a versatile and widespread tool. However, in the case of vibrational spectra of large molecular systems, the most popular approach still relies on a harmonic treatment, because of the difficulty to explore the multidimensional anharmonic potential energy surface. These can be overcome considering that, in many cases, the vibrational transitions are well localized and only some of them are observed experimentally. To this aim, the procedure for the simulation of vibrational spectra of large molecular systems beyond the harmonic approximation is discussed. The quality of system-specific reduced dimensional anharmonic approaches is first validated by comparison with computations taking into account all modes simultaneously for anisole and glycine. Next, the approach is applied to two larger systems, namely glycine adsorbed on a silicon surface and chlorophyll-a in solution, and the results are compared with experimental data showing significant improvement over the standard harmonic approximation. Our results show that properly tailored reduced dimension anharmonic approaches stand as feasible routes for state-of-the-art computational spectroscopy studies and allow to take into account both anharmonic and environmental effects on the spectra even for relatively large molecular systems.

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 ....

The subtle interplay of several different effects means that the interpretation and analysis of experimental spectra in terms of structural and dynamic characteristics is a challenging task. In this context, theoretical studies can be helpful, and as such, computational spectroscopy is rapidly evolving from a highly specialized research field toward a versatile and widespread tool. However, in the case of electronic spectra (e.g. UV/Vis, circular dichroism, photoelectron, and X-ray spectra), the most commonly used methods still rely on the computation of vertical excitation energies, which are further convoluted to simulate line shapes. Such treatment completely neglects the influence of nuclear motions, despite the well-recognized notion that a proper account of vibronic effects is often mandatory to correctly interpret experimental findings. Development and validation of improved models rooted into density functional theory (DFT) and its time-dependent extension (TD-DFT) is of course instrumental for the optimal balance between reliability and favorable scaling with the number of electrons. However, the implementation of easy-to-use and effective procedures to simulate vibrationally resolved electronic spectra, and their availability to a wide community of users, is at least equally important for reliable simulations of spectral line shapes for compounds of biological and technological interest. Here, such an approach has been applied to the study of the UV/Vis spectra of chlorophyll a. The results show that properly tailored approaches are feasible for state-of-the-art computational spectroscopy studies, and allow, with affordable computational resources, vibrational and environmental effects on the spectral line shapes to be taken into account for large systems.

Inspired by nature, many applications and new materials benefit from the interplay of inorganic materials and biomolecules. A fundamental understanding of complex organic–inorganic interactions would improve the controlled production of nanomaterials and biosensors to the development of biocompatible implants for the human body. Although widely exploited in applications, the interaction of amino acids and peptides with most inorganic surfaces is not fully understood. To date, precisely characterizing complex surfaces of inorganic materials and analyzing surface–biomolecule interactions remain challenging both experimentally and computationally. This article reviews several approaches to characterizing biomolecule–surface interactions and illustrates the advantages and disadvantages of the methods presented. First, we explain how the adsorption mechanism of amino acids/peptides to inorganic surfaces can be determined and how thermodynamic and kinetic process constants can be obtained. Second, we demonstrate how this data can be used to develop models for peptide–surface interactions. The understanding and simulation of such interactions constitute a basis for developing molecules with high affinity binding domains in proteins for bioprocess engineering and future biomedical technologies.