Peptid‐ und Kohlenhydratbiochips lassen sich MALDI‐massenspektrometrisch analysieren. Selbstorganisierte Monoschichten (SAMs), die mit Liganden ausgestattet sind, können zur Identifizierung selektiver Protein‐Ligand‐ und Enzym‐Substrat‐Wechselwirkungen dienen. MALDI‐MS lässt sich als schnelle und empfindliche Nachweismethode einsetzen, wodurch die Notwendigkeit umgangen wird, die Proteinanalyte mit Fluoreszenz‐ oder radioaktiven Markern zu versehen. Das Bild zeigt das Massenspektrum einer Kohlenhydrat‐modifizierten SAM.

The potassium cation affinities (PCAs) of 136 ligands (20 classes) in the gas phase were established by hybrid density functional theory calculations (B3-LYP with the 6-311+G(3df,2p) basis set). For these 136 ligands, 70 experimental values are available for comparison. Except for five specific PCA values-those of phenylalanine, cytosine, guanine, adenine (kinetic-method measurement), and Me(2)SO (by high-pressure mass spectrometric equilibrium measurement)-our theoretical estimates and the experimental affinities are in excellent agreement (mean absolute deviation (MAD) of 4.5 kJ mol(-1)). Comparisons with previously reported theoretical PCAs are also made. The effect of substituents on the modes of binding and the PCAs of unsubstituted parent ligands are discussed. Linear relations between Li+/Na+ and K+ affinities suggest that for the wide range of ligands studied here, the nature of binding between the cations and a given ligand is similar, and this allows the estimation of PCAs from known Li+ and/or Na+ affinities. Furthermore, empirical equations relating the PCAs of ligands with their dipole moments, polarizabilities (or molecular weights), and the number of binding sites were established. Such equations offer a simple method for estimating the PCAs of ligands not included in the present study.

The promotion of spatial skills is essential in chemistry education. However, the process of acquiring these skills can be monotonous if learning is limited to the memorization of Newman projections or 3D molecular kits. Existing approaches to learning using visualizing tools require physical models which limit learning activities to within the classroom. Augmented reality (AR) in chemistry education allows students to see actual compound representation in a 3D environment, inspect compounds from multiple viewpoints, and control compounds interaction in real-time in any location. This facilitates the understanding of the spatial relations between compounds. We developed a methodology to use and assess an AR program to teach chemistry to associate degree science students. Figures of small organic molecules together with customized AR cards were used to let students appreciate the complexity of a 3D compound structure by viewing and rotating the depicted compounds. The effectiveness of learning chemistry using AR technology was evaluated. Quantitative questionnaire feedback results from students showed that 87% found that using AR technology for chemistry subjects was an effective teaching method that enhanced their learning, and students were satisfied with the AR educational app and the AR materials used. In a pre- and post-test evaluation of a group activity, students learned better and remembered more information about functional groups and drawings of complicated compounds after using AR technology. On the basis of our results, we can conclude that using AR has a positive impact on enthusiasm and learning in higher education chemistry courses for subdegree students, and this technology should be broadly used as a digital tool to promote active learning during the COVID-19 pandemic.

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