Molecular aggregation is of paramount importance in many chemical processes, including those in living beings. Thus, characterization of the intermolecular interactions is an important step on its understanding. We describe...

Gas-phase spectroscopic studies of alcohol clusters offer accurate information on the influence of non-covalent interactions on molecular recognition, and are of paramount importance to model supramolecular and biological chemical processes....

Sugars are small carbohydrates which play numerous roles in living organisms such as storage of energy or as structural components. Modifications of specific sites within the glycan chain can modulate a carbohydrate's overall biological function as it happens with nucleic acids and proteins. Hence, identifying discrete carbohydrate modifications and understanding their biological effects is essential. A study of such processes requires of a deep knowledge of the interaction mechanism at the molecular level. Here, we use a combination of laser spectroscopy in jets and quantum mechanical calculations to characterize the interaction between phenyl-β-d-glucopyranoside and N-methylacetamide as a model to understand the interaction between a sugar and a peptide bond. The most stable structure of the molecular aggregate shows that the main interaction between the peptide fragment and the sugar proceeds via a C[double bond, length as m-dash]OH-O2 hydrogen bond. A second conformer was also found, in which the peptide establishes a C[double bond, length as m-dash]OH-O6 hydrogen bond with the hydroxymethyl substituent of the sugar unit. All the conformers present an additional interaction point with the aromatic ring. This particular preference of the peptide for the hydroxyl close to the aromatic ring could explain why glycogenin uses tyrosine in order to convert glucose into glycogen by exposing the O4H hydroxyl group for the other glucoses for the polymerization to take place.

Intermolecular interactions are difficult to model, especially in systems formed by multiple interactions. Such is the case of caffeine-phenol. Structural data has been extracted by using mass-resolved excitation spectroscopy and double resonance techniques. Then the predictions of seven different computational methods have been explored to discover structural ande nergeticd iscrepancies betweenthem that may even result in different assignmentso ft he system. The resultsp resented herein highlight the difficulty of constructing functionals to model systems with several competing interactions, and raise awareness of problems with assignmentso fc omplexs ystemsw ith limited experimental information that rely exclusivelyo ne nergetic data.[a] Dr.