A Supramolecular Model for the Co-Catalytic Role of Nitro Compounds in Brønsted Acid Catalyzed Reactions.

Nitro compounds are known to change reaction rates and kinetic concentration dependence of Brønsted-acid-catalyzed reactions. Yet, no mechanistic model exists to account for these observations. In this work, an atomistic model for the catalytically active form for an alcohol dehydroazidation reaction is presented, which is generated by DFT calculations and consists of an H-bonded aggregate of two molecules of Brønsted acid and two molecules of nitro compound. The computed O-H stretching frequencies for the aggregate indicate they are stronger acids than the individual acid molecules and serve as predictors for experimental reaction rates. By applying the model to a chemically diverse set of potential promoters, it was predicted and verified experimentally that sulfate esters induce a similar co-catalytic effect. The important implication is that Brønsted-acid catalysis must be viewed from a supramolecular perspective that accounts for not only the pKa of the acid and the bulk properties of a solvent, but also the weak interactions between all molecules in solution.

Evolving methods for rational de novo design of functional RNA molecules.

Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient alternative to experimental screening and selection pipelines. In this review, we describe methods common to many such computational approaches, thoroughly dissect these methods and highlight open questions for the individual steps. Initially, it is essential to investigate the biological target system, the regulatory mechanism that will be exploited, as well as the desired components in order to define design objectives. Subsequent computational design is needed to combine the selected components and to obtain novel functionality. This process can usually be split into constrained sequence sampling, the formulation of an optimization problem and an in silico analysis to narrow down the number of candidates with respect to secondary goals. Finally, experimental analysis is important to check whether the defined design objectives are indeed met in the target environment and detailed characterization experiments should be performed to improve the mechanistic models and detect missing design requirements.