Hidden Conformations in Aspergillus niger Monoamine Oxidase are Key for Catalytic Efficiency.

Enzymes exist as an ensemble of conformational states, whose populations can be shifted by substrate binding, allosteric interactions, but also by introducing mutations to their sequence. Tuning the populations of the enzyme conformational states through mutation enables evolution towards novel activity. Herein, Markov state models are used to unveil hidden conformational states of monoamine oxidase from Aspergillus niger (MAO-N). These hidden conformations, not previously observed by any other technique, play a crucial role in substrate binding and enzyme activity. This reveals how distal mutations regulate MAO-N activity by stabilizing these hidden, catalytically important conformational states, but also by modulating the communication pathway between both MAO-N subunits.

On the performance of some aromaticity indices: a critical assessment using a test set.

Aromaticity is a central chemical concept widely used in modern chemistry for the interpretation of molecular structure, stability, reactivity, and magnetic properties of many compounds. As such, its reliable prediction is an important task of computational chemistry. In recent years, many methods to quantify aromaticity based on different physicochemical properties of molecules have been proposed. However, the nonobservable nature of aromaticity makes difficult to assess the performance of the numerous existing indices. In the present work, we introduce a series of fifteen aromaticity tests that can be used to analyze the advantages and drawbacks of a group of aromaticity descriptors. On the basis of the results obtained for a set of ten indicators of aromaticity, we conclude that indices based on the study of electron delocalization in aromatic species are the most accurate among those examined in this work.