Predictive methods for computational metalloenzyme redesign - a test case with carboxypeptidase A.

Computational metalloenzyme design is a multi-scale problem. It requires treating the metal coordination quantum mechanically, extensive sampling of the protein backbone, and additionally accounting for the polarization of the active site by both the metal cation and the surrounding protein (a phenomenon called electrostatic preorganization). We bring together a combination of theoretical methods that jointly offer these desired qualities: QM/DMD for mixed quantum-classical dynamic sampling, quantum theory of atoms in molecules (QTAIM) for the assessment of electrostatic preorganization, and Density Functional Theory (DFT) for mechanistic studies.

σ-Aromaticity in polyhydride complexes of Ru, Ir, Os, and Pt.

Transition-metal hydrides represent a unique class of compounds, which are essential for catalysis, organic synthesis, and hydrogen storage. In this work we study IrH5(PPh3)2, (RuH5(P(i)Pr3)2)(-), (OsH5(P(i)Pr3)2)(-), and OsH4(PPhMe2)3 polyhydride complexes, inspired by the recent discovery of the σ-aromatic PtZnH5(-) cluster anion. The distinctive feature of these molecules is that, like in the PtZnH5(-) cluster, the metal is five-fold coordinated in-plane, and holds additional ligands at the axial positions.