Bond bundle analysis is used to investigate enzymatic catalysis in the ketosteroid isomerase (KSI) active site. We identify the unique bonding regions in five KSI systems, including those exposed to applied oriented electric fields and those with amino acid mutations, and calculate the precise redistribution of electron density and other regional properties that accompanies either enhancement or inhibition of KSI catalytic activity. We find that catalytic enhancement results from promoting both inter- and intra-molecular electron density redistribution, between bond bundles and bond wedges within the KSI-docked substrate molecule, in the forward direction of the catalyzed reaction. Though the redistribution applies to both types of perturbed systems and is thus suggestive of a general catalytic role, we observe that bond properties (e.g., volume vs energy vs electron count) can respond independently and disproportionately depending on the type of perturbation. We conclude that the resulting catalytic enhancement/inhibition proceeds via different mechanisms, where some bond properties are utilized more by one type of perturbation than the other. Additionally, we find that the correlations between bond wedge properties and catalyzed reaction barrier energies are additive to predict those of bond bundles and atomic basins, providing a rigorous grounding for connecting changes in local charge density to resulting shifts in reaction barrier energy.

Electrostatic preorganization is thought to be a principle factor responsible for the impressive catalytic capabilities of enzymes. The full protein structure is believed to facilitate catalysis by exerting a highly specific electrostatic field on the active site. Computationally determining the extent of electrostatic preorganization is a challenging process. We propose using the topology and geometry of the electron charge density in the enzyme's active site to asses the effects of electrostatic preorganization. In support of this approach we study the convergence of features of the charge density as the size of the active site model increases in Histone Deacetylase 8. The magnitude of charge density at critical points and most Bader atomic charges are found to converge quickly as more of the protein is included in the simulation. The exact position of critical points however, is found to converge more slowly and be strongly influenced by the protein residues that are further away from the active site. We conjecture that the positions of critical points are affected through perturbations to the wavefunctions in the active site caused by dipole moments from amino acid residues throughout the protein. We further hypothesize that electrostatic preorganization, from the point of view of charge density, can not be easily understood through the charges on atoms or the nature of the bonding interactions, but through the relative positions of critical points that are known to correlate with reactivity and reaction barriers.

Histone deacetylases (HDACs) are responsible for the removal of acetyl groups from histones, resulting in gene silencing. Overexpression of HDACs is associated with cancer, and their inhibitors are of particular interest as chemotherapeutics. However, HDACs remain a target of mechanistic debate. HDAC class 8 is the most studied HDAC, and of particular importance due to its human oncological relevance. HDAC8 has traditionally been considered to be a Zn-dependent enzyme. However, recent experimental assays have challenged this assumption and shown that HDAC8 is catalytically active with a variety of different metals, and that it may be a Fe-dependent enzyme in vivo. We studied two opposing mechanisms utilizing a series of divalent metal ions in physiological abundance (Zn(2+), Fe(2+), Co(2+), Mn(2+), Ni(2+), and Mg(2+)). Extensive sampling of the entire protein with different bound metals was done with the mixed quantum-classical QM/DMD method. Density functional theory (DFT) on an unusually large cluster model was used to describe the active site and reaction mechanism. We have found that the reaction profile of HDAC8 is similar among all metals tested, and follows one of the previously published mechanisms, but the rate-determining step is different from the one previously claimed. We further provide a scheme for estimating the metal binding affinities to the protein. We use the quantum theory of atoms in molecules (QTAIM) to understand the different binding affinities for each metal in HDAC8 as well as the ability of each metal to bind and properly orient the substrate for deacetylation. The combination of this data with the catalytic rate constants is required to reproduce the experimentally observed trend in metal-depending performance. We predict Co(2+) and Zn(2+) to be the most active metals in HDAC8, followed by Fe(2+), and Mn(2+) and Mg(2+) to be the least active.

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. Within this suite of principally different methods, there are both complementarity of capabilities and cross-validation. Using these methods, predictions can be made regarding the relative activities of related enzymes, as we show on the native Zn²⁺-dependent carboxypeptidase A (CPA), and its mutant proteins, which are hypothesized to hydrolyze modified substrates. For the native CPA, we replicated the catalytic mechanism and the rate in close agreement with the experiment, giving validity to the QM/DMD predicted structure, the DFT mechanism, and the QTAIM assessment of catalytic activity. For most sequences of the modified substrate and tried CPA mutants, substantially worsened activity is predicted. However, for the substrate mutant that contains Asp instead of Phe at the C-terminus, one CPA mutant exhibits a reasonable activity, as predicted across the theoretical methods. CPA is a well-studied system, and here it serves as a testing ground for the offered methods.