VTST/MT studies of the catalytic mechanism of C-H activation by transition metal complexes with [Cu2(μ-O2)], [Fe2(μ-O2)] and Fe(IV)-O cores based on DFT potential energy surfaces

Quantum effects in CH activation with [Cu2O2]2+ complexes

We investigate the mechanism of primary alkane CH bond activation with dioxo-dicopper ([Cu2O2]2+) complexes, which serve as model catalysts for enzymes capable of activating CH bonds under mild conditions. As large H/D kinetic isotope effects (KIEs) are observed in enzymes and their synthetic mimics, we employ density functional theory along with variational transition-state theory with multidimensional tunneling to estimate reaction rate coefficients. By systematically varying ligand electrophilicity and substrate chain length, we examine trends in rate coefficients and kinetic isotope effects for the two proposed CH activation pathways - one-step oxo-insertion and two-step radical recombination. Although larger tunneling transmission coefficients are obtained for the radical pathway, the oxo-insertion mechanism yields higher rate coefficients on account of lower activation barriers. The question of the preferred CH activation mechanism, however, remains open: excellent agreement is observed between the predicted and known experimental KIE results for the radical pathway, while calculated Hammett slopes for the oxo-insertion pathway closely mirror experiments.

Simulating chemical reactions promoted by self-assembled peptides with catalytic properties

Peptides that self-assemble exhibit distinct three-dimensional structures and attributes, positioning them as promising candidates for biocatalysts. Exploring their catalytic processes enhances our comprehension of the catalytic actions inherent to self-assembling peptides, laying a theoretical foundation for creating novel biocatalysts. The investigation into the intricate reaction mechanisms of these entities is rendered challenging due to the vast variability in peptide sequences, their aggregated formations, supportive elements, structures of active sites, types of catalytic reactions, and the interplay between these variables. This complexity hampers the elucidation of the linkage between sequence, structure, and catalytic efficiency in self-assembling peptide catalysts. This chapter delves into the latest progress in understanding the mechanisms behind peptide self-assembly, serving as a catalyst in hydrolysis and oxidation reactions, and employing computational analyses. It discusses the establishment of models, selection of computational strategies, and analysis of computational procedures, emphasizing the application of modeling techniques in probing the catalytic mechanisms of peptide self-assemblies. It also looks ahead to the potential future trajectories within this research domain. Despite facing numerous obstacles, a thorough investigation into the structural and catalytic mechanisms of peptide self-assemblies, combined with the ongoing advancement in computational simulations and experimental methodologies, is set to offer valuable theoretical insights for the development of new biocatalysts, thereby significantly advancing the biocatalysis field.

A matrix completion algorithm for efficient calculation of quantum and variational effects in chemical reactions

This work examines the viability of matrix completion methods as cost-effective alternatives to full nuclear Hessians for calculating quantum and variational effects in chemical reactions. The harmonic variety-based matrix completion (HVMC) algorithm, developed in a previous study [S. J. Quiton et al., J. Chem. Phys. 153, 054122 (2020)], exploits the low-rank character of the polynomial expansion of potential energy to recover vibrational frequencies (square roots of eigenvalues of nuclear Hessians) constituting the reaction path using a small sample of its entities. These frequencies are essential for calculating rate coefficients using variational transition state theory with multidimensional tunneling (VTST-MT). HVMC performance is examined for four S_N2 reactions and five hydrogen transfer reactions, with each H-transfer reaction consisting of at least one vibrational mode strongly coupled to the reaction coordinate. HVMC is robust and captures zero-point energies, vibrational free energies, zero-curvature tunneling, and adiabatic ground state and free energy barriers as well as their positions on the reaction coordinate. For medium to large reactions involving H-transfer, with the sole exception of the most complex Ir catalysis system, less than 35% of total eigenvalue information is necessary for accurate recovery of key VTST-MT observables.

Privileged Role of Thiolate as the Axial Ligand in Hydrogen Atom Transfer Reactions by Oxoiron(IV) Complexes in Shaping the Potential Energy Surface and Inducing Significant H-Atom Tunneling

An H/D kinetic isotope effect (KIE) of 80 is found at -20 °C for the oxidation of 9,10-dihydroanthracene by [Fe^IV(O)(TMCS)]⁺, a complex supported by the tetramethylcyclam (TMC) macrocycle with a tethered thiolate. This KIE value approaches that previously predicted by DFT calculations. Other [Fe^IV(O)(TMC)(anion)] complexes exhibit values of 20, suggesting that the thiolate ligand of [Fe^IV(O)(TMCS)]⁺ plays a unique role in facilitating tunneling. Calculations show that tunneling is most enhanced (a) when the bond asymmetry between C-H bond breaking and O-H bond formation in the transition state is minimized, and (b) when the electrostatic interactions in the O---H---C moiety are maximal. These two factors-which peak for the best electron donor, the thiolate ligand-afford a slim and narrow barrier through which the H-atom can tunnel most effectively.

Recent Trends in Quantum Chemical Modeling of Enzymatic Reactions

The quantum chemical cluster approach is a powerful method for investigating enzymatic reactions. Over the past two decades, a large number of highly diverse systems have been studied and a great wealth of mechanistic insight has been developed using this technique. This Perspective reviews the current status of the methodology. The latest technical developments are highlighted, and challenges are discussed. Some recent applications are presented to illustrate the capabilities and progress of this approach, and likely future directions are outlined.