On calculating reorganization energies for electrochemical reactions using density functional theory and continuum solvation models

Unraveling redox pathways of the disulfide bond in dimethyl disulfide: Ab initio modeling

CONTEXT

In cellular environments, the reduction of disulfide bonds is pivotal for protein folding and synthesis. However, the intricate enzymatic mechanisms governing this process remain poorly understood. This study addresses this gap by investigating a disulfide bridge reduction reaction, serving as a model for comprehending electron and proton transfer in biological systems. Six potential mechanisms for reducing the dimethyl disulfide (DMDS) bridge through electron and proton capture were explored. Thermodynamic and kinetic analyses elucidated the sequence of proton and electron addition. MD-PMM, a method that combines molecular dynamics simulations and quantum-chemical calculations, was employed to compute the redox potential of the mechanism. This research provides valuable insights into the mechanisms and redox potentials involved in disulfide bridge reduction within proteins, offering an understanding of phenomena that are challenging to explore experimentally.

METHODS

All calculations used the Gaussian 09 software package at the MP2/6-311 + g(d,p) theory level. Visualization of the molecular orbitals and electron densities was conducted using Gaussview6. Molecular dynamics simulations were performed using GROMACS with the CHARMM36 force field. The PyMM program (Python Program for QM/MM Simulations Based on the Perturbed Matrix Method) is used to apply the Perturbed Matrix Method to MD simulations.

Mechanistic explorations on the decarboxylative allylation of amino esters via dual photoredox and palladium catalysis

Mechanistic studies reveal that the decarboxylative allylation of amino esters via dual photoredox and palladium catalysis occurs via oxidation giving π-allyl-Pd(II) species and carboxylate, which is oxidized by *Ir(III)-catalyst offering benzyl radicals. The alkylated product is formed via an S_N2 pathway. Single-electron transfer between Pd(I)-species and Ir(II)-catalysis restores both catalysts.

AutoSolvate: A toolkit for automating quantum chemistry design and discovery of solvated molecules

The availability of large, high-quality datasets is crucial for artificial intelligence design and discovery in chemistry. Despite the essential roles of solvents in chemistry, the rapid computational dataset generation of solution-phase molecular properties at the quantum mechanical level of theory was previously hampered by the complicated simulation procedure. Software toolkits that can automate the procedure to set up high-throughput explicit-solvent quantum chemistry (QC) calculations for arbitrary solutes and solvents in an open-source framework are still lacking. We developed AutoSolvate, an open-source toolkit, to streamline the workflow for QC calculation of explicitly solvated molecules. It automates the solvated-structure generation, force field fitting, configuration sampling, and the final extraction of microsolvated cluster structures that QC packages can readily use to predict molecular properties of interest. AutoSolvate is available through both a command line interface and a graphical user interface, making it accessible to the broader scientific community. To improve the quality of the initial structures generated by AutoSolvate, we investigated the dependence of solute-solvent closeness on solute/solvent identities and trained a machine learning model to predict the closeness and guide initial structure generation. Finally, we tested the capability of AutoSolvate for rapid dataset curation by calculating the outer-sphere reorganization energy of a large dataset of 166 redox couples, which demonstrated the promise of the AutoSolvate package for chemical discovery efforts.

Intrinsic nature of photocatalysis by comparing with electrochemistry

Photocatalysis has been gathering much attention because of the unique applications of photoenergy for environmental cleaning and solar fuel production. Electron transfer (ET) at the solid-liquid interface, which initiates photocatalytic reactions, has been the subject of electrochemistry, and hence the reactions are often analyzed in terms of electrochemistry. However, how extensively the concept of electrochemistry can be incorporated has not been discussed so far. In this report, by comparing with electrochemistry, the intrinsic nature of photocatalysis is disclosed and the limitation of the use of the concept of electrochemistry was pointed out. The electric potential near the photocatalyst surface was calculated and visualized, showing a potential gradient similar to that at the electrode surface but localized near the positive hole. Since the frequency of the ET at the photocatalyst surface is limited by the photon absorption, the investigation of photocatalysis in terms of energy states and kinetics should be different from those for electrochemistry. Since semiconductor photocatalysts are not wired to the electric source, the estimation of energy band positions may be altered, which was actually discussed in terms of the band alignments of anatase and rutile TiO2 crystals.

Rates and Routes of Electron Transfer of [NiFe]-Hydrogenase in an Enzymatic Fuel Cell

Hydrogenase enzymes are being used in enzymatic fuel cells immobilized on a graphite or carbon electrode surface, for example. The enzyme is used for the anodic oxidation of molecular hydrogen (H2) to produce protons and electrons. The association and orientation of the enzyme at the anode electrode for a direct electron transfer is not completely resolved. The distal FeS-cluster in [NiFe]-hydrogenases contains a histidine residue which is known to play a critical role in the intermolecular electron transfer between the enzyme and the electrode surface. The [NiFe]-hydrogenase graphite electrode association was investigated using Brownian Dynamics simulations. Residues that were shown to be in proximity to the electrode surface were identified (His184, Ser196, Glu461, Glu464), and electron transfer routes connecting the distal FeS-cluster with the surface residues were investigated. Several possible pathways for electron transfer between the distal FeS-cluster and the terminal amino acid residues were probed in terms of their rates of electron transfer using DFT methods. The reorganization energies λ of the distal iron-sulfur cluster and coronene as a molecular model for graphite were calculated. The reorganization energy of the distal (His)(Cys)3 cluster was found to be not very different from that of a standard cubane clusters with a (Cys)4 coordination. Electronic coupling matrix elements and rates of electron transfer for the different pathways were calculated according to the Marcus equation. The rates for glutamate-mediated electrode binding were found to be incompatible with experimental data. A direct electron transfer from the histidine ligand of the distal FeS-cluster to the electrode yielded rates of electron transfer in excellent agreement with experiment. A second pathway, however, from the distal FeS-cluster to the Ser196 residue was found to be equally efficient and feasible.