AlkB repair enzymes are important nonheme iron enzymes that catalyse the demethylation of alkylated DNA bases in humans, which is a vital reaction in the body that heals externally damaged DNA bases. Its mechanism is currently controversial and in order to resolve the catalytic mechanism of these enzymes, a quantum mechanics/molecular mechanics (QM/MM) study was performed on the demethylation of the N¹‐methyladenine fragment by AlkB repair enzymes. Firstly, the initial modelling identified the oxygen binding site of the enzyme. Secondly, the oxygen activation mechanism was investigated and a novel pathway was found, whereby the catalytically active iron(IV)–oxo intermediate in the catalytic cycle undergoes an initial isomerisation assisted by an Arg residue in the substrate binding pocket, which then brings the oxo group in close contact with the methyl group of the alkylated DNA base. This enables a subsequent rate‐determining hydrogen‐atom abstraction on competitive σ‐ and π‐pathways on a quintet spin‐state surface. These findings give evidence of different locations of the oxygen and substrate binding channels in the enzyme and the origin of the separation of the oxygen‐bound intermediates in the catalytic cycle from substrate. Our studies are compared with small model complexes and the effect of protein and environment on the kinetics and mechanism is explained.

Methane, the main component of natural and shale gas, is a significant carbon source for chemical synthesis. The direct partial oxidation of methane to liquid oxygenates under mild conditions^1–3 is an attractive pathway, but the inertness of the molecule makes it challenging to achieve simultaneously high conversion and high selectivity towards a single target product. This difficulty is amplified when aiming for more valuable products that require C–C coupling^4,5. Whereas selective partial methane oxidation processes^1–3,6–9 have thus typically generated C₁ oxygenates^6,7, recent reports have documented photocatalytic methane conversion to the C₂ oxygenate ethanol with low conversions but good-to-high selectivities^4,5,8–12. Here we show that the intramolecular junction photocatalyst covalent triazine-based framework-1 with alternating benzene and triazine motifs^13,14 drives methane coupling and oxidation to ethanol with a high selectivity and significantly improved conversion. The heterojunction architecture not only enables efficient and long-lived separation of charges after their generation, but also preferential adsorption of H₂O and O₂ to the triazine and benzene units, respectively. This dual-site feature separates C–C coupling to form ethane intermediates from the sites where •OH radicals are formed, thereby avoiding over-oxidation. When loaded with Pt to further boost performance, the molecular heterojunction photocatalyst generates ethanol in a packed-bed flow reactor with greatly improved conversion that results in an apparent quantum efficiency of 9.4%. We anticipate that further developing the ‘intramolecular junction’ approach will deliver efficient and selective catalysts for C–C coupling, pertaining, but not limited, to methane conversion to C₂₊ chemicals.

The new biomimetic ligands N4Py^2Ph (1) and N4Py^2Ph,amide (2) were synthesized and yield the iron(II) complexes [Fe^II(N4Py^2Ph)(NCCH₃)](BF₄)₂ (3) and [Fe^II(N4Py^2Ph,amide)](BF₄)₂ (5). Controlled orientation of the Ph substituents in 3 leads to facile triplet spin reactivity for a putative Fe^IV(O) intermediate, resulting in rapid arene hydroxylation. Addition of a peripheral amide substituent within hydrogen-bond distance of the iron first coordination sphere leads to stabilization of a high-spin Fe^IIIOOR species which decays without arene hydroxylation. These results provide new insights regarding the impact of secondary coordination sphere effects at nonheme iron centers.

With computational resources becoming more efficient and more powerful and at the same time cheaper, computational methods have become more and more popular for studies on biochemical and biomimetic systems. Although large efforts from the scientific community have gone into exploring the possibilities of computational methods for studies on large biochemical systems, such studies are not without pitfalls and often cannot be routinely done but require expert execution. In this review we summarize and highlight advances in computational methodology and its application to enzymatic and biomimetic model complexes. In particular, we emphasize on topical and state-of-the-art methodologies that are able to either reproduce experimental findings, e.g., spectroscopic parameters and rate constants, accurately or make predictions of short-lived intermediates and fast reaction processes in nature. Moreover, we give examples of processes where certain computational methods dramatically fail.