A QM/MM Study of Nitrite Binding Modes in a Three-Domain Heme-Cu Nitrite Reductase

Unveiling novel pathways and key contributors in the nitrogen cycle: Validation of enrichment and taxonomic characterization of oxygenic denitrifying microorganisms in environmental samples

Microorganisms play a crucial role in both the nitrogen cycle and greenhouse gas emissions. A recent discovery has unveiled a new denitrification pathway called oxygenic denitrification, entailing the enzymatic reduction of nitrite to nitric oxide (NO) by a putative nitric oxide dismutase (nod) enzyme. In this study, the presence of the nod gene was detected and subsequently enriched in anaerobic-activated sludge, farmland soil, and paddy soil samples. After 150 days, the enriched samples exhibited significant denitrification, and concomitant oxygen production. The removal efficiency of nitrite ranged from 64.6 % to 79.0 %, while the oxygen production rate was between 15.4 μL/min and 18.6 μL/min when exposed to a sole nitrogen source of 80 mg/L sodium nitrite. Additionally, batch experiments and kinetic analyses revealed the intricate pathways and underlying mechanisms governing the oxygenic denitrification reaction by using CARBOXY-PTIO, 18O-labelled water, and acetylene to unravel the intricacies of the reaction. The quantitative polymerase chain reaction (qPCR) results indicated a significant surge in the abundance of nod genes, escalating from 7.59 to 10.12-fold. Moreover, analysis of 16S ribosomal DNA (rDNA) amplicons revealed Proteobacteria as the dominant phylum and Thauera as the main genus, with the presumed affiliation. In this study, a new nitrogen conversion pathway, oxygenic denitrification, was discovered in environmental samples. This process provides the possibility for the control of nitrous oxide in the treatment of nitrogenous wastewater.

Multiscale QM/MM modelling of catalytic systems with ChemShell

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods are a powerful computational tool for the investigation of all forms of catalysis, as they allow for an accurate description of reactions occurring at catalytic sites in the context of a complicated electrostatic environment. The scriptable computational chemistry environment ChemShell is a leading software package for QM/MM calculations, providing a flexible, high performance framework for modelling both biomolecular and materials catalysis. We present an overview of recent applications of ChemShell to problems in catalysis and review new functionality introduced into the redeveloped Python-based version of ChemShell to support catalytic modelling. These include a fully guided workflow for biomolecular QM/MM modelling, starting from an experimental structure, a periodic QM/MM embedding scheme to support modelling of metallic materials, and a comprehensive set of tutorials for biomolecular and materials modelling.

QM/MM Simulations of Protein Crystal Reactivity Guided by MSOX Crystallography: A Copper Nitrite Reductase Case Study

The recently developed multiple structures from one crystal (MSOX) serial crystallography method can be used to provide multiple snapshots of the progress of enzymatic reactions taking place within a protein crystal. Such MSOX snapshots can be used as a reference for combined quantum mechanical/molecular mechanical (QM/MM) simulations of enzyme reactivity within the crystal. QM/MM calculations are used to identify details of reference states that cannot be directly observed by X-ray diffraction experiments, such as protonation and oxidation states. These reference states are then used as known fixed endpoints for the modeling of reaction paths. We investigate the mechanism of nitrite reduction in an Achromobacter cycloclastes copper nitrite reductase crystal using MSOX-guided QM/MM calculations, identifying the change in nitrite binding orientation with a change in copper oxidation state, and determining the reaction path to the final NO-bound MSOX structure. The results are compared with QM/MM simulations performed in a solvated environment.