Computational Studies on Bioinspired Transition-Metal-Based Catalysts

Dear Colleagues,

The relevance of oxidation and reduction reactions in biology cannot be overstated, driving essential processes such as respiration, metabolism, and photosynthesis. They are central to energy production, the detoxification of harmful substances, and the regulation of cellular processes. Enzymes like cytochrome P450, hemoglobin, and nitrogenase catalyze these reactions with remarkable efficiency and selectivity.

A variety of bioinspired metal complexes based on iron, copper, manganese, molybdenum, tungsten, and nickel are capable of catalyzing a variety of oxidation and reduction reactions such as oxygen reduction, water oxidation, proton and CO₂ reduction, organic molecule transformation, and energy conversion processes, often using ligands like porphyrins, phthalocyanines, and nonporphyrinic tetradentate N4 ligands. By mimicking the mechanisms of biological catalysts, these artificial complexes offer potential applications in energy production, environmental remediation, or pharmaceutical synthesis.

Computational studies play a crucial role in understanding the reactivity of metal complexes and in designing new and more efficient catalysts. Through quantum and molecular mechanical calculations, researchers can investigate reaction mechanisms, predict the properties of catalysts, and optimize their performance. By integrating theory and experiment, computational studies contribute to the advancement of bioinspired catalysis and the realization of its potential for addressing pressing societal challenges.

This Special Issue aims to attract research work about new advances in the computational modelling of bioinspired reactions catalyzed by transition metal complexes, as well as their electronic structure characterization and design. The scope includes, but is not limited to, the following:

• Computational chemistry;
• Quantum mechanics;
• QM/MM;
• Density Functional Theory (DFT);
• Catalysis;
• Reaction mechanism;
• Electronic structure analysis.

Dr. Ferran Acuña-Parés
Guest Editor

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