Computational approaches to the prediction of the redox potentials of iron and copper bioinorganic systems

Abstract

Aim of this contribution is to review some recent quantum mechanical approaches used to compute the redox potentials of transition metal complexes, with the emphasis on copper and iron species, which are particularly relevant in inorganic biochemistry and in synthetic chemistry of biomimetic compounds. The paper presents also new DFT results obtained on Cu and Fe aquo ions in the framework of the Thermodynamic Integration and Grand Canonical Ensemble approaches.Such results show that without explicit inclusion of water molecules in the external solvation shells (even using a continuum solvation model) also very advanced methodologies fail to predict the redox potential in an acceptable manner. This is a confirmation of some previous studies which however never addressed this specific problem along the aforementioned approaches. Better Parkinson and Alzheimer diseases. [2][3][4] As a consequence, the disclosure of the catalytic mechanism of Fe and Cu enzymes, as well as of related bio-mimetic or bio-inspired compounds, is crucial to understand such processes at the molecular level. In this context, the role of computational chemistry, and more specifically of quantum mechanical (QM) methods, cannot be underestimated. These methods, when giving reliable predictions, may nicely complement the experimental investigations, especially to elucidate the catalytic mechanisms of Fe and Cu enzymes, and of related bio-mimetic coordination compounds. [5,6] In fact, most QM studies have been focused on the chemical steps of the catalytic cycles, [7] that is, steps characterized by covalent bond formation and/or cleavage, disclosing the structure and relative energy of key intermediate species and corresponding transition states connecting them, whereas the energetics of redox steps has been often neglected. Indeed, the proper description of electron transfer in coordination compounds implies the accurate calculation of standard reduction potentials, which can be more or less tricky, depending on the coordination compound under investigation. When considering Fe and Cu biologically relevant compounds, several considerations are in order. While iron is often bound to proteins as a cofactor (e.g., the heme group), copper is usually Int.

Toward Diiron Dithiolato Biomimetics with Rotated Conformation of the [FeFe]‐Hydrogenase Active Site: A DFT Case Study on Electron‐Rich, Isocyanide‐Based Scaffolds

“…All calculations were performed with the TURBOMOLE 7.4 suite of programs. [42] The BP86 functional [43,44] has been used in conjunction with a TZVP basis set, [45] plus D3 correction to account for dispersive forces, [46] a protocol that has been intensively validated in the investigation of transition metalcontaining complexes, also in relation to hydrogenase modelling.. [47][48][49][50][51] In order to corroborate the calculated energy trend, we also performed calculations with both TPSS and TPSSh functionals, [52,53] since they provided very satisfactory performances in previous investigations on FeS clusters. [54][55][56] The COSMO approach allowed us to implicitly model the solvation effects.…”

Artificial Photosynthesis: Is Computation Ready for the Challenge Ahead?

“…As already discussed in the presented review, in order to accurately determine the redox properties of metalloproteins, both the electronic structure of the redox center and the environment must be considered. Treating the environment with an implicit solvent approximation eliminated the need of conformational sampling search, strongly reducing the computational cost [ 142 , 143 ]. Yet, these homogeneous models cannot be used to describe explicit contribution and coupling between the redox center and the environment, where polarization can play a crucial role [ 144 ].…”

Accurate Ionization Energies for Mononuclear Copper Complexes Remain a Challenge for Density Functional Theory

“…In solution,t he energetics associated with such processes are typicallye xpressed in terms of standard reduction potentials, and these can often be conveniently measured by cyclic voltammetry and related electrochemical techniques,a lbeit with potentialc omplications associated with irreversible reactions when they occur.C omputational approaches for the prediction of standard reduction potentials, which offer affordable tools for in silico catalystd esign,h ave been extensively benchmarked for many organic andi norganic systems. [17][18][19][20][21][22][23][24][25][26] Although theoretical protocols based on density functional theory (DFT) are in many cases robust, exceptionsa re not uncommon, particularly when transition-metal-based compounds are consid-ered. In our experience, copper-based compoundsc an be particularly challenging in this regard.…”