An important task of biomolecular simulation is the calculation of relative binding free energies upon chemical modification of partner molecules in a biomolecular complex. The potential of mean force (PMF) along a reaction coordinate for association or dissociation of the complex can be used to estimate binding affinities. A free energy perturbation approach, termed umbrella sampling (US) perturbation, has been designed that allows an efficient calculation of the change of the PMF upon modification of a binding partner based on the trajectories obtained for the wild type reference complex. The approach was tested on the interaction of modified water molecules in aqueous solution and applied to *in silico* alanine scanning of a peptide-protein complex. For the water interaction test case, excellent agreement with an explicit PMF calculation for each modification was obtained as long as no long range electrostatic perturbations were considered. For the alanine scanning, the experimentally determined ranking and binding affinity changes upon alanine substitutions could be reproduced within 0.1–2.0 kcal/mol. In addition, good agreement with explicitly calculated PMFs was obtained mostly within the sampling uncertainty. The combined US and perturbation approach yields, under the condition of sufficiently small system modifications, rigorously derived changes in free energy and is applicable to any PMF calculation. © 2014 Wiley Periodicals, Inc.

The change of a potential of mean force upon the modification of a system can be estimated by an umbrella sampling perturbation method that does not require additional simulations. Application to computational alanine-scanning of a peptide-protein complex by means of relative separation PMFs resulted in accurate free energy estimates for a series of peptide modifications. The method yields rigorously derived free energy changes under the condition of sufficiently small perturbations.

The generalized Newton–Euler inverse mass operator (GNEIMO) method is an advanced method for internal coordinates molecular dynamics (ICMD). GNEIMO includes several theoretical and algorithmic advancements that address longstanding challenges with ICMD simulations. In this article, we describe the GneimoSim ICMD software package that implements the GNEIMO method. We believe that GneimoSim is the first software package to include advanced features such as the equipartition principle derived for internal coordinates, and a method for including the Fixman potential to eliminate systematic statistical biases introduced by the use of hard constraints. Moreover, by design, GneimoSim is extensible and can be easily interfaced with third party force field packages for ICMD simulations. Currently, GneimoSim includes interfaces to LAMMPS, OpenMM, and Rosetta force field calculation packages. The availability of a comprehensive Python interface to the underlying C++ classes and their methods provides a powerful and versatile mechanism for users to develop simulation scripts to configure the simulation and control the simulation flow. GneimoSim has been used extensively for studying the dynamics of protein structures, refinement of protein homology models, and for simulating large scale protein conformational changes with enhanced sampling methods. GneimoSim is not limited to proteins and can also be used for the simulation of polymeric materials.

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The generalized Newton–Euler inverse mass operator (GNEIMO) method is an advanced method for internal coordinates molecular dynamics (ICMD). GNEIMO includes several theoretical and algorithmic advancements that address longstanding challenges with ICMD simulations. In this article, we describe the GneimoSim ICMD software package that implements the GNEIMO method. We believe that GneimoSim is the first software package to include advanced features such as the equipartition principle derived for internal coordinates, and a method for including the Fixman potential to eliminate systematic statistical biases introduced by the use of hard constraints. Moreover, by design, GneimoSim is extensible and can be easily interfaced with third party force field packages for ICMD simulations. Currently, GneimoSim includes interfaces to LAMMPS, OpenMM, and Rosetta force field calculation packages. The availability of a comprehensive Python interface to the underlying C++ classes and their methods provides a powerful and versatile mechanism for users to develop simulation scripts to configure the simulation and control the simulation flow. GneimoSim has been used extensively for studying the dynamics of protein structures, refinement of protein homology models, and for simulating large scale protein conformational changes with enhanced sampling methods. GneimoSim is not limited to proteins and can also be used for the simulation of polymeric materials.
Bayesian inference of conformational state populations from computational models and sparse experimental observables http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1002%2Fjcc.23738Bayesian inference of conformational state populations from computational models and sparse experimental observables Vincent A. Voelz, Guangfeng Zhou 2014-09-24T07:43:26.261276-05:00 doi:10.1002/jcc.23738 John Wiley & Sons, Inc. 10.1002/jcc.23738 http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1002%2Fjcc.23738 Full Paper n/a n/a

We present a Bayesian inference approach to estimating conformational state populations from a combination of molecular modeling and sparse experimental data. Unlike alternative approaches, our method is designed for use with small molecules and emphasizes high-resolution structural models, using inferential structure determination with reference potentials, and Markov Chain Monte Carlo to sample the posterior distribution of conformational states. As an application of the method, we determine solution-state conformational populations of the 14-membered macrocycle cineromycin B, using a combination of previously published sparse Nuclear Magnetic Resonance (NMR) observables and replica-exchange molecular dynamic/Quantum Mechanical (QM)-refined conformational ensembles. Our results agree better with experimental data compared to previous modeling efforts. Bayes factors are calculated to quantify the consistency of computational modeling with experiment, and the relative importance of reference potentials and other model parameters. © 2014 Wiley Periodicals, Inc.

We present a Bayesian inference approach to estimating conformational state populations from a combination of molecular modeling and sparse experimental data. Unlike alternative approaches, our method is designed for use with small molecules and emphasizes high-resolution structural models, using inferential structure determination with reference potentials, and MCMC to sample the posterior distribution of conformational states. As an application of the method, we determine solution-state conformational populations of the 14-membered macrocycle cineromycin B, using a combination of previously published sparse NMR observables and REMD/QM-refined conformational ensembles. Our results agree better with experimental data compared to previous modeling efforts. Bayes factors are calculated to quantify the consistency of computational modeling with experiment, and the relative importance of reference potentials and other model parameters.

Hydrogen interstitials in austenitic Fe-Mn alloys were studied using density-functional theory to gain insights into the mechanisms of hydrogen embrittlement in high-strength Mn steels. The investigations reveal that H atoms at octahedral interstitial sites prefer a local environment containing Mn atoms rather than Fe atoms. This phenomenon is closely examined combining total energy calculations and crystal orbital Hamilton population analysis. Contributions from various electronic phenomena such as elastic, chemical, and magnetic effects are characterized. The primary reason for the environmental preference is a volumetric effect, which causes a linear dependence on the number of nearest-neighbour Mn atoms. A secondary electronic/magnetic effect explains the deviations from this linearity. © 2014 Wiley Periodicals, Inc.

Adding a substantial amount of manganese to steels yields a material with extraordinary mechanical properties. A tiny amount of hydrogen in high-Mn steels, however, is already suffcient for the onset of devastating embrittlement effects. Using first-principles methods, an attraction of both elements is revealed, providing a complete analysis of the elastic, chemical, and magnetic origin of this phenomenon. These insights contribute to strategies to better control the hydrogen distribution in steels.

B3LYP calculations were carried out on hydrolysis reactions of monosubstituted(R) phosphate dianion and sulfate monoanion. In the reacting system, water clusters (H_{2}O)_{22} and (H_{2}O)_{35} are included to trace reaction paths. For both P and S substrates with R = methyl group, elementary processes were calculated. While the phosphate undergoes the substitution at the phosphorus, the sulfate does at the methyl carbon. For the S substrate with R = neopentyl group, the product tert-amyl alcohol was found to be formed via a dyotropic rearrangement from the neopentyl alcohol intermediate. For R = aryl groups, transition-state geometries were calculated to be similar between P and S substrates. Calculated activation energies are in good agreement with experimental values. After the rate-determining transition state of the substitution, the hydronium ion H_{3}O^{+} is formed at the third water molecule. It was suggested that alkyl and aryl substrates are of the different reactivity of the hydrolysis. © 2014 Wiley Periodicals, Inc.

DFT calculations were carried out on hydrolysis reactions of monosubstituted (R) phosphate dianion and sulfate monoanion with water clusters (H_{2}O)_{22} and (H_{2}O)_{33}. For P and S substrates with R = methyl group, different substitution paths were obtained. In contrast, for R = aryl groups, transition-state geometries are similar, and activation energies are in good agreement with experimental values. Kinetic isotope effects were examined for R = 4-nitrophenyl group.

The thermal stabilities and melting behavior of icosahedral nickel clusters under hydrostatic pressure have been studied by constant-pressure molecular dynamics simulation. The potential energy and Lindemann index are calculated. The overall melting temperature exhibits a strong dependence on pressure. The Lindemann index of solid structure before melting varies slowly and is almost independent of pressure. However, after the clusters melt completely, the Lindemann index at the overall melting point strongly depends on pressure. The overall melting temperature is found to be increasing nonlinearly with increasing pressure, while the volume change during melting decreases linearly with increasing pressure. Under a high pressure and temperature environment, similar angular distributions were found between liquid and solid structures, indicating the existence of a converging local structure. © 2014 Wiley Periodicals, Inc.

Since nickel–iron mixture is one kind of dominant components in terrestrial planet lower mantle, melting of nickel under hydrostatic pressure is always an interesting topic. In this work, the melting behaviors of icosahedral nickel clusters under hydrostatic pressure have been studied by constant-pressure molecular dynamic simulation. This work is intended to provide a better understanding for the thermal properties of nickel cluster and will help to develop new nanomaterials under hydrostatic pressure.

Although recent years have seen much progress in the elucidation of the mechanisms underlying the bioluminescence of fireflies, there is to date no consensus on the precise contributions to the light emission from the different possible forms of the chemiexcited oxyluciferin (OxyLH_{2}) cofactor. Here, this problem is investigated by the calculation of excited-state equilibrium constants in aqueous solution for keto–enol and acid–base reactions connecting six neutral, monoanionic and dianionic forms of OxyLH_{2}. Particularly, rather than relying on the standard Förster equation and the associated assumption that entropic effects are negligible, these equilibrium constants are for the first time calculated in terms of excited-state free energies of a Born–Haber cycle. Performing quantum chemical calculations with density functional theory methods and using a hybrid cluster-continuum approach to describe solvent effects, a suitable protocol for the modeling is first defined from benchmark calculations on phenol. Applying this protocol to the various OxyLH_{2} species and verifying that available experimental data (absorption shifts and ground-state equilibrium constants) are accurately reproduced, it is then found that the phenolate-keto-OxyLH^{–} monoanion is intrinsically the preferred form of OxyLH_{2} in the excited state, which suggests a potential key role for this species in the bioluminescence of fireflies. © 2014 Wiley Periodicals, Inc.

Aqueous keto–enol and acid–base excited-state equilibrium constants between six neutral, monoanionic, and dianionic forms of oxyluciferin—the cofactor responsible for the bioluminescence of firefly luciferase—are for the first time calculated from free energies of a Born–Haber cycle, rather than using the Förster equation. Thereby, it is found that the phenolate-keto-OxyLH^{–} monoanion is the preferred excited-state form of oxyluciferin in aqueous solution, attributing a potential key role to this species in the bioluminescence of fireflies.

The efficiency and accuracy of the perturbation-selection used in the symmetry-adapted cluster-configuration interaction (SAC-CI) calculations are investigated for several low-lying valence excited states of 21 medium-size molecules, including typical chromophores with heterocyclic macrocycles (free-base porphine, coumarin, indole, and BODIPY), nucleobases, amino acids (tyrosine and tryptophan), polycyclic aromatic hydrocarbons, and organometallics (ferrocene and Re(bpy) ). Benchmark SAC-CI calculations with up to 110 million operators are performed. The efficiency of the perturbation-selection depends on the molecular orbitals (MOs); therefore, the canonical MO and localized MO (LMO) obtained by Pipek-Mezey's method are examined. Except for the highly symmetric molecules, using LMOs improves the efficiency and accuracy of the perturbation-selection. With using LMOs and perturbation-selection, sufficiently reliable results can be obtained in less than 10% of the computational costs required for the full-dimensional calculations. The perturbation-selection with LMOs is suggested to be a promising method for excited states in larger molecular systems.Copyright © 2014 Wiley Periodicals, Inc.

The efficiency and accuracy of the perturbation-selection for the SAC-CI calculations are investigated for excited states of 21 medium-size molecules. Benchmark SAC-CI calculations with up to 110 million operators are performed. The efficiency of the selection using the canonical and localized MO (LMO) is also examined. Except for highly symmetric molecules, using LMOs improves the efficiency and accuracy. The perturbation-selection with LMOs is a promising method for excited states in larger molecules.

Carbohydrate-binding proteins (CBPs) are potential biomarkers and drug targets. However, the interactions between carbohydrates and proteins are challenging to study experimentally and computationally because of their low binding affinity, high flexibility, and the lack of a linear sequence in carbohydrates as exists in RNA, DNA, and proteins. Here, we describe a structure-based function-prediction technique called SPOT-Struc that identifies carbohydrate-recognizing proteins and their binding amino acid residues by structural alignment program SPalign and binding affinity scoring according to a knowledge-based statistical potential based on the distance-scaled finite-ideal gas reference state (DFIRE). The leave-one-out cross-validation of the method on 113 carbohydrate-binding domains and 3442 noncarbohydrate binding proteins yields a Matthews correlation coefficient of 0.56 for SPalign alone and 0.63 for SPOT-Struc (SPalign + binding affinity scoring) for CBP prediction. SPOT-Struc is a technique with high positive predictive value (79% correct predictions in all positive CBP predictions) with a reasonable sensitivity (52% positive predictions in all CBPs). The sensitivity of the method was changed slightly when applied to 31 APO (unbound) structures found in the protein databank (14/31 for APO versus 15/31 for HOLO). The result of SPOT-Struc will not change significantly if highly homologous templates were used. SPOT-Struc predicted 19 out of 2076 structural genome targets as CBPs. In particular, one uncharacterized protein in *Bacillus subtilis* (1oq1A) was matched to galectin-9 from *Mus musculus*. Thus, SPOT-Struc is useful for uncovering novel carbohydrate-binding proteins. SPOT-Struc is available at http://sparks-lab.org. © 2014 Wiley Periodicals, Inc.

Discovering new carbohydrate-binding proteins (CBPs) is important as they are potential biomarkers and drug targets. A template-based technique is developed to predict CBPs by structural alignment and binding affinity scoring. Its application to structural genome targets yields several novel CBPs.

Oxidative addition of aryl halides to gold(I) complexes are known to be kinetically sluggish. The reasons have so far not been understood. On page 2140 (DOI: 10.1002/jcc.23734), Israel Fernández, Lando P. Wolters, and F. Matthias Bickelhaupt provide the missing insight using the Activation Strain Model (ASM) of chemical reactivity. The relatively high rigidity of gold(I) complexes plays a key role. This rigidity, in combination with the fact that oxidative addition requires bending of the complex, leads to a high catalyst activation strain and thus a high activation energy. Based on this new insight, strategies are developed to achieve lower, more feasible reaction barriers.

On page 2146 (DOI: 10.1002/jcc.23740), ground- and excited-state properties of copper(II) charge-transfer systems are investigated by Alexander Hoffmann, Martin Rohrmüller, Anton Jesser, Ines dos Santos Vieira, Wolf Gero Schmidt, and Sonja Herres-Pawlis starting from density-functional calculations with particular emphasis on the role of the exchange and correlation functional, the basis set, solvent effects, and the treatment of dispersive interactions. Furthermore, the applicability of TD-DFT to excitations of copper(II) bis(chelate) charge-transfer systems is explored by performing many-body perturbation theory (GW+BSE), independent-particle approximation (IPA) and ΔSCF calculations for a small model system containing simple guanidine and imine groups.

An extension of the GROMOS 53A6_{GLYC} force field for carbohydrates to encompass glycoprotein linkages is presented. The set includes new atomic charges and incorporates adequate torsional potential parameters for N-, S-, C-, P-, and O-glycosydic linkages, offering compatibility with the GROMOS force field family for proteins. Validation included the description of glycosydic linkage geometries between amino acid and monosaccharide residues, comparison of NMR-derived protein-carbohydrate and carbohydrate–carbohydrate nuclear overhauser effect (NOE) signals for glycoproteins and the effects of glycosylation on protein flexibility and dynamics. © 2014 Wiley Periodicals, Inc.

The GROMOS 53A6glyc parameter set is suitable for molecular simulations of carbohydrates and glycoproteins. It can properly describe monosaccharide ring pucker, relative abundance of the hydroxymethyl group, and glycosidic linkage geometries, as well as the effects of glycosylation over protein structure and dynamics.

The existence of a network of structured waters in the vicinity of the bimetallic site of Cu/Zn-superoxide dismutase (SOD) has been inferred from high-resolution X-ray crystallography. Long-duration molecular dynamics (MD) simulations could enable to quantify the lifetimes and possible interchanges of these waters between themselves as well as with a ligand diffusing toward the bimetallic site. The presence of several charged or polar ligands makes it necessary to resort to second-generation polarizable potentials. As a first step toward such simulations, we benchmark in this article the accuracy of one such potential, sum of interactions between fragments Ab initio computed (SIBFA), by comparisons with quantum mechanics (QM) computations. We first consider the bimetallic binding site of a Cu/Zn-SOD, in which three histidines and a water molecule are bound to Cu(I) and three histidines and one aspartate are bound to Zn(II). The comparisons are made for different His6 complexes with either one or both cations, and either with or without Asp and water. The total net charges vary from zero to three. We subsequently perform preliminary short-duration MD simulations of 296 waters solvating Cu/Zn-SOD. Six representative geometries are selected and energy-minimized. Single-point SIBFA and QM computations are then performed in parallel on model binding sites extracted from these six structures, each of which totals 301 atoms including the closest 28 waters from the Cu metal site. The ranking of their relative stabilities as given by SIBFA is identical to the QM one, and the relative energy differences by both approaches are fully consistent. In addition, the lowest-energy structure, from SIBFA and QM, has a close overlap with the crystallographic one. The SIBFA calculations enable to quantify the impact of polarization and charge transfer in the ranking of the six structures. Five structural waters, which connect Arg141 and Glu131, are endowed with very high dipole moments (2.7–3.0 Debye), equal and larger than the one computed by SIBFA in ice-like arrangements (2.7 D).

The existence of a network of structured waters in the vicinity of the bimetallic site of Cu, Zn-SOD has been inferred from high-resolution X-ray crystallography. The accuracy of a polarizable force-field, SIBFA, is benchmarked by comparisons with quantum mechanics computations. Six representative geometries are selected from short-duration molecular dynamics and energy-minimized. The ranking of their relative stabilities is identical to the quantum mechanical one. The impact of polarization and charge-transfer contributions is analyzed.

The main photophysical properties of a series of recently synthetized 1,2- and 1,3-squaraines, including absorption electronic spectra, singlet-triplet energy gaps, and spin-orbit matrix elements, have been investigated by means of density functional theory (DFT) and time-dependent DFT approaches. A benchmark of three exchange-correlation functionals has been performed in six different solvent environments. The investigated 1,2 squaraines have been found to possess two excited triplet states (T_{1} and T_{2}) that lie below the energy of the excited singlet one (S_{1}). The radiationless intersystem spin crossing efficiency is thus enhanced in both the studied systems and both the transitions could contribute to the excited singlet oxygen production. Moreover, they have a singlet-triplet energy gap higher than that required to generate the cytotoxic singlet oxygen species. According to our data, these compounds could be used in photodynamic therapy applications that do not require high tissue penetration. © 2014 Wiley Periodicals, Inc.

The main photophysical properties of a series of recently synthetized 1,2- and 1,3-squaraines have been investigated by means of density functional theory (DFT) and time-dependent DFT approaches. Two singlet-triplet intersystem crossings have been found, which could contribute to the excited singlet oxygen production.

The content of chiral carbon atoms or structural complexity, which is known to correlate well with relevant physicochemical properties of small molecules, represents a promising descriptor that could fill the gap in existing drug discovery between ligand library filtering rules and the corresponding properties of the target's recognition site.

Herein, we present an *in silico* study on the yet unclear underlying correlations between molecular complexity and other more sophisticated physicochemical and biological properties. By analyzing thousands of protein–ligand complexes from DrugBank, we show that increasing molecular complexity of drugs is an approach to addressing particularly low-druggability and polar recognition sites. We also show that biologically relevant protein classes characteristically bind molecules with a certain degree of structural complexity. Three distinct behaviors toward drug recognition are described.

The reported results set the basis for a better understanding of protein–drug recognition, and open the possibility of including target information in the filtering of large ligand libraries for screening. © 2014 Wiley Periodicals, Inc.

Using chiral molecules as an approach to address low-druggability recognition sites, the reported theoretical study on the DrugBank database shows that the content of chiral atoms or structural complexity correlates well with relevant physicochemical properties of drugs and their target's recognition site, including its hydrophobic character and druggability. The reported results set the basis for a better understanding of protein–drug recognition and for the inclusion of target information in the filtering of large ligand libraries for drug discovery.

Trifluoromethylation of acetonitrile with 3,3-dimethyl-1-(trifluoromethyl)−1*λ*^{3},2- benziodoxol is assumed to occur via reductive elimination (RE) of the electrophilic CF_{3}-ligand and MeCN bound to the hypervalent iodine. Computations in gas phase showed that the reaction might also occur via an S* _{N}*2 mechanism. There is a substantial solvent effect present for both reaction mechanisms, and their energies of activation are very sensitive toward the solvent model used (implicit, microsolvation, and cluster-continuum). With polarizable continuum model-based methods, the S

Hypervalent iodine compounds, in particular *λ*^{3}-iodanes, have gained considerable attention in synthesis. However, little is known about the mechanistic details. By exploring the reaction mechanism of an iodane reagent with a nucleophile (acetonitrile), it is shown that the same products may be obtained via two different reaction mechanisms. These show a very distinct response to the effect of the solvent; the correct prediction of the mechanism will call for an explicit treatment of the solvent.

The Poisson–Boltzmann implicit solvent (PB) is widely used to estimate the solvation free energies of biomolecules in molecular simulations. An optimized set of atomic radii (PB radii) is an important parameter for PB calculations, which determines the distribution of dielectric constants around the solute. We here present new PB radii for the AMBER protein force field to accurately reproduce the solvation free energies obtained from explicit solvent simulations. The presented PB radii were optimized using results from explicit solvent simulations of the large systems. In addition, we discriminated PB radii for N- and C-terminal residues from those for nonterminal residues. The performances using our PB radii showed high accuracy for the estimation of solvation free energies at the level of the molecular fragment. The obtained PB radii are effective for the detailed analysis of the solvation effects of biomolecules. © 2014 The Authors Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

A collection of atomic radii, which determines the distribution of dielectric constants around the solute, is an important parameter for the Poisson–Boltzmann implicit solvent. For accurate estimation of the solvation free energy of proteins, a new parameter was developed based on results from explicit solvent simulations. New radii showed good agreement with the explicit solvent simulations for large peptides at the level of the small molecular fragment.

By means of density functional theory calculations, we computationally analyze the physical factors governing the oxidative addition of aryl halides to gold(I) complexes. Using the activation strain model of chemical reactivity, it is found that the strain energy associated with the bending of the gold(I) complex plays a key role in controlling the activation barrier of the process. A systematic study on how the reaction barrier depends on the nature of the aryl halide, ligand, and counteranion allows us to identify the best combination of gold(I) complex and aryl halide to achieve a feasible (i.e., low barrier) oxidative addition to gold(I), a process considered as kinetically sluggish so far. © 2014 Wiley Periodicals, Inc.

The oxidative addition of aryl halides to Au(I) complexes is considered a kinetically sluggish reaction. By combining the Activation Strain Model and Energy Decomposition Analysis methods, the factors causing this reaction to be slow are been identified. Based on this new insight, we suggest the best combination of gold(I) complex and aryl halide to turn this process into a feasible, low-barrier transformation.

Ground- and excited-state properties of copper(II) charge-transfer systems have been investigated starting from density-functional calculations with particular emphasis on the role of (i) the exchange and correlation functional, (ii) the basis set, (iii) solvent effects, and (iv) the treatment of dispersive interactions. Furthermore (v), the applicability of TD-DFT to excitations of copper(II) bis(chelate) charge-transfer systems is explored by performing many-body perturbation theory (GW + BSE), independent-particle approximation and ΔSCF calculations for a small model system that contains simple guanidine and imine groups. These results show that DFT and TD-DFT in particular in combination with hybrid functionals are well suited for the description of the structural and optical properties, respectively, of copper(II) bis(chelate) complexes. Furthermore, it is found an accurate theoretical geometrical description requires the use of dispersion correction with Becke–Johnson damping and triple-zeta basis sets while solvent effects are small. The hybrid functionals B3LYP and TPSSh yielded best performance. The optical description is best with B3LYP, whereby heavily mixed molecular transitions of MLCT and LLCT character are obtained which can be more easily understood using natural transition orbitals. An natural bond orbital analysis sheds light on the donor properties of the different donor functions and the intraguanidine stabilization during coordination to copper(I) and (II). © 2014 Wiley Periodicals, Inc.

Ground- and excited-state properties of copper(II) charge-transfer systems have been investigated starting from density-functional calculations with particular emphasis on the role of the exchange and correlation functional, the basis set, solvent effects, and the treatment of dispersive interactions. Furthermore, the applicability of TD-DFT to excitations of copper(II) bis(chelate) charge-transfer systems was explored by performing many-body perturbation theory (GW + BSE), independent-particle approximation (IPA) and ΔSCF calculations for a small model system that contains simple guanidine and imine groups.