Journal of Inorganic Biochemistry 204 (2020) 110953 Contents lists available at ScienceDirect Journal of Inorganic Biochemistry journal homepage: www.elsevier.com/locate/jinorgbio Quantitative prediction of electronic absorption spectra of copper T (II)–bioligand systems: Validation and applications Giuseppe Sciortinoa,b, Jean-Didier Maréchala, István Fábiánc,d, Norbert Lihic,d, , ⁎ Eugenio Garribbab, ⁎⁎ a Departament de Química, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallés, Barcelona, Spain b Dipartimento di Chimica e Farmacia, Università di Sassari, Via Vienna 2, I-07100 Sassari, Italy c Department of Inorganic and Analytical Chemistry, University of Debrecen, H-4032 Debrecen, Hungary d MTA-DE Redox and Homogeneous Catalytic Reaction Mechanisms Research Group, University of Debrecen, H-4032 Debrecen, Hungary ARTICLE INFO ABSTRACT Keywords: The visible region of the electronic absorption spectra of Cu(II) complexes was studied by time-dependent density Copper functional theory (TD-DFT). The performance of twelve functionals in the prediction of absorption maxima (λmax) Electronic absorption spectra was tested on eleven compounds with different geometry, donors and charge. The ranking of the functionals for λmax TD-DFT methods was determined in terms of mean absolute percent deviation (MAPD) and standard deviation (SD) and it is as follows: Proteins BHandHLYP > M06 ≫ CAM-B3LYP ≫ MPW1PW91 ~ B1LYP ~ BLYP > HSE06 ~ B3LYP > B3P86 ~ ω-B97x- D ≫ TPSSh ≫ M06-2X (MAPD) and BHandHLYP > M06 ~ HSE06 > ω-B97x-D ~ CAM-B3LYP ~ MPW1PW91 > B1LYP ~ B3LYP > B3P86 > BLYP ≫ TPSSh ≫ M06-2X (SD). With BHandHLYP functional the MAPD is 3.1% and SD is 2.3%, while with M06 the MAPD is 3.7% and SD is 3.7%. The protocol validated in the first step of the study was applied to: i) calculate the number of transitions in the spectra and relate them to the geometry of Cu(II) species; ii) determine the coordination of axial water(s); iii) predict the electronic spectra of the systems where Cu(II) is bound to human serum albumin (HSA) and to the regions 94–97 and 108–112 of prion protein (PrP). The results indicate that the proposed computational protocol allows a successful prediction of the electronic spectra of Cu(II) species and to relate an experimental spectrum to a specific structure. 1. Introduction comprehensive reviews are available in this field focusing on the characterization of structural, functional and spectroscopic features of The molecular modeling of the bioinorganic structures, the elec- (transition metal)–bioligand systems [4–8]. With respect to the spec- tronic and spectroscopic properties of metalloenzymes and their model troscopic properties of these systems, electron paramagnetic resonance systems is a subject of growing interest over the last decade, due mainly (EPR) [9–13] and 1H and 13C nuclear magnetic resonance (NMR) to the effective development of computational methods. Among them, parameters [14–17] have been calculated with great accuracy by density functional theory (DFT) [1] and its time-dependent extension computational techniques and the effect of the pseudo-contact chemical (TD-DFT) [2,3] have been frequently used because of their relative low shift on the NMR spectra originating from paramagnetic complexes was computational cost and implementation in most of the available com- successfully simulated with the use of DFT methods [18–21]. The pre- putational software. Moreover, the effect of the solvation of the che- diction of infrared (IR) and optical (UV-Vis, circular dichroism (CD) and mical species can be treated routinely. Several studies and magnetic circular dichroism (MCD)) spectra have been examined by Abbreviations: APD, absolute percent deviation; ATCUN, amino terminal copper and Nickel binding site; BSA, bovine serum albumin; CD, circular dichroism; CSA, chicken serum albumin; DFT, density functional theory; DSA, dog serum albumin; EPR, electron paramagnetic resonance; GGA, generalized gradient approximation; HSA, human serum albumin; IR, infrared; LMCT, ligand to metal charge transfer; MAPD, mean absolute percent deviation; MBS, multi-metal binding site; MCD, magnetic circular dichroism; MLCT, metal to ligand charge transfer; MO, molecular orbital; MPA, Mulliken population analysis; NMR, nuclear magnetic resonance; PCM, polarized continuum model; PD, percent deviation; PrP, prion protein; RSA, rat serum albumin; SD, standard deviation; SDD, Stuttgart Dresden; TD-DFT, time- dependent density functional theory; UV-Vis, ultraviolet-visible; XRD, X-ray diffraction; εmax, molar absorption coefficient; λmax, absorption maximum ⁎ Correspondence to: Norbert Lihi, MTA-DE Redox and Homogeneous Catalytic Reaction Mechanisms Research Group, University of Debrecen, H-4032 Debrecen, Hungary. ⁎⁎ Correspondence to: Eugenio Garribba, Dipartimento di Chimica e Farmacia, Università di Sassari, Via Vienna 2, I-07100 Sassari, Italy. E-mail addresses: lihi.norbert@science.unideb.hu (N. Lihi), garribba@uniss.it (E. Garribba). https://doi.org/10.1016/j.jinorgbio.2019.110953 Received 4 October 2019; Received in revised form 21 November 2019; Accepted 25 November 2019 Available online 27 November 2019 0162-0134/ © 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/). G. Sciortino, et al. Journal of Inorganic Biochemistry 204 (2020) 110953 several research groups. However, the interpretation of these spectra is such as CAM-B3LYP and M06-2X overestimate these energies [55]; the not a trivial task since the spectroscopic behavior of a metal compound best performance was obtained using hybrid functionals with the B3 is influenced by various factors – such as the specific donors bound to exchange part independently of the correlation part (for example, the metal ion, the geometry and symmetry of the species formed – and B3LYP and B3PW91) [55]. the calculated properties are greatly dependent on the applied theore- The calculation of the electronic absorption spectra of Cu(II) (both tical methods (i.e. functional and basis set for DFT) [22–30]. Therefore, for d-d transitions and ligand to metal charge transfers) and Zn(II) finding robust and suitable methods to calculate accurately the spec- complexes (only for ligand to metal charge transfers) through 41 pure troscopic parameters remains a great challenge for the chemists' com- GGA, hybrid GGA, pure meta-GGA and hybrid meta-GGA functionals munity. indicated that the hybrid approaches perform better than the others, Copper, which is one of the most abundant transition metal ions in with B1LYP giving the most accurate results [56]. In a recent publica- living organisms, has a crucial role in several biological processes. tion, we investigated the electronic absorption spectra of square planar Copper containing metalloenzymes are involved in oxygenation reac- nickel(II) complexes using TD-DFT methods [57]. It was shown that the tions and oxygen transport [31–34], and in electron transfer reactions functionals with 25% HF exchange (HSE06, MPW1PW91, PBE0) per- [35,36]. Moreover, the role of copper in neurodegenerative diseases is formed better than the other ones; it was also demonstrated that the also extensively examined [37,38]. In all cases, copper interacts with effect of the basis set on the calculated spectra is weaker than the effect the amino acid residues of a protein, although the coordination en- of the functional and the use of triple-ζ type def2-TZVP set is enough to vironment and geometry around the metal center may significantly obtain results in agreement with the experiment [57]. differ. Consequently, the metal–peptide complexes are excellent choices In this work, a systematic study on the TD-DFT prediction of λmax in for mimicking the active site of metalloenzymes and metalloproteins the visible region for several Cu(II) complexes is discussed. In the first and, for this reason, these systems are thoroughly studied [39,40]. In section, a benchmark of eleven species will be considered and the addition to the biological species, inorganic copper complexes have performance of twelve functionals compared. In the second and third been used as catalysts and several copper compounds showed antic- sections, the number of experimental and expected transitions and their ancer activity [41,42]. relation with the metal complex geometry will be analyzed and the Three oxidation states are characteristic for copper: +1 (config- effect of the weak coordination of axial water(s) evaluated; in the two uration 3d10), +2 (3d9) and +3 (3d8). Among those, +2 state is the final sections, the best functional (BHandHLYP) will be used to calcu- most stable in biological systems – even if specific ligands are able to late λmax for the binding of Cu(II) ion to the N-terminal region of human stabilize the +1 and +3 oxidation states [43,44] – and we will focus serum albumin (HSA) and to the regions 94-97 and 108-112 of prion here on copper(II) species. In general, Cu(II) prefers tetragonally dis- protein (PrP). torted octahedral geometries, even if it exhibits non-rigid structures such as compressed and elongated octahedral, tetra- and penta-co- 2. Experimental and computational details ordinated geometries, which are accompanied by Jahn-Teller effect [45]. Often, this behavior is designed “plasticity”. 2.1. Materials The complexation of copper(II) can be easily studied by UV-Vis spectroscopy. In water, copper(II) exists as [Cu(H2O)6]2+ ion, which All of the investigated ligands (GGG = Gly-Gly-Gly, GGGG = Gly- exhibits three electronic transitions that collapse into a single absorp- Gly-Gly-Gly, GGH = Gly-Gly-His, MKHM = Met-Lys-His-Met, tion band. The replacement of the coordinated water molecules by GTHS = Gly-Thr-His-Ser, trien = triethylenetetraamine, salen = N,N′- stronger donors shifts the absorption maxima (λmax) to higher energies, bis(salicylidene)ethylenediamine, bipy = 2,2′-bipyridine) and the salt and the value and molar absorptivity of λmax significantly depend on precursor of Cu(II) ion, CuSO4·5H2O, were purchased from Bachem, the nature of the coordinated atoms. Billo before and Sigel and Martin Reanal, AG or Sigma-Aldrich and used without further purification. subsequently developed a general rule for estimating the value of λmax Human serum albumin was a Sigma-Aldrich product (code A9511; for simple copper(II) species and, particularly, for copper(II)–peptide molecular mass of 66 kDa). complexes [46,47]. The empirical equation is based on the interpola- tion of a large number of Cu(II) electronic spectra (eq. 1) [47]: 2.2. Spectroscopic methods 103 UV-visible spectra of the Cu(II) complexes were recorded from 200 max = nm 0.294p(H2 O/CO) + 0.346q(COO ) + 0.434r(imide N) to 1000 nm on a PerkinElmer Lambda 25 or an Agilent Technologies + 0.460s(NH2) + 0.494t(peptide N ) (1) Cary 8454 UV-Vis diode array spectrophotometer. – – In Eq. (1), H2O, CO, COO , imide-N, NH2 and peptide-N denote the 2.3. Density functional theory (DFT) and time-dependent density functional type of equatorial coordinating donors, while p, q, r, s, t indicate the theory (TD-DFT) calculations number of these donors involved in the equatorial binding. In the presence of axial ligands, the estimated values of λmax through Eq. (1) The geometries of all the complexes in the benchmark were opti- can significantly differ from those experimentally observed [48]. mized through Gaussian 09 (rev. D01) software [58] at DFT level of The simulation of the electronic absorption spectra using TD-DFT theory, using the hybrid Becke three-parameter B3P86 functional, was frequently discussed and a number of reviews are available in the which is often used because of its high degree of accuracy for structural literature [24,49–52]. For the TD-DFT prediction of an electronic ab- prediction of transition metal species [59,60], combined with the triple- sorption spectrum, it is necessary to choose an appropriate combination ζ def2-TZVP basis set. The solvent effect was taken into account of functional and basis set. The effect of solvation as specific correction adopting the Polarizable Continuum Model (PCM) for water [61,62]. for the excited states can also be considered and several comprehensive The adducts formed upon binding of Cu(II) ion to the region 1-5 of studies and reviews were published [24,26,53,54]. At this time, the human serum albumin and to the regions 94-97 and 108-112 of prion literature data suggest that, for transition metal complexes, it is not protein were optimized with the functional B3LYP-D3, and the basis set possible to find a general computational condition to get a good 6-311g(d,p) for main group elements and SDD[ECP] plus f-polarization agreement between an experimental and a calculated spectrum within functions for Cu. the framework of TD-DFT approach. An investigation on four Ir(III) and The electronic transitions were calculated on the geometries opti- seven Pt(II) complexes has shown that local functionals (GGA and meta- mized for the ground electronic state at TD-DFT level of theory, with GGA) underestimate the excitation energies, whereas other functionals PCM for water. Twelve functionals were tested. Among them, pure, 2 G. Sciortino, et al. Journal of Inorganic Biochemistry 204 (2020) 110953 generalized gradient approximations (GGA) and meta GGA functionals: the functional and using the basis set def2-TZVP. For each spectrum the BLYP [63,64], TPSSh [65,66], M06 [67], M06-2X [67], B1LYP [64,68], visible range (400–800 nm) was taken into account because the d-d B3LYP [64,69], B3P86 [69–71] CAM-B3LYP [72], ω-B97x-D [73], transitions between the copper orbitals fall in this region. MPW1PW91 [74], HSE06 [75], and BHandHLYP [58]. The basis set was The number of d-d transitions is strongly influenced by the geometry def2-TZVP for benchmark and case studies. The predicted electronic and degree of distortion of the copper complexes. Cu(II) species, having spectra were generated using Gabedit software [76], while the mole- a degenerate d9 configuration in an octahedral crystal field, undergo cular orbitals (MOs) involved in the transitions identified via the AOMix Jahn-Teller effect and are characterized by elongated or compressed package (vers. 6.52) [77] and simulated performing a Mulliken popu- octahedral, square pyramidal or square planar structures, close to D4h lation analysis (MPA) with Gaussian 09 at the same level of theory used symmetry. In the analysis of the spectra, when only one transition is for the optimization. predicted, it can directly be compared to the experimental λmax value. When the number of excitations is higher than one, the spectrum gen- 2.4. Statistical analysis erated by the superimposition of the corresponding bands is compared to the experimental one. In this work, the spectra were generated with The statistical dispersion of the calculated values of λmax (λmaxcalcd) Gabedit software [76] using a Gaussian shape. from the experimental ones (λmaxexptl) for the jth complex of the The performance of the functionals was assessed using MAPD (Eq. benchmark is defined in terms of percent deviation (PD) and absolute (2)) and SD. The values of MAPD obtained for the eleven Cu(II) com- percent deviation (APD). However, in the analysis of a large dataset it is plexes are summarized in Fig 2. From an analysis of the data, it emerges necessary to refer to a mean absolute percent deviation (MAPD) [78], that the best performance is reached with the functional BHandHLYP that was proposed previously as a criterion of quality [79,80]: (50% HF exchange) and M06 global hybrid functional (27% HF ex- N change); their MAPDs are 3.1% and 3.7%, while the SD's are 2.3% and calcd exptl 1 max (j) max (j) 3.7%, respectively. These functionals are followed by the long-range- MAPD = exptl × 100 N j=i max (j) (2) corrected CAM-B3LYP (short range HF exchange 19%, long range HF exchange 65%; MAPD = 9.7% and SD = 5.4%) and by MPW1PW91 where N is the number of compounds in the dataset. The mean percent (25% HF exchange; MAPD = 12.0% and SD = 5.5%) and B1LYP (25% deviation is denoted with MPD. Beside MAPD, the standard deviation HF exchange; MAPD = 12.4% and SD = 6.1%). All the other func- (SD), related to the data dispersion, is also reported. tionals tested give worse predictions and are not recommended to calculate an electronic absorption spectrum of a Cu(II) species. 3. Results and discussion The hybrid GGA BHandHLYP is a widely used functional, including 50% of HF and mixed LSDA/B88 exchange plus LYP correlation, par- 3.1. Validation: optimization of the structures, and analysis of the spectra ticularly appropriate to describe hydrogen bonds, potential energy and benchmark data surfaces, transition states, excitation energies, and oscillator strengths with high quality results, comparable as other post-HF methods Eleven Cu(II) complexes with various ligands L were studied: [Cu [81,82]. Its potential in predicting the electronic spectra of transition (H–2GGG)]–, [Cu(H–3GGGG)]2–, [Cu(H–2GGH)]–, [Cu(H–2MKHM)]+, metal compounds were recently discussed for 'bare' V(IV) species [Cu(H–2MKHM)]–, [Cu(H–2GTHS)]–, [Cu(trien)]2+, [Cu(salen)], [Cu [83,84]. The top performances reached by the meta hybrid-GGA M06 (Gly)2(H2O)], [Cu(bipy)2]2+, [Cu(bipy)3]2+ and [Cu(H–4βAla-Gly- functional are particularly interesting considering its quite low cap- βAla-Gly)]2–. The notation H–xL indicates the dissociation of groups (in ability of predicting the UV-vis spectra of Ni(II) [57] or EPR parameters this case the amide bond of oligopeptides) that do not undergo depro- of Cu(II) compounds [13], and the general low accuracy observed for tonation in the absence of Cu(II) binding. The comparison between the functionals with a large number of empirical parameters in the calcu- calculated and experimental bond lengths and angles for some selected lation of the electronic density [85]. complexes is summarized in Table S1 of the Supplementary Material. As Considering MPD, the difference between the experimental and an example, Fig. 1 shows the overlap between the optimized geometries predicted λmax values is ~0.0% and 0.2% when M06 and BHandHLYP (in blue) and the XRD structures (in orange) of [Cu(bipy)2]2+ and [Cu are used, respectively. The use of the other functionals leads to an (H–4βAla-Gly-βAla-Gly)]2–: the agreement is very satisfactory and this is underestimation of λmax, from −7.5% (BLYP) to −9.3% (TPSSh). The obviously a good starting point to calculate accurately the electronic only exception is obtained with M06-2X for which the difference is absorption spectra. The Cartesian coordinates of the optimized minima +15.9%. It is noticeable that the functional B1LYP, considered the best are available in Tables S2–S12 of the Supplementary material. by Holland and Green [56], is outperformed by several functionals, and To ascertain the best computational protocol, the electronic ab- BHandHLYP, M06 and CAM-B3LYP work significantly better than it. sorption spectra of the eleven Cu(II) complexes were calculated varying Fig. 1. Comparison of the calculated (blue) and XRD experimental (orange) structures for (a) [Cu(bipy)2]2+ and (b) [Cu(H–4βAla-Gly-βAla-Gly)]2–. 3 G. Sciortino, et al. Journal of Inorganic Biochemistry 204 (2020) 110953 Fig. 2. (a) Mean absolute percent deviation (MAPD) and (b) standard deviation (SD) from the experimental values of λmax determined with the twelve functionals on eleven Cu(II) complexes included in the dataset. The comparison between the experimental spectrum of [Cu non-rigid structures including several distorted geometries (phenom- (bipy)2]2+ and those calculated with various functionals is shown in enon known as 'plasticity') [86,87]. Species with coordination numbers Fig. 3. Looking at this figure, the functionals can be divided into three 4, 5 and 6, and geometries square planar, square pyramidal, bipyr- groups: one containing BHandHLYP and M06, another containing the amidal trigonal, octahedral compressed and elongated, with all the functional with intermediate performance such CAM-B3LYP, B1LYP, possible distortions, have been reported [88]. The distortion degree B3LYP and B3P86, and the last group with the worse functional TPSSh. determines the number of absorptions in the visible region. For hexa- coordinated tetragonal structures, three transitions are expected from 3.2. Applications: correlation between geometry and type of spectrum symmetry considerations, that collapses into a single experimental band if the distortion is small; the absorption becomes sharper and shifts to Due to the non-spherical symmetry and Jahn-Teller effect expected higher energy values with increasing the donor strength [89]. One ex- for a d9 ion, the stereochemistry of Cu(II) complexes is characterized by perimental absorption is predicted for trigonal bipyramidal complexes, 4 G. Sciortino, et al. Journal of Inorganic Biochemistry 204 (2020) 110953 Fig. 3. Comparison of the experimental spectrum of [Cu(bipy)2]2+ and the spectra calculated with BHandHLYP, M06, B1LYP, CAM-B3LYP, B3P86, B3LYP, and TPSSh functionals. although the number of electronic transitions expected on the basis of coordinated structure two bands in the case of a regular trigonal bi- ligand field theory is larger than those detected in the spectrum pyramidal arrangement, and three bands in the case of a distortion [88,89]. Theory also predicts one experimental band for tetrahedral toward the square pyramid but at higher wavelengths, are expected species with small distortion [88,89]. Therefore, in contrast with other [95]. The calculated transitions are listed in Table 1. metal ions – for example oxidovanadium(IV) for which all the three or Another example is the spectrum of [Cu(H−2GGG)]− (Fig. 4b). It is four d-d excitations are usually detected [90,91] – , for copper(II) the more symmetric than the one of [Cu(bipy)2]2+, suggesting a less dis- number of electronic transitions expected from symmetry considera- torted geometry. The absorption maximum at 553 nm indicates a tions is larger than those experimentally detected in the spectrum. square planar or a very elongated octahedral geometry. The calcula- Therefore, it is not easy to determine the exact number of excitations tions allow us to determine the transitions from the MOs based on Cu- below the broad absorptions and relate the experimental spectrum with dxy and Cu-dz2 orbitals to Cu-dx2-y2, with comparable intensity, ac- the molecular structure of complexes. Computational methods may counting for the shape of the experimental band. The predicted beha- help to do this and interpret correctly a spectral signal. In the following vior is in agreement, in this case too, with the ligand field theory de- paragraphs two examples will be discussed. scription of the d orbital energy order for a square planar geometry In Fig. 4, the experimental spectra of [Cu(bipy)2]2+ and [Cu [92]. The absence of a third excitation in the visible region induces to (H–2GGG)]– are given. The spectrum of [Cu(bipy)2]2+ is characterized exclude a rhombic distortion, which would remove the degeneration of by a broad band centered at 730 nm (Fig. 4a). This suggests a tetra- the Cu-dxz and Cu-dyz orbitals, causing an increase of the transition hedral arrangement. The computational data indicate that three bands number. Overall, for [Cu(H−2GGG)]−, the results indicate that the with different intensity are expected in the range 670–720 nm and this geometry is almost regular, in line with the predicted structure with accounts for the large linewidth and asymmetry of the band, suggesting copper(II) ion in an almost perfect plane formed by the four donors, i.e. a distortion of the structure toward the square planar arrangement amino-NH2, amide-N−, amide-N−, and carboxylate-O−. which causes the splitting of the e and t2 orbitals of a tetrahedron. The predicted band at 716 nm is composed by three d-d transitions at – in increasing energy order – 716.8, 698.3 and 670.7 nm, from MOs with 3.3. Applications: determination of the coordination of axial water prevalent Cu-dxy/xz, Cu-dz2 and Cu-dxy/yz character to that based on Cu- dx2-y2. This order follows the correlation diagram for the transformation Due to the 'plasticity' of Cu(II) ion and its non-rigid stereochemistry of a regular tetrahedral to a square planar geometry, for which the [86,87], the coordination of axial water(s) is possible for a complex metal energy order is: Cu-dxy < Cu-dz2 < Cu-dxz ~ Cu-dyz < Cu-dx2-y2 with four strong equatorial donors. For a system with two equatorial [92]. This analysis also agrees with the X-ray structure of [Cu(bipy)2]2+ bidentate L or one tetradentate L’ ligand and a monodentate X ligand (X (ref. [93] and Fig. 1a), for which it has been proposed that the steric can be a halide ion, a polyatomic anion such as ClO4–, NO3–, NCS–, etc., hindrance of hydrogens in 3,3′ position precludes the coplanar ar- or a solvent molecule), the stoichiometry may vary from CuL2 to rangement of the two bipy molecules [94]. In contrast, for a penta- CuL2X/CuL2X2 and from CuL′ to CuL′X/CuL′X2, respectively. For ex- ample, with amino-N donors such as ethylenediamine (en) and trien, Fig. 4. Comparison between the experimental (in black) and calculated (in red) spectra of: (a) [Cu(bipy)2]2+ and (b) [Cu(H–2GGG)]–. The predicted transitions with the corresponding intensity are also shown. 5 G. Sciortino, et al. Journal of Inorganic Biochemistry 204 (2020) 110953 Table 1 Calculated and experimental transitions (λmax) for some Cu(II) complexes of the benchmark.a Species Transition (% weight) Main characterb,c λmaxcalcdd f (×105)e λmaxexptl (εmaxexptl)d,f [Cu(bipy)2]2+ I (23.8) Cu-dxy/yz (45.1) → Cu-dx2-y2 (16.9) 716.8 80 730 (90) II (20.3) Cu-dz2 (47.6) → Cu-dx2-y2 (16.9) 698.3 40 III (15.4) Cu-dxy/xz (32.5) → Cu-dx2-y2 (16.9) 670.7 10 [Cu(H–2GGG)]– I (28.3) Cu-dxy (65.2) → Cu-dx2-y2 (25.8) 524.5 60 553 (150) II (25.0) Cu-dxy/dz2 (66.5) → Cu-dx2-y2 (25.8) 509.6 90 a Transitions calculated with BHandHLYP functional combined with the basis-set def2-TZVP. b The character of the orbital was assigned considering the largest contribution of the atomic orbitals to the specific MO. c Percent contribution of the Cu-d orbital to the MO. d λ values measured in nm. e Strength of the oscillator associated with the transition. f ε values measured in M−1 cm−1. [Cu(en)2](NO3)2, [Cu(en)2(H2O)2]SO4, [Cu(en)2(ClO4)2] and [Cu(trien) I]I are isolated in the solid state [96,97]. In aqueous solution, various species are formed by either retaining the solid phase composition, or through the replacement of the monodentate X ligand by water mole- cules to give [CuL2]2+, [CuL2(H2O)]2+ or [CuL2(H2O)2]2+, and [CuL′]2+, [CuL′(H2O)]2+ or [CuL′(H2O)2]2+. In solution, it is not straightforward to determine if water is bound to copper and, even- tually, how many molecules are coordinated to the metal ion since the effect of the axial ligands on the spectroscopic properties (λmax in an electronic spectrum or g and A in an EPR spectrum) is not easily pre- dictable. Obviously, an electronic absorption spectrum changes in the absence or presence of axial water(s), with the change depending on the number of water (one or two) and on the strength of the bond (i.e., the distance Cu–OH2). In these cases, TD-DFT methods can be useful to characterize the species in solution and prove if solvent coordination Fig. 6. The comparison of the experimental spectrum of [Cu(trien)]2+ (black) occurs. and the calculated spectra for [Cu(trien)]2+ (red) and [Cu(trien)(H2O)]2+ In this section, the effect of the coordination of an axial water ligand (blue). to [Cu(trien)]2+ and [Cu(Gly)2] is discussed. For the species with trien, initially the three possible structures in aqueous solution, [Cu (trien)]2+, [Cu(trien)(H2O)]2+ and [Cu(trien)(H2O)2]2+, were opti- ligand – observed in the solid state [96] – is lost in aqueous solution. mized. The results demonstrate that [Cu(trien)(H2O)2]2+ is not stable The large change in the calculated absorption wavelength of the and a water molecule is released from one of the two axial positions. monohydrate complex is due to the short Cu–OH2 distance expected for The optimized geometry of [Cu(trien)]2+ and [Cu(trien)(H2O)]2+ with the penta-coordinated species (2.277 Å, Fig. 5). the corresponding bond lengths is reported in Fig. 5. Subsequently, the An analogous approach was applied for the bis-chelated complex of electronic spectra of [Cu(trien)]2+ and [Cu(trien)(H2O)]2+ were cal- glycinate: the species [Cu(Gly)2] and [Cu(Gly)2(H2O)] – this latter ex- culated using the best computational conditions, i.e. the functional isting in the solid state [98–100] – were optimized through a DFT si- BHandHLYP and the basis set def2-TZVP, and compared to the experi- mulation. The calculations give a λmaxcalcd of 616 nm for [Cu(Gly)2] and mental one. It is easy to notice that the experimental spectrum with 621 nm for [Cu(Gly)2(H2O)], while the experimental value is 628 nm λmaxexptl at 582 nm is well reproduced for [Cu(trien)]2+ (PD = 1.9% and 1.1%, respectively). Therefore, the data suggest that (λmaxcalcd = 558 nm, PD = −4.1%) but not by [Cu(trien)(H2O)]2+ the penta-coordinated structure is retained in solution. The small (λmaxcalcd = 644 nm, PD = 10.7%); the comparison is shown in Fig. 6. change in the absorption maximum going from [Cu(Gly)2] to [Cu This indicates that [Cu(trien)]2+ is square planar in water and the axial Fig. 5. Optimized structure in aqueous solution of: (a) [Cu(trien)]2+ and (b) [Cu(trien)(H2O)]2+. The distances of the Cu–N and Cu–O bonds are reported in Å. 6 G. Sciortino, et al. Journal of Inorganic Biochemistry 204 (2020) 110953 (Gly)2(H2O)] is due to the long Cu–OH2 distance (2.376 Å experimental 3.5. Applications: calculation of the spectrum of Cu(II)–PrP adducts [98], and 2.434 Å calculated). Prion proteins (PrP) are cellular proteins that undergo a misfolding 3.4. Applications: calculation of the spectrum of the Cu(II)–HSA adduct in the C-terminal region (128-231) to scrapie form (PrPSc). In this latter form, the α-helical folded PrP gives β-sheet and generates aggregates Human serum albumin is involved in the transport of various metal [108]. The misfolding is related to several diseases known as trans- ions such as Ni(II) [101], Zn(II) [102,103] and Cu(II) [104]. Two metal missible spongiform encephalopathies, which include bovine spongi- binding sites exist in its structure: the ATCUN (Amino Terminal Copper form encephalopathy in cattle, scrapie in sheep and goat and Creutz- and Nickel) or site I in the N-terminal region that binds Cu(II) and Ni(II) feldt-Jakob disease in humans [109,110]. through the donor set NH2, N–, N–, His3-N [104], and the multi-metal Prion proteins bind several Cu(II) ions [111,112]: four ions in the binding site (MBS) or site II to which Zn(II) and V(IV)O are bound ‘octarepeat’ region 60-91 based on PHGGGWGQ unit [113,114], two through His67, Asn99, His247 and Asp249 residues [105,106]. The ions in the region 92-111 [107,115,116] and one additional ion in that coordination of His3 in the fourth equatorial position plays a funda- 180-193 [117]. It has been proposed that copper binding in the non- mental role and promotes the deprotonation of amides of Ala2 and His3 octarepeat regions may be related to the PrP misfolding [107,117–119]. to yield a distorted square planar geometry. Bovine serum albumin In the binding between Cu(II) and PrP, the interaction with histidine (BSA) and rat serum albumin (RSA) behave in the same way. In con- residues (His61, His69, His77, His85 in 'octarepeat' and His96, His111, trast, albumin of other animals such as dog serum albumin (DSA) and His187 in the non 'octarepeat' regions) plays the key role of anchoring chicken serum albumin (CSA), where His3 is replaced by Tyr3 (DSA) or donors. Glu3 (CSA), does not bind Cu(II) through the ATCUN site [104]. The In this study, two sites were considered with the aim to calculate the electronic spectrum of HSA is characterized by a broad band centred at electronic absorption spectrum: that containing the amino acids 94-97 529 nm (Fig. 7); the λmaxexptl is perfectly in agreement with that esti- modeled by the tetrapeptide Ac–GTHS–NHCH3, and that 108-112, mated by Eq. (1) for a (NH2, N−, N−, His3-N) coordination. modeled by the pentapeptide Ac–NMKHM–NHCH3. Exploiting the results of this work, we calculated the electronic The interaction of Cu(II) ion with Ac–GTHS–NHCH3 can be de- absorption spectrum of the model complex containing the first five scribed through the coordination of His96 that favors the deprotonation amino acids of human serum albumin (DAHKS–NHCH3), a model which of the amide groups of His96, Thr95 and Gly94 to give (His96-N, N−, was already successfully used to simulate the EPR spectrum of Cu N−, N−) donor set. The optimized structure is reported in Fig. 9 and the (II)–HSA adduct [13]. The Cartesian coordinates of this adduct are re- Cartesian coordinates in Table S14 of the Supplementary Material. The ported in Table S13 of the Supplementary Material. The optimized spectrum was simulated with BHandHLYP functional and basis set def2- geometry is shown in Fig. 7a and is characterized by a square planar TZVP. The experimental and the calculated maxima are at 555 nm and arrangement of the four equatorial donors with a slight distortion of the 585 nm, respectively, with a PD of 5.4%, in line with the result found equatorial plane. The experimental and calculated spectra are com- with the model of HSA (Table 2). pared in Fig. 7b. The agreement is rather good and the calculated value In the system involving Cu(II) and fragment 108-112, two species of λmax at 552 nm deviates only 4.3% from the experimental value of are detected at pH 7.4: one of them is the adduct with (N−, N−, N−, 529 nm (see Table 2). The predicted spectrum is broad due to the four His111-N) coordination [107,120,121], while for the second one two transitions expected at 568.7 nm (oscillator strength f × 105 = 50), possible donor sets were proposed, (Met109-S, N−, N−, His111-N) 555.3 nm (f × 105 = 10), 545.8 nm (f × 105 = 20) and 526.7 nm [107] and (CO, N−, N−, His111-N) [120,121]; in both cases N−-s are (f × 105 = 20). The large number of transitions compared to the sys- the deprotonated backbone peptide nitrogens of Lys110 and His111. tems with high symmetry is due to the distortion of the equatorial plane The two possibilities are given in Fig. 10. The Cartesian coordinates for of the metal ion. The intense absorptions below 450 nm are assigned as these three adducts can be found in Tables S15-S17 of the Supple- metal to ligand or ligand to metal charge transfers (MLCT and LMCT). mentary Material. The main d-d character of the absorptions in the range 500–600 nm The value of λmaxcalcd for (N−, N−, N−, His111-N) coordination is has been ascertained from the analysis of the vertical transitions and very close to λmaxexptl (555 nm vs. 550 nm with a PD of only 0.9%, the MOs involved in the transitions (Table 3). It must be highlighted Table 2). This allowed us to confirm the presence of this adduct in that single-electron excitations originate from occupied MOs with metal aqueous solution. Concerning the second species, two different calcu- character, lower in energy compared to the HOMO, to the LUMO orbital lations were carried out on the optimized structures with (Met109-S, (which is the orbital Cu-dx2-y2, bearing the unpaired electron). The MOs N−, N−, His111-N; Fig. 10a) and (CO, N−, N−, His111-N; Fig. 10b) involved in the most relevant transitions are depicted in Fig. 8. coordination. The values of λmaxcalcd are 653 and 627 nm, respectively, Fig. 7. (a) Optimized structure of the ad- duct formed by Cu(II) ion with the penta- peptide DAHKS–NHCH3 (region 1–5 of HSA or site I). Hydrogen atoms are omitted for clarity. Adapted from ref. [13]; (b) com- parison between the experimental spectrum of the Cu(II)–HSA system (Cu(II)/HSA 1/1, HSA 0.75 mM, black) and the calculated spectrum for the binding of Cu(II) ion to the model DAHKS–NHCH3 (red). The four pre- dicted transitions with the corresponding intensity are also shown. 7 G. Sciortino, et al. Journal of Inorganic Biochemistry 204 (2020) 110953 Table 2 Experimental and TD-DFT calculated λmax for the interaction of Cu(II) with regions 1–5 of human serum albumin, and 94–97 and 108–112 of prion protein.a Protein Region Model Coordination λmaxcalcd λmaxexptl PD − − b b HSA 1–5 DAHKS–NHCH3 NH2, N , N , His3-N 552 529 4.3 PrP 94–97 Ac–GTHS–NHCH3 His96-N, N−, N−, N− 585b 555b 5.4 PrP 108–112 Ac–NMKHM–NHCH3 His111-N, N−, N−, Met109-S 653c 610c 7.0 PrP 108–112 Ac–NMKHM–NHCH3 His111-N, N−, N−, CO 627c 610c 2.8 PrP 108–112 Ac–NMKHM–NHCH3 His111-N, N−, N−, N− 555c 550c 0.9 a Value of λmaxcalcd (in nm) calculated with BHandHLYP functional combined with the basis set def2-TZVP. b This study. c Data taken from ref. [107]. Table 3 Calculated and experimental transitions (λmax) for the adduct formed upon the interaction of Cu(II) ion with region 1-5 of human serum albumin.a Transition (% weight) Main characterb,c λcalcd d f (×105)e λexptl (εexptl)d,f I (39.4) Cu-dyz/xy (73.9) → Cu-dx2-y2 (43.6) 568.7 50 529 (130) II (29.6) Cu-dxz (24.3) → Cu-dx2-y2 (43.6) 555.3 10 III (40.9) Cu-dxz (64.2) → Cu-dx2-y2 (43.6) 545.8 20 IV (32.4) Cu-dxy (30.8) → Cu-dx2-y2 (43.6) 526.7 20 a Transitions calculated with BHandHLYP functional and def2-TZVP basis-set. b The character of the orbital was assigned considering the largest contribution of the atomic orbitals to the specific MO. c Percent contribution of the Cu-d orbital to the MO. d λ values measured in nm. e Strength of the oscillator associated with the transition. f ε values in M–1 cm–1. Fig. 8. Graphical representation of the MOs involved in the most relevant TD-DFT cal- culated transitions (λmax) for the adduct of Cu(II) ion with region 1-5 of human serum albumin. The level of theory B3LYP-D3 combined with 6-311g(d,p) for main group elements and SDD plus f-polarization func- tions and pseudopotential for Cu was used. and must be compared to λmaxexptl of 610 nm. The better agreement was 4. Conclusions obtained with the donor set (CO, N−, N−, His111-N) and this suggests that the binding to CO of the backbone instead of Met109-S is more The results presented in this study confirm and offer a new evidence likely (Table 2). Taking into account that the three Cu–N distances are of the potential of computational techniques in bioinorganic chemistry. very similar, in the range 1.917–1.993 Å for (Met109-S, N−, N−, In particular for copper, an element with many biological and phar- His111-N) and 1.928–1.975 Å for (CO, N−, N−, His111-N) species, the macological properties, both EPR spectra [13] and now electronic ab- main difference of the two structures is the length of the Cu–O bond sorption spectra can be successfully predicted. Using B3LYP functional (2.102 Å), compared to Cu–S (2.541 Å), that determines the lower for EPR and BHandHLYP for electronic spectra, Az and λmax are pre- wavelength maximum in the predicted electronic spectrum. dicted with MAPD of 8.6% and 3.1%, respectively. It is noteworthy 8 G. Sciortino, et al. Journal of Inorganic Biochemistry 204 (2020) 110953 mainly, functional) which gives the best agreement with the experi- mental data. In this situation, the computational procedure must be validated using a benchmark which includes as many as possible metal complexes with different geometries, coordination numbers and electric charges. The results of this manuscript suggest that functionals BHandHLYP and M06 perform much better than HSE06 and MPW1PW91 in the case of Cu(II); in contrast, with square planar Ni(II) complexes, HSE06 and MPW1PW91 are the best, while BHandHLYP and M06 give worse predictions [57]. This effect can be explained by considering the fact that the open shell systems, such as Cu(II) or V(IV) O complexes, are quite sensitive to the amount of Hartree-Fock ex- change included in the functional, as already reported earlier [122]. Similar results were obtained for the prediction of hyperfine coupling constant in the EPR spectra. For example, for vanadium in the oxidation state +4, it was shown that the functional BHandHLYP is re- commended for oxidovanadium(IV) complexes [11], while for ‘bare’ non-oxidovanadium(IV) species the double hybrid B2PLYP functional must be used [12]. As pointed out in a number of papers, the effect of the basis set is less important than the functional, and a triple-ζ po- larized (for example, def2-TZVP) is enough to reach good predictions. It Fig. 9. Optimized structure of the adduct formed between Cu(II) ion and tet- rapeptide Ac–GTHS–NHCH3 (region 94-97 of PrP). needs to be emphasized that, in this study, the functionals BHandHLYP and M06 outperformed B1LYP, which gave the best results for a limited number of Cu(II) species [56]. Accordingly, the latter one is not re- that, for Cu(II) complexes, the prediction of the optical spectra is better commended if an accurate prediction is desired: specifically, the value than that of electron paramagnetic resonance spectra, a finding which is of MAPD is 3.1% and 3.7% with BHandHLYP and M06, respectively, in contrast with results for other metal ions such as V(IV) [11,12]. Thus, and as high as 12.4% with B1LYP. the assessment that NMR and EPR spectra can be calculated success- Finally, it must be highlighted that the procedure validated in this fully, while the prediction of optical spectra is possible only qualita- paper can be applied to predict the transitions and the electronic ab- tively for metal complexes, must be reconsidered. In addition to the sorption spectra of Cu(II)–bioligand adducts. The results could be useful results presented here, we have recently demonstrated that the ab- to confirm the geometry of a hypothesized adduct through the com- sorption spectra of square planar Ni(II) species can be predicted with a parison between the experimental and calculated spectra and, in gen- MAPD of 1.5% in the visible region using HSE06 and MPW1PW91 eral, to relate the experimental spectral data to a specific structure of a functionals [57]. metallospecies. Up today, there are no rules to determine the protocol (basis set and, Fig. 10. Optimized structures of the adduct formed between Cu(II) and pentapeptide Ac–NMKHM–NHCH3 (region 108–112 of PrP): (a) coordination (Met109-S, N−, N−, His111-N) and (b) coordination (CO, N−, N−, His111-N). Hydrogen atoms are omitted for clarity. The level of theory B3LYP-D3 combined with 6-311g(d,p) for main group elements and SDD plus f-polarization functions and pseudopotential for Cu was used. 9 G. Sciortino, et al. Journal of Inorganic Biochemistry 204 (2020) 110953 Declaration of competing interests [32] K.A. Magnus, H. Ton-That, J.E. Carpenter, Chem. Rev. 94 (1994) 727–735. [33] H. Decker, N. Terwilliger, J. Exp. Biol. 203 (2000) 1777–1782. [34] E.I. Solomon, P. Chen, M. Metz, S.-K. Lee, A.E. Palmer, Angew. Chem., Int. Ed. 40 The authors declare that they have no known competing financial (2001) 4570–4590. interests or personal relationships that could have appeared to influ- [35] A.G. Sykes, Chem. Soc. Rev. 14 (1985) 283–315. ence the work reported in this paper. [36] H.B. 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