Computational Methods for Metal Sulfide Clusters - ACS Publications

Chapter 7 Computational Methods for Clusters

Metal

Sulfide

Downloaded by STANFORD UNIV GREEN LIBR on October 7, 2012 | http://pubs.acs.org Publication Date: November 29, 1996 | doi: 10.1021/bk-1996-0653.ch007

Ian Dance School of Chemistry, University of New South Wales, Sydney 2052, Australia The applicability of contemporary techniques in computational chemistry for large molecules containing metal and sulfur atoms is considered, with emphasis on density functional (DF) and force-field methods. Non-local density functional methodology has been evaluated for three different metal sulfide clusters and shown to yield accurate geometries by optimization of the total electronic energy. This method is then applied to calculation of the structures (and related reactivities) of new copper sulfide clusters [Cu S ]- for which the available experimental data comes from the gas phase. DF calculations applied to metallocarbohedrenes inspired postulation of a mechanism for the binding and reduction of N at theFe7MoS9cluster of the nitrogenase active site. The N is bound to an Fe4 face, and the N-N bond weakened by torsion of the cluster. The pathway for protonation of the reducing N , and the egress of the reduction products, are explained in this concerted mechanism, which involves the surrounding protein and is supported by DF calculations. Force -field calculations are used to model the molecular biomineral with composition Cd80S62{(γ-glu-cys)3gly} which is formed when yeasts are grown with a burden of Cd +. x

y

2

2

2

2

22

The progress we make in understanding the chemistry of metal-sulfur compounds depends on the perspectives we take and the questions we ask. In this account, in which computations are the investigative tool, I adopt two perspectives on metal sulfide clusters. Most molecular metal sulfide clusters contain the metal and sulfur atoms in a core structure, surrounded by terminating ligands, which may be elaborated sulfur (i.e., thiolate) or heteroligands. One perspective strips away the terminating ligands, and asks fundamental questions about the metal-sulfur core of the cluster, and its existence, stability, and structure in the absence of the coating of ligands. The other perspective focuses on the coating and the environment, and enquires about the influences of the environment on the properties of the molecular cluster. This is the domain of supramolecular inorganic chemistry ( 1,2) The significance of both of these approaches is illustrated by the Fe-Mo-S cluster at the active site of nitrogenase (3-11). This Fe7MoS9 cluster (described further below) has a remarkable structure, unprecedented amongst the plethora of metal sulfide molecules synthesised in mimicry, and in comparison with the standard clusters is remarkably underligated with connections to the protein by only two amino 0097-6156/96/0653-0135$15.00/0 © 1996 American Chemical Society In Transition Metal Sulfur Chemistry; Stiefel, E., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1996.

136

TRANSITION METAL SULFUR CHEMISTRY


acids at two of the eight metal atoms. Further, for this Fe7MoS9 cluster to perform its remarkable function of catalyzing the reduction of triply-bonded N 2 to N H 3 under ambient conditions there is strong dependence on the protein environment. Thus the core of the cluster is distinctive and the environment essential, and the two research perspectives are demonstrated. The mechanism of action at the active site of nitrogenase has been partly revealed by computational methods, as explained below. Questions about unligated cluster cores, and about environmental influences, are not so readily approached experimentally (except where the environment is a crystal lattice). One technique allowing experimental access to metal sulfide cores is gas phase synthesis in the cooling energized plume formed by laser ablation of solids. By coupling this synthesis with Fourier transform ion-cyclotron resonance mass spectrometry we have revealed the existence of many hundreds of metal sulfide clusters, and been able to describe the reactivities of some of them (12-18). More often than not the compositions of these binary metal sulfide molecules are unexpected and unprecedented. However, these experiments are performed under high vacuum conditions, and direct measurement of structure is not yet possible. Computational methods (i.e., theory in practice) in inorganic chemistry are now powerful and reliable, and can be used profitably in investigations of the questions just raised. Figure 1 shows the principal methods and their features and relationships. In compounds where the bonds and stereochemistry are well defined, mechanical models and force-field methods are most applicable (79-22), particularly where the atoms are numerous. Where the bonding is unconventional, uncertain, or variable, calculations of electronic structure through the molecular orbitals are most suitable. In compounds where the bonding has a high degree of ionic character, electrostatic models are useful (23). Calculations of electronic structure are parametrized (semi-empirical) or ab initio. Conventional ab initio methods are the widely used Hartree-Fock (HF) calculation, preferably supplemented with a procedure such as configurational interaction (CI) to account for electron correlation, which is significant in inorganic molecules. The alternative to HF-CI is the density functional (DF) method in which the electron exchange and correlation are built in through the use of " functional ", which describe exchange and correlation as functions of electron density (24-36). There are various functional, derived from the properties of an electron gas, and corrections (known as gradient corrections, or non-local density functionals) that take account not only of the electron density but also its curvature. Finally, a promising development in computational inorganic chemistry involves the embedded cluster methodology (see Fig. 1), in which the core structures with unknown bonding are treated by electronic structure calculations while the surroundings (such as solvent, or protein) are treated at the same time by force-field methods. While unbiased calculations of electronic structure (and geometry optimization by minimization of electronic energy) are clearly desirable for inorganic molecules of all types, there is the practical issue of computational effort and demand for resources. This effort is roughly proportional to the number of orbitals (basis functions) raised to an exponent n: computational effort = (number of orbitals)

0

When DF methods are compared with HF-CI methods of comparable accuracy, it is generally found that the exponent η for DF is at least one integer less than η for HFCI. Therefore with density functional methods there is a saving of computational time/resources by a factor that is of the order of the number of orbitals, which for In Transition Metal Sulfur Chemistry; Stiefel, E., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1996.

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Computational Methods for Metal Sulfide Clusters

137

typical inorganic clusters could be of order 1000. Thus, with density functional methods it is possible to tackle big molecules with big (i.e., inorganic) atoms, containing significantly correlated electrons.


The accuracy of density functional methods for metal sulfide clusters Expediency must be accompanied by accuracy. What is the accuracy of DF methods for metal sulfide clusters? Accuracy can be assessed against various observables, each of which has an energy scale to be considered in the evaluation of the agreement between calculated and observed properties. By far the most widely available observable is molecular geometry, from diffraction analyses of crystals. Here the flatness of the geometry-energy hypersurface is a factor, which can be assessed experimentally by examining the variation of "equivalent" dimensions in the molecule, and if available, the variation of dimensions over symmetry-inequivalent molecules in the crystal, or molecules in different crystals. (The accuracy of molecular geometries from crystal structures is usually less than the quoted precision.) Another common observable for these clusters is spin state, which is often dependent on relatively small differences in the energies of orbitals that are neither strongly bonding or antibonding, and on energies as low as kT. In the following, the DF methodology is evaluated by its reproduction of observed geometry in selected compounds (37). Accurate reproduction of geometry is a prerequisite for accurate calculation of other properties. The implementation of DF methods in the program DMol was used (30, 38-40). Various local density functionals and non-local density functionals were tested, and the best results were obtained with Becke's 1988 version (41) of the gradient corrected exchange functional combined with the Lee-Yang-Parr (42) correlation functional which includes both local and non-local terms. This combination is labeled the "blyp" functional. The non-local corrections were applied after the self consistent field convergence. The basis sets are expressed numerically rather than analytically, and are generated by solution of the DF equations (for each element) with the same functionals as used for the complete cluster. The basis sets employed were double numerical, augmented with polarization functions (basis type DND in DMol). Core orbitals can be frozen without significant loss of accuracy. Clusters were evaluated in their even-electron charge state, with spin restricted calculations. The electronic state was the aufbau ground state. In molecules where there are closely spaced orbitals at the Fermi level or degenerate partially occupied orbitals, and thus the possibility of non-singlet spin states and low-lying excited states, the calculation of electronic structure was facilitated by a smearing of the occupancy of orbitals within about 0.1 eV at the Fermi level. This is equivalent to calculation of the average of the accessible states. The geometry optimization, by minimization of the total energy, was commenced with a geometry close to that observed. Tertiary phosphine and organo-thiolate ligands were simplified to P H 3 and SH, respectively.

2+

[Fe6S6(PEt3)6] . A significant structure type in FeS cluster chemistry is the "basket" isomer of [Fe6S6(PEt3)6] (43). Figure 2 shows the structure of [Fe6S6(PH3)6] as optimised in symmetry C2v> and defines the atom types and notation. The best results were obtained with the blyp functional, and are are compared in Table I with the observed distances in [Fe6S6(PEt3)6] . The calculated and observed structures are virtually superimposable, with agreement between the 2+

2+

2+

In Transition Metal Sulfur Chemistry; Stiefel, E., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1996.

138


MECHANICAL MODELS • force field methods

ELECTRONIC STRUCTURE • molecular orbitals • total electronic energy

ELECTROSTATIC MODELS for lattices with monatomic ions


1f EMBEDDED CLUSTER METHODS

AB INITIO first principles

1

SEMI-EMPIRICAL parametrized

I

DENSITY FUNCTIONAL (DF) includes exchange and correlation

HARTREE-FOCK (HF) includes electron exchange omits electron correlation

HF with CI (configuration interaction) includes electron correlation

Figure 1. The methodologies of computational inorganic chemistry.

2+

Figure 2. The optimized structure of [Fe6S6(PH3)6] , with the definitions of atom types: symmetry C2 applies. In the notation S , η also represents the coordination number of the sulfur atom. Fe-Fe bonds are not drawn, for clarity. n

V


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139


calculated and observed Fe-S bond distances and Fe-Fe distances better than 0.04À in all cases. The F e l - S distance involving the unusual doubly bridging sulfide is calculated exactly. The two different types of Fe-Fe bond at 2.63À are reproduced very well, and the longer non-bonded Fe2-Fe2 distance of 2.97Â is calculated within 0.03Â. The terminal Fe-P bond distances are observed both slightly shorter and slightly longer than those calculated. 2

[yFe S6(PEt3) (SPh)]-. The second test cluster is [VFe S6(PEt ) (SPh)]- (44). The cluster core approximates threefold symmetry, although this is quite strongly disrupted by the thiolate substituent. The core can be regarded as a trigonal bipyramid of metal atoms with V axial, bridged by \i2~S between F e l and V and by between F e 9 and Fe**** . Again the best results come with use of the blyp functional (see Table II). Note that the bonds involving bridging S atoms are all calculated to better than 0.04À, as are the V - F e and Fe^Fe? bonds. The Ft -F& distance is calculated to be ca 0.1 OA longer than the observed range. The occurrence of this range of 0.07Â in the crystal is indicative of the relatively weak, perturbable nature of this bond. The calculated bond lengths to the terminal phosphine and thiolate ligands are in very good agreement with those observed. 4

4

4

3

4


e c

e

u a t o r i a l

u a t o r i a l

1

e

e

4-

[ N b o S n ] . The third test involves an unusual metal sulfide cluster involving a second transition series metal, [ N b o S n ] , which approaches C$ symmetry and contains five different types of S atom (45). The structure is shown in Figure 4. A pentagonal pyramid of Nb atoms (Nb axial, N b equatorial) is triply-bridged on its triangular faces by S , doubly-bridged on its equatorial edges by S , and sextuplybridged at its center by S : N b and N b carry terminal sulfur atoms S and respectively. The geometry calculated using the blyp functional (see Table III) calculates N b - S distances up to 0.1Â longer than observed, while the N b - S distances are calculated longer by 0.07Â. The unique N b ^ S bond is reproduced exactly, although the longer non-bonding Nb—Nb distances are calculated up to 0.2Â longer than observed. 4-

w

a

e

3

2

6

a

e

a

3

e

2

6

Other non-local density functionals can be used, with slightly different results, and for some metal sulfide clusters not reported here the other functionals perform better than blyp. Local density functionals, without the gradient corrections, consistently calculate tighter bonding with shorter bonds and excessive binding energies. While improvements in DF methods are expected and further evaluations are required and are in progress (37), it can be concluded that the current DF procedures provide reliable information about metal sulfide clusters. As a first application of DF methods to metal sulfide systems I describe copper sulfide clusters generated and investigated in the gas phase. Pristine copper sulfide clusters Laser ablation of solid copper-sulfide compounds yields a collection of clusters [Cu S ]~, with the compositions plotted in Figure 5 (14,18). Using a Fourier transform ion cyclotron resonance (FTICR) mass spectrometer these ions can be collected in an ion trap. Then a particular cluster ion can be isolated in the ion trap by removal of all others, and the selected cluster allowed to react with gaseous reagents, or dissociated (17,18,46). Figure 6 summarizes some of these results, showing the most abundant clusters, the least reactive clusters, and the dissociation pathways. [Q16S4]- is abundant, unreactive, and the common product of dissociation of larger ions, and clearly is very stable. [ C U 3 S 3 ] - and [Q110S6]" are similarly stable x

y


140


2+

Table I. Bond distances observed in [Fe6S6(PEt3>6] in comparison with those in [Fe6S6(PH ) ] optimized ( C ) with the functional blyp. See Fig. 2. 2+

3


Bond

6

2v

Obs (Â) (ref 43)

Calc (Â)

Fel-S

2

2.15

2.15

Fel-S

3

2.22,2.23

2.20

Fe2-S

3

2.19,2.20

2.20

Fe3 - S

3

2.22

2.18

Fe3 - S

4

2.28,2.30

2.25

Fe2 - S

4

2.23

2.19

Fel-Fel

2.63

2.62

Fe2-Fel

2.72

2.73

Fe2-Fe2

2.97

3.00

Fe2-Fe3

2.63,2.65

2.61

Fel-P

2.27, 2.29

2.32

Fe2-P

2.28

2.31

Fe3-P

2.36, 2.38

2.31

Table II. Bond distances in [VFe4S (PEt3) (SPh)]- in comparison with those optimized for structure [VFe4S6(PH3)4(SH)]- (symmetry C , functional blyp): see Fig. 3 for definitions of atom types. 6

4

s

Bond e

Fe - S a

Fe -S

3

e

Fe - S V-S

Fe -S

a

e

Fe -Fe

e

e

V-Fe a

Fe -Fe

e

2

2

a

V-P

3

a

Fe -P

e

e

Obs (Â) (ref 44)

Calc (À)

2.15-2.19

2.17

2.19-2.22

2.17

2.22-2.24

2.25, 2.26

2.16-2.20

2.22

2.25

2.23

2.61-2.68

2.72, 2.77

2.58-2.61

2.57, 2.61

2.62-2.67

2.59, 2.63

2.48

2.53

2.26-2.29

2.29, 2.32



7. DANCE


Figure 3. The structure of [VFe4S6(PR3)4(SR')]- as observed (R=Et, R'=Ph) and calculated (R=R'=H). Fe , P and S lie on the molecular axis, Fe and P are equatorial, and S , S refer to the triply- and doubly-bridging sulfur atoms respectively (threefold symmetry assumed in atom labelling). Bonds between metal atoms are not drawn, for clarity. a

e

0

3

a

a

2

4-

Figure 4. The structure and atoms types of [NboSn] : five-fold symmetry is assumed in the atom labelling.


141


4

Table ΠΙ. Observed and calculated distances in [NbeSn] " Bond a

Nb - S e


Nb -S

Obs (Â) Cref45)

Cale (A)

2.58-2.60

2.68-2.70

2.49-2.53

2.57-2.63

3

3

e

2

Nb - S

2.40-2.42

2.48-2.49

a

6

2.64

2.64

e

6

2.89-3.01

3.00-3.18

a

a

2.20

2.29

e

e

Nb -S Nb -S Nb -S

2.15-2.19

2.27-2.28

e

e

3.38-3.44

3.52-3.66

a

e

3.61-3.65

3.75-3.80

Nb -S

Nb -Nb Nb -Nb

ι 9ι %

y Μ

r

WΤ

9 "1 y

i r

0

10

u

Γ 91κ M

Κ

20

30

40

50

Cu

Figure 5. Map of the compositions of the ions [Cu S ]" generated by laser ablation of KC114S3. x

y



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143


0

2

4

6

8

10

12

Cu

Figure 6. Map of the ions [ C u S ] - (x £ 12) showing relative abundance (circle size), those least reactive with thiols and H 2 S (open circle), and the products of collisionally induced dissociation (arrows). x

y


144


-

compositions, as is [CuçSs] even though its abundance is lower. In contrast, the other ions are generally less abundant and more reactive. These findings provoke many questions. For example, what are the geometrical and electronic structures of these clusters? What factors stabilize the four special compositions? Since these experiments are performed at 10~ mbar there are no spectroscopic data (and it is not likely that such data could be interpreted unambiguously to yield structure), and so DF methods can be deployed. The following results were obtained with the progam DMol, as above, using the blyp functional, D N D basis, spin restricted calculations of even-electron species, with geometry optimizations usually in symmetry lower than ideal. Downloaded by STANFORD UNIV GREEN LIBR on October 7, 2012 | http://pubs.acs.org Publication Date: November 29, 1996 | doi: 10.1021/bk-1996-0653.ch007

8

Figure 7 shows the most stable isomer for [CU3S3]", the D3h structure, and the next most stable geometry, [^3-S)^2-S)2Cu3], which is 47 kcal m o l higher, and which transforms without energy barrier to the D3h isomer. For [CU4S4] the most and next stable structures and their relative energies a shown in Figure 7: the common cubane connectivity with (μ3-5)4 bridging is less stable than square CU4 isomers with (μ-8)4 bridging, and the planar D4h arrangement is most stable. The best calculated structures for [CU6S4] and [CU9S5]- are also portrayed in Figure 7. The best structure for [Q19S5]- is effectively a fusion of two stable Td isomers of - 1

[CU6S4].

From these results a structural principle is readily identified: stability is conferred by local quasi-linear S-Cu-S coordination. In all of the most stable isomers each Cu atom possesses this coordination: both isomers of [CuçSs] have this property, and are similarly stable. Reactivity occurs where there are Cu atoms with non-linear coordination (18). -

These DF calculations are being extended to much larger [Cu Sy] clusters. Ahlrichs and Fenske have used HF and HF-CI calculations to model similar copper sulfide and selenide clusters with terminal phosphine ligands, with good results (47,48). x

Nitrogenase Elucidation of the structure and mechanism of the enzyme nitrogenase has been a longstanding goal of research. The crystal structure of the protein, first reported in 1992 (4-11), uncovered the special structure of the iron-molybdenum-sulfide cluster at the active site, but did not reveal (49-53) the location or mode of binding of N 2 at this site. Computational methods have now provided considerable insight into the probable location and stereochemistry of the binding of N , and elucidated the mechanism for the weakening of the N - N bond and the pathway for proton transfer to the reducing N (54). 2

2

Figure 8 shows the (cysteine)Fe7S9Mo(histidine)(homocitrate) cluster at the active site, together with some significant surrounding protein. A central trigonal prism of Fe atoms is capped on the upper triangular face by ^3-S)3Fe(S-cysteine) and on the lower triangular face by (μ3-S)3Mo(N-histidine)(0,0-homocitrate). The three vertical edges of the Fe6 trigonal prism each carry doubly-bridging sulfide. A significant feature is that the cluster is bound to the protein only at the M o and the upper Fe atom: the six-coordinate Mo provides an anchor point at the base of the cluster, while the upper section should be free to rotate about the Fe-S-cysteine bond, allowing torsion in the central region of the cluster. In the center, there is trigonal prism of six under-coordinated Fe atoms. This trigonal prism presents three Fe4 faces around the equator, and one of these is sufficiently unobstructed by protein as to In Transition Metal Sulfur Chemistry; Stiefel, E., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1996.



DANCE

0

- 1

Figure 7. Isomers of [ C u S ] - , with relative energies in kcal m o l (symmetries in parentheses are those imposed during geometry optimization). x

y



146


Figure 8. The active site of nitrogenase as determined by X-ray diffraction (55), showing the histidine and homocitrate ligands for six-coordinate Mo at the base of the cluster, the Fe6 trigonal prism in the central region, and the cysteine coordination of Fe at the top. The N (not present in the structure determination) is shown at the proposed binding site, enclosed by arginine359, in the parallel binding conformation (see text). A hydrogen bond exists between arginine-96 and the μ - 8 ligand in the center-front of the picture. 2

2


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147


offer a site for binding of N2 (54). Arginine-359 provides a cover for this binding site. Clues about the geometry of binding and weakening of N 2 came from computations on the metallocarbohedrenes (binary metal-carbon clusters, M C ) (5659), in which C 2 ~ (iso-electronic with N2) binds to a quadrilateral of metal atoms (60-66). The two relevant conformations (labelled diagonal and parallel) are shown in Figure 9, for N2 over Fe4, analogous to C2 over M 4 . More stable binding occurs for N2 diagonal to an F e rhombus, with favourable overlap of the N2 π-bonding orbitals with Fe 3d. The alternative binding of N2 parallel to the edges of an F e rectangle is less stable overall, and involves overlap of Fe 3d orbitals with N2 πantibonding orbitals, thus weakening the N - N bond. This parallel conformation can alternatively be regarded as four Fe-N σ-bonds to N 2 ~ in the doubly reduced state. The key concept is that the N2 can be initially trapped in the diagonal conformation, and then its N - N bond weakened by conversion to the parallel conformation. The interconversion of these two F e shapes could be achieved by rotation of the upper section of the cluster, causing torsion of the Fe6 trigonal prism. In Fig. 8 the N2 is shown bound in the parallel conformation. x

y

2

4


4

2

4

These hypotheses have been substantiated and quantitated by DF calculations (54), which also reveal another significant characteristic of the active site. Increased electron population during the reduction is calculated to have largest effect on atomic charges at the doubly-bridging sulfide ligands which flank the binding site. These μ2-8 ligands, unusual in polymetallic sulfide clusters (16), are thus postulated to play a significant role in the proton transfer components of the total reduction of N2. This proposal is supported by the fact that both of the flanking μ2-8 ligands accept hydrogen bonds from behind, as marked in Figure 10 (and portrayed in more detail in ref 54). Thus, during reduction of bound N2 there is also an increase in basicity of the flanking μ2-8 ligands, facilitating transfer of H to them via protein. Inversion of the hydrogen on the resulting Fe2SH (a facile process) places it immediately adjacent to the reducing N2, and subsequent transfer of the proton to the increasingly basic nitrogen atom is stereochemically facile (see Figure 10). This proton transfer stage has been evaluated with DF calculations (54). While the μ2-8 ligands were unexpected in the Fe-Mo-S cluster, they are seen to have a mechanistic function that could not be achieved with \I3-S. +

Finally, another role for the obligatory homocitrate ligand is recognised. After reduction, the amine product must leave the active site via the opening near the guanidine terminus of arginine-359. The homocitrate ligand at the base of the egress route provides the required hydrophilic pathway. The other role of homocitrate is to anchor the coordinatively saturated Mo atom, as required for the torsion of the upper part of the cluster. It is proposed that this torsion is induced by hydrogen bonds with the surrounding protein. Thus a concerted mechanism is proposed for the function of the active site of nitrogenase, and supported computationally (54). This proposal emphasises and illustrates nicely the significance of the two questions raised in the introduction, concerning details of fundamental cluster core structure, and the role of the cluster environment. Biomineralization 2

2 +

2

Plants and fungi detoxify heavy metals such as Cd +, H g , Pb + by inducing the synthesis of cysteine-rich oligopeptides known as phytochelatins (PC), which then


148


Parallel binding of N over F e rectangle

Diagonal binding of N over F e rhombus


2

2

4

4

Fe overlap with N π-bondlng orbitale 2

Fe overlap with N π-antlbondlng orbitals 2

Figure 9. The diagonal and parallel conformations of N bonded over an Fe4 quadrilateral. Adapted from reference 54. 2

Figure 10. Representation of the hypothesis for proton transfer from the hydrogen bonds behind the two μ - 8 ligands which flank the binding site, around μ - 8 by inversion, and to reducing N : hydrogen atoms (open circles) are drawn in each of the locations along these two flanking pathways. Arginine-359 which covers this site has been removed for clarity. 2

2

2


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sequester the metal ions in innocuous complexes. The phytochelatins are usually (γ-glutamic acid-cysteine) glycine with η varying between 2 and 8, symbolised P C . n

n

OH

HN


2

Organisms such as the yeasts Candida glabrata and Schizosaccharomyces pombe have increased the efficacy of this protection by further generating sulfide, S ~ (presumably from glutathione), which initiates formation of a metal sulfide biomineral together with the metal-phytochelatin complexes. Thus, when these yeasts are burdened with C d they grow a crystallite of CdS, coated with phytochelatins. This is an unusual example of biomineralization, or biochemicallycontrolled mineral formation. The dimensions of the CdS nanocrystallite are restricted, to ca 20 Â diameter: the thermodynamically favoured growth (Ostwald ripening) of nanocrystalline CdS to bulk CdS which would otherwise occur is controlled and restricted by a coating of phytochelatin peptides. The formation (in vivo and in vitro) and properties of these have been described by Dameron, Winge et al. (67-69). 2

2 +

These biomineral materials are significant in fields other than metal detoxification, since CdS is a size-quantized photoresponsive semiconductor. That is, the band gap for absorption of radiation, and the energy separation of the reducing electrons in the valence band and oxidizing holes in the conduction band, are tunable by variation of the size of the crystallite in the nm size domain (70). Thus, control of nanocrystallite size and avoidance of Ostwald ripening are important objectives, and the yeasts provide a natural solution to a technological problem in materials science. Using knowledge of many smaller cadmium-sulfide-thiolate clusters with known structures in crystals and in solution, I have developed a computer model of a representative CdS bio-nanocrystallite, with composition Cd8fjS62{(Y-glucys)3gly}22> chosen to fit the compositional, diffraction, and size data (71). This model and the modelling process were very informative about structural possibilities, which are in fact limited as a consequence of the unusual coordination properties of the phytochelatins. A chelate ring formed by the cys-y-glu-cys sequence contains 14 atoms, which is anomalously large and conformationally demanding. In the absence of data interprétable at the atomic level, computational methods are valuable. The refinement of this model (which has a total of 1990 atoms) employed force-field methods, using parameters determined for Cd-S-SR clusters (72). The significant characteristic of this structure is the close packing of the 22 peptides over the surface; surface packing is tight, and the core is completely covered by peptide. There is a preponderance of carboxylate oxygen atoms on the surface, with a total charge of -96 if all are deprotonated. The close packing of peptides over the surface provides the clue to the mechanism for size control. The diagrammatic representation (Fig 11) of the separation of peptides anchored with fixed spacing over the surface of small and large mineral cores indicates how the peptides come together as the core grows. At the limiting size, any addition to the core would decrease the general curvature of the surface, force the peptides together, prevent the ingress of C d and S ~, and prevent further growth. 2 +

2


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Figure 11. Diagrammatic representation of the growth of the CdS biomineral core, with surface coordination by phytochelatin peptides. As the core grows and the surface curvature decreases the peptides (which have fixed separations at the connection points on the core) are forced together and prevent further growth. Conclusions I conclude that contemporary computational techniques, especially the density functional calculations, enable expedient insight into key questions at the frontiers of metal sulfide cluster chemistry, providing information not yet accessible experimentally, and providing direction for experimental programs. Acknowledgments. This research is supported by the Australian Research Council. I thank Professor Doug Rees for provision of information on the structure of nitrogenase, and Professors Ahlrichs and Fenske for information in advance of publication. Computational resources provided by the Australian Nuclear Science and Technology Organisation are gratefully acknowledged. References 1. Dance, I.G. in Perspectives in Supramolecular Chemistry, G. Desiraju, ed. John Wiley and Sons, 1995, 2, 137-233. 2. Müller, A; Reuter, H; Dillinger, S. Angew. Chem. Int. Ed. Engl., 1995, 34, 2328-2361. 3. Burgess, B.K. Chem. Rev., 1990, 90, 1377-1406. 4. Georgiadis, M.M.; Komiya, H.; Chakrabarti, P.; Woo, D.; Kornuc, J.J.; Rees, D.C Science, 1992, 257, 1653-1659. 5. Kim, J.; Rees, D.C. Science, 1992, 257, 1677-1682. 6. Kim, J.; Rees, D.C. Nature, 1992, 360, 553-560. 7. Rees, D.C.; Chan, M.K.; Kim, J. Adv. Inorg. Chem., 1993, 40, 89-118. 8. Chan, M.K.; Kim, J.; Rees, D.C. Science, 1993, 260, 792-794. 9. Bolin, J.T.; Ronco, A.E.; Morgan, T.V.; Mortenson, L.E.; Xuong, N.H. Proc. Nat. Acad. Sci. USA, 1993, 90, 1078-82. 10. Rees, D.C; Kim, J.; Georgiadis, M.M.; Komiya, H.; Chirino, A.J.; Woo, D.; Schlessman, J.; Chan, M.K.; Joshua-Tor, L.; Santillan, G.; Chakrabarti, P.; Hsu, B.T. ACS Symposium Series, 1993, 535, 171 - 185. 11. Bolin, J.T.; Campobasso, N.; Morgan, T.V.; Muchmore, S.W.; Mortenson, L.E. in Molybdenum Enzymes, Cofactors and Models, Stiefel, E.I.; Coucouvanis, D.; Newton, W.E. Eds, ACS Symposium Series, 1993, 535, 186-215. 12. El-Nakat, H.J.; Dance, I.G.; Fisher, K.J.; Willett, G.D. J. Chem. Soc., Chem. Comm., 1991, 746-748. 13. El Nakat, J.H.; Dance, I.G.; Fisher, K.J.; Rice, D.; Willett, G.D. J. Am. Chem. Soc., 1991, 113, 5141-5148 14. El Nakat, J.H.; Dance, I.G.; Fisher, K.J.; Willett, G.D. Inorg. Chem., 1991, 30, 2957-2958 15. El Nakat, J.H.; Fisher, K.J.; Dance, I.G.; Willett, G.D. Inorg. Chem., 1993, 32, 1931-1940. In Transition Metal Sulfur Chemistry; Stiefel, E., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1996.


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Computational Methods for Metal Sulfide Clusters - ACS Publications

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